Qualification:
Ph.D
shyam@amrita.edu
Phone:
+91 (0476-2896318)

Shyam Diwakar is the Lab Director of Computational Neuroscience and Neurophysiology Laboratory, a Faculty fellow at the Amrita Center for International Programs and an Associate Professor at the School of Biotechnology. He is the Institute Integration Coordinator and Co-investigator of VALUE (Virtual and Accessible Laboratories for Universalizing Education); a major virtual labs initiative supported by Sakshat mission of MHRD, Government of India, and Principal Investigator of few other projects funded by Department of Science and Technology.

He was awarded the Young Faculty Research Fellowship under the Sir Visvesvaraya PhD scheme by Department of Electronics and Information Technology, Govt. of India in April 2016.

He holds a Ph. D. in Computational Sciences from University of Milan, Italy and has worked on as a Postdoctoral Researcher at the Department of  Physiology, University of Pavia, Italy. His postdoctoral research was supported by INGENIO grant from Regione Lombardia and SENSOPAC grant from EU framework 7.

Before his doctoral studies, he worked as a Research Assistant at Amrita Vishwa Vidyapeetham, on Machine Learning and Intelligence for two years. He has co-authored a book titled “Insights into Data Mining” which has been published by Prentice Hall, PHI, December 2005 and another book on Computational Neuroscience.

He is a Senior Member of IEEE, Faculty Member of Organization for Computational Neurosciences (OCNS) and Life Member of Indian Academy of Neuroscience. He has organized, participated and presented in various meetings and workshops around Europe and Asia and has also served as an invited speaker in conferences and graduate schools in Europe and India.

Dr. Diwakar was awarded the NVIDIA Innovation award on December 16, 2015 for his computational neuroscience work on GPUs. He also coordinates the NVIDIA GPU research center and NVIDIA GPU teaching Center at Amrita Vishwa Vidyapeetham.

Dr. Diwakar's research uses principles from Electrical Engineering and Informatics to study cerebellum and its functioning.  His research has shown how noise is represented in extracellular neuronal tissue besides developing multi-scale mathematical models of the cerebellum granular layer. The current work at his lab is on Computational Neurophysiology, Neuromorphic Hardware and Bio-Robotics besides pedagogical techniques for enhancing Biotechnology laboratory education through ICT.

For full list of code, papers and journal articles, see [link]

## Publications

### Publication Type: Journal Article

Year of Publication Title

2019

C. Nutakki, Radhakrishnan, S., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling fMRI BOLD signals and temporal mismatches in the cerebellar cortex”, CSI Transactions on ICT, 2019.[Abstract]

To understand brain activity relating neurons to circuits to learning and behavior, we explored a bottom-up computational reconstruction of population signals arising from cerebellum granular layer. As a first implementation, using bio-realistic computational models of cerebellum granule cell, in vivo spike train patterns were computed and then translated into functional Magnetic Resonance Imaging, Blood Oxygen-Level Dependent (BOLD) signals. The BOLD response was generated from averaged activity arising from center-surround organization modeled by using excitatory-inhibitory ratios related to experimental data. The averaged responses were converted to BOLD signals using the balloon and modified Windkessel models. Although both models generated BOLD responses corresponding to neural activity, the temporal mismatch was attributed to the response by the delayed compliance parameter in the Windkessel model. The modeling suggests that experimental variability observed in the cerebellar micro-zones could be related to compliance chances, activation patterns and number of neurons. Although detailed neuro-vasculature information was not modeled, the advantage in this methodology is that cerebellar cortex may allow seemingly linear transformations of underlying spiking that could be then used to validate network reconstructions.

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2018

Manjusha Nair, M. K. Jinesh, Bharat Jayaraman, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Temporal constrained objects for modelling neuronal dynamics”, PeerJ Computer Science, vol. 4, p. e159, 2018.[Abstract]

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2018

Dr. Krishnashree Achuthan, VK, K., and Dr. Shyam Diwakar, “Using Virtual Laboratories in Chemistry Classrooms as Interactive Tools Towards Modifying Alternate Conceptions in Molecular Symmetry”, Educ Inf Technol , 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Krishna Chaitanya Medini, Asha Vijayan, and Arathi G. Rajendran, “Computational Modelling of Cerebellum Granule Neuron Temporal Responses for Auditory and Visual Stimuli”, International Journal of Advanced Intelligence Paradigms, vol. 10, p. 1, 2018.

2018

Parasuram H., Dr. Bipin G. Nair, Naldi G., D’Angelo E., and Dr. Shyam Diwakar, “Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials”, Annals of Neuroscience, vol. 25, pp. 11-24, 2018.[Abstract]

Background: The cerebellar granular layer input stage of cerebellum receives information from tactile and sensory regions of the body. The somatosensory activity in the cerebellar granular layer corresponds to sensory and tactile input has been observed by recording Local Field Potential (LFP) from the Crus-IIa regions of cerebellum in brain slices and in anesthetized animals. Purpose: In this paper, a detailed biophysical model of Wistar rat cerebellum granular layer network model and LFP modelling schemas were used to simulate circuit’s evoked response. Methods: Point Source Approximation and Line Source Approximation were used to reconstruct the network LFP. The LFP mechanism in in vitro was validated in network model and generated the in vivo LFP using the same mechanism. Results: The network simulations distinctly displayed the Trigeminal and Cortical (TC) wave components generated by 2 independent bursts implicating the generation of TC waves by 2 independent granule neuron populations. Induced plasticity was simulated to estimate granule neuron activation related population responses. As a prediction, cerebellar dysfunction (ataxia) was also studied using the model. Dysfunction at individual neurons in the network was affected by the population response. Conclusion: Our present study utilizes available knowledge on known mechanisms in a single cell and associates network function to population responses.

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2018

P. Chellaiah, Dr. Bipin G. Nair, K. Achuthan, and Dr. Shyam Diwakar, “Using theme-based narrative construct of images as passwords: Implementation and assessment of remembered sequences”, International Journal of Online Engineering, vol. 13, pp. 77-93, 2018.[Abstract]

With many online engineering platforms such as virtual and remote laboratories designed for young or aged users, user authentication and passwords-based methods are being re-evaluated for tracking usage patterns and security. For ICT-enabled online engineering platforms, image-based humancentric approaches are gaining relevance for access frameworks. With the rubber- hose attacks, increased senior users, many existing systems are vulnerable to many attacks. This paper employs human uniqueness of narrative skills on an image-based password system for online platforms with focus on theme in the password generation process. To generate the secret password, a specially designed computer game was used. We used narrative constructs composed of cartoon image sequences to generate user-speci!c secret key. The durability of generated passwords and the authentication process while assessing the reconstruction process by a potential hacker was verified. For validating use of coerced attacks, under imposed psychological duress, users failed retrieving the password sequence suggesting the reliability as an anti-coercive attack cybersecurity tool. A set of experiments were used to analyze user behavior behind the image-based password system. EEG measurements demonstrated increased activity of " rhythms in F3 and FC5 channel bins and augmented levels of α rhythms in F3 and O1 channels, suggesting users added personalization to authentication more than in alpha-numeric password-based logins.

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2017

Radhamani R., Kumar D, Nizar N., Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementation of ICT-based Virtual Labs for Sustainable Laboratory Education in Universities”, CSI journal of Computing, vol. 3, no. 2, pp. 67-75, 2017.

2017

Arathi G. Rajendran, Chaitanya Nutakki, Hemalatha Sasidharakurup, Sandeep Bodda, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Cerebellum in Neurological Disorders: A Review on the Role of Inter-Connected Neural Circuits”, Journal of Neurology and Stroke, vol. 6, pp. 1-4, 2017.[Abstract]

Recent studies have indicated the additional role of cerebellum beyond motor coordination non-motor and socio-cognitive tasks. Exploration of cerebellar roles in timing and plasticity have been attributed specific roles in neurological conditions such as ataxia, severe disorders such as Parkinson's and epilepsy. Cerebellar dysfunctions elaborate the need of research on cerebellar circuitry and physiology to better understand neurological functions and dysfunctions. Structural and functional studies of cerebellum also implicate the connection between cerebellum with interconnected circuits such as thalamo cortical and basal ganglia networks during motor and non-motor functions. In this review, we list some of recently perceived roles of cerebellum in information processing, neurological conditions in disorders.

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2017

K. Achuthan, Francis, S. P., and Dr. Shyam Diwakar, “Augmented reflective learning and knowledge retention perceived among students in classrooms involving virtual laboratories”, Education and Information Technologies, pp. 1-31, 2017.[Abstract]

Learning theories converge on the principles of reflective learning processes and perceive them as fundamental to effective learning. Traditional laboratory education in science and engineering often happens in highly resource-constrained environments that compromise some of the learning objectives. This paper focuses on characterizing three learning attributes associated with reflective learning i.e. metacognition (M), analogical reasoning (A) and transfer of knowledge (T) and assessed college laboratory education blended with ICT-enabled virtual laboratories. Key contributions of this study include: 1) Development of assessment of MAT attributes using a combination of multiple choice questions, True/False statements and descriptive questions 2) assessment of conceptual learning occurring in the laboratory environment and of learning attributes using Virtual Laboratories (VLs) in classroom education. Feedback data indicated using virtual laboratories in classrooms for training students before using physical laboratories demonstrated a significant improvement (>100% change) in learning in comparison to physical laboratories without VLs. We also show using VLs as pre-lab or post-lab exercise augmented reflective learning and information retention among 145 students in this blended learning case study, compared to an independent control group of 45 students who had no virtual laboratory training. © 2017 Springer Science+Business Media, LLC More »»

2017

Asha Vijayan, Chaitanya Nutakki, Dhanush Kumar, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Enabling a freely accessible open source remotely controlled robotic articulator with a neuro-inspired control algorithm”, International Journal of Interactive Mobile Technologies, vol. 13, no. 1, pp. 61-75, 2017.[Abstract]

Internet-enabled technologies for robotics education are gaining importance as online platforms facilitating and promoting skill training. Understanding the use and design of robotics is now introduced at university undergraduate levels, but in developing economies establishing usable hardware and software platforms face several challenges like cost, equipment etc. Remote labs help providing alternatives to some of the challenges. We developed an online laboratory for bioinspired robotics using a low-cost 6 degree-of-freedom robotic articulator with a neuro-inspired controller. Cerebellum-inspired neural network algorithm approximates forward and inverse kinematics for movement coordination. With over 210000 registered users, the remote lab has been perceived as an interactive online learning tool and a practice platform. Direct feedback from 60 students and 100 university teachers indicated that the remote laboratory motivated self-organized learning and was useful as teaching material to aid robotics skill education.

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2016

R. Radhamani, D. Kumar, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementing and deploying magnetic material testing as an online laboratory”, Advances in Intelligent Systems and Computing, vol. 530, pp. 925-934, 2016.[Abstract]

Hysteresis loop tracing (HLT) experiment is an undergraduate experiment for physics and engineering students to demonstrate magnetic properties of ferrite materials. In this paper, we explore a new approach of setting- up triggered testing of magnetic hysteresis via a remotely controlled loop tracer. To aid student learners, through an experimental design, we focused on factors such as analytical expression of mathematical model and modeling of reversible changes, which were crucial for learning hysterisis components. The goal was to study the phenomena of magnetic hysteresis and to calculate the retentivity, coercivity and saturation magnetization of a material using a hybrid model including simulation and remotely controlled hysteresis loop tracer. The remotely controlled equipment allowed recording the applied magnetic field (H) from an internet-enabled computer. To analyze learning experiences using online laboratories, we evaluated usage of online experiment among engineering students (N=200) by organized hands-on workshops and direct feedback collection. We found students adapted to use simualtions and remotely controlled lab equipment augmenting laboratory skills, equipment accessibility and blended learning experiences. © Springer International Publishing AG 2016.

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2016

Harilal Parasuram, Dr. Bipin G. Nair, Egidio D‘Angelo, Michael Hines, Giovanni Naldi, and Dr. Shyam Diwakar, “Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim”, Frontiers in Computational Neuroscience, p. 10, 2016.[Abstract]

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

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2016

Dr. Shyam Diwakar, Dhanush Kumar, Rakhi Radhamani, Hemalatha Sasidharakurup, Nijin Nizar, Dr. Krishnashree Achuthan, Prema Nedungadi, Raghu Raman, and Dr. Bipin G. Nair, “Complementing Education via Virtual Labs: Implementation and Deployment of Remote Laboratories and Usage Analysis in South Indian Villages”, International Journal of Online Engineering (iJOE), vol. 12, no. 03, 2016.[Abstract]

ICT-enabled virtual and remote labs have become a platform augmenting user engagement in blended education scenarios enhancing University education in rural India.
A novel trend is the use of remote laboratories as learning and teaching tools in classrooms and elsewhere. This paper reports case studies based on our deployment of 20 web-based
virtual labs with more than 170+ online experiments in Biotechnology and Biomedical engineering discipline with content for undergraduate and postgraduate education.

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2016

Dr. Shyam Diwakar, R. Radhamani, Hemalata Sasidharakurup, Dhanush Kumar, N. Nizar, Dr. Krishnashree Achuthan, and Dr. Bipin G. Nair, “Assessing students and teachers experience on simulation and remote biotechnology virtual labs: A case study with a light microscopy experiment”, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 160, pp. 44-51, 2016.[Abstract]

With recent trends of using Information and Communication Technologies in education, virtual labs have become more prevalent in classrooms of most schools and universities, especially in South India. The purpose of this paper was to perform a comparative analysis of virtual learning components such as animations, simulations and real-time remotely controlled experiments. As a part of this study, we conducted a series of biotechnology virtual lab workshops for University-level users within India and collected feedback related to the usage of virtual labs via direct approach. The survey amongst the students and teachers suggested simulation-based labs were more preferred in enhancing teaching and learning strategy compared to graphics-mediated animations and remotely controlled experiments. This paper also reports some of the issues faced by virtual lab users. Studies indicated that even though the web-based technologies are a new venture in education, it still poses adaptability issues. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

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2015

Raghu Raman, Dr. Krishnashree Achuthan, Prema Nedungadi, Dr. Shyam Diwakar, and Bose, R., “The VLAB OER Experience: Modeling Potential-Adopter Students' Acceptance”, IEEE Transactions on Education, vol. 57, pp. 235–241, 2015.[Abstract]

Virtual Labs (VLAB) is a multi-institutional Open Educational Resources (OER) initiative, exclusively focused on lab experiments for engineering education. This project envisages building a large OER repository, containing over 1650 virtual experiments mapped to the engineering curriculum. The introduction of VLAB is a paradigm shift in an educational system that is slow to change. Treating VLAB OER as an educational technology innovation, its adoption by potential-adopter engineering students (N=131) is modeled based on Roger's theory of perceived attributes. Regression and factor analysis were used to analyze the data. Results indicate that the attributes of Compatibility, Ease of Use, Relative Advantage, and Trialability significantly influence potential-adopter students' intention to adopt an innovation like VLAB. The study also observed that using OER (such as VLAB) on desktops and low-cost tablets had similar effects in student performance to using physical labs. This has interesting implications for education policy-makers who are looking to reduce the digital divide.

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2015

Manjusha Nair, Dr. Bipin G. Nair, Dr. Shyam Diwakar, di Serio C., Nonis A., and Tagliaferri R., “GPGPU implementation of a spiking neuronal circuit performing sparse recoding”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8623, pp. 285-297, 2015.[Abstract]

Modeling and simulation techniques have been used extensively to study the complexities of brain circuits. Simulations of bio-realistic networks consisting of large number of neurons require massive computational power when they are designed to provide real-time responses in millisecond scale. A network model of cerebellar granular layer was developed and simulated here on Graphic Processing Units (GPU) which delivered a high compute capacity at low cost. We used a mathematical model namely, Adaptive Exponential leaky integrate-and-fire (AdEx) equations to model the different types of neurons in the cerebellum. The hypothesis relating spatiotemporal information processing in the input layer of the cerebellum and its relations to sparse activation of cell clusters was evaluated. The main goal of this paper was to understand the computational efficiency and scalability issues while implementing a large-scale microcircuit consisting of millions of neurons and synapses. The results suggest efficient scale-up based on pleasantly parallel modes of operations allows simulations of large-scale spiking network models for cerebellum-like network circuits. © Springer International Publishing Switzerland 2015.

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2015

Sandipan Ray, Dr. Shyam Diwakar, S. Srivastava, and Dr. Bipin G. Nair, “E-learning resources and virtual labs”, Nature India Special Issue, pp. 13-14., 2015.[Abstract]

India’s recent strides in information technology have propelled the growth of web-based digital learning in most disciplines of science and engineering education. Distance education and open learning endeavours offer many advantages in resource-limited developing countries, where the number of potential learners is much higher than the number of experienced teachers or advanced educational institutes1.

However, these endeavours alone have proved insufficient in providing practical skills for science experiments or analysis of scientific data. Virtual laboratories, which act as free, round-the-clock replicas of actual laboratories, could be an effective alternative. Learners in a virtual laboratory can understand scientific theories and also experience practical experimental procedures2,3. As educational budgets in developing and under-developed countries continue to shrink, e-learning and open-learning programmes are gaining popularity4.

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2015

Edward S. Dove, Ömer I Barlas, Kean Birch, Catharina Boehme, Alexander Borda-Rodriguez, William M Byne, Florence Chaverneff, Yavuz Coşkun, Marja-Liisa Dahl, Türkay Dereli, Dr. Shyam Diwakar, Levent Elbeyli, Laszlo Endrenyi, Belgin Eroğlu-Kesim, Lynnette R. Ferguson, Kıvanç Güngör, Ulvi Gürsoy, Nezih Hekim, Farah Huzair, Kabeer Kaushik, Ilona Kickbusch, Olcay Kıroğlu, Eugene Kolker, Eija Könönen, Biaoyang Lin, Adrian Llerena, Faruk Malha, Dr. Bipin G. Nair, George P. Patrinos, Semra Şardaş, Özlem Sert, Sanjeeva Srivastava, Lotte M.G. Steuten, Cengiz Toraman, Effy Vayena, Wei Wang, Louise Warnich, and Vural Özdemir, “An Appeal to the Global Health Community for a Tripartite Innovation: An “Essential Diagnostics List,”“Health in All Policies,” and “See-Through 21st Century Science and Ethics””, Omics: a journal of integrative biology, vol. 19, pp. 435–442, 2015.[Abstract]

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an “Essential Diagnostics List.” Additionally, we explain the ways in which adopting a vision for “Health in All Policies” could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, “see through” taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20th century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public–private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge-based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations.

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2015

Hemalata Sasidharakurup, R. Radhamani, Dhanush Kumar, Dr. Shyam Diwakar, N. Nizar, Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, “Using Virtual Laboratories as Interactive Textbooks: Studies on Blended Learning in Biotechnology Classrooms”, EAI Endorsed Trans. e-Learning, Accept., 2015.[Abstract]

Virtual laboratories, an ICT-based initiative, is a new venture that is becoming more prevalent in universities for improving classroom education. With geographically remote and economically constrained institutes in India as the focus, we developed web-based virtual labs for virtualizing the wet-lab techniques and experiments with the aid of graphics favoured animations, mathematical simulators and remote triggered experimentations. In this paper, we analysed perceived usefulness of Biotechnology virtual labs amongst student groups and its role in improving the student’s performance when introduced as a learning tool in a blended classroom scenario. A pedagogical survey, via workshops and online feedback, was carried out among 600 university-level students and 100 remote users of various Indian universities. Comparing learning groups on usage of blended learning approach against a control group (traditional classroom methods) and an experimental group (teacher-mediated virtual labs), our studies indicate augmented academic performance among students in blended environments. Findings also indicated usage of remotely-triggered labs aided enhancing interaction-based lab education enabling anytime-anywhere student participation scenarios.

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2014

Raghu Raman, Achuthan, K., Prof. Prema Nedungadi, Dr. Shyam Diwakar, and Bose, R., “Modeling Potential-Adopter Student Acceptance”, IEEE Transactions on Education, vol. 57, pp. 235-241, 2014.[Abstract]

Virtual Labs (VLAB) is a multi-institutional Open Educational Resources (OER) initiative, exclusively focused on lab experiments for engineering education. This project envisages building a large OER repository, containing over 1650 virtual experiments mapped to the engineering curriculum. The introduction of VLAB is a paradigm shift in an educational system that is slow to change. Treating VLAB OER as an educational technology innovation, its adoption by potential-adopter engineering students (N=131) is modeled based on Roger's theory of perceived attributes. Regression and factor analysis were used to analyze the data. Results indicate that the attributes of Compatibility, Ease of Use, Relative Advantage, and Trialability significantly influence potential-adopter students' intention to adopt an innovation like VLAB. The study also observed that using OER (such as VLAB) on desktops and low-cost tablets had similar effects in student performance to using physical labs. This has interesting implications for education policy-makers who are looking to reduce the digital divide. More »»

2014

Dr. Shyam Diwakar, Harilal Parasuram, Medini Chaitanya, Raghu Raman, Prof. Prema Nedungadi, E. Wiertelak, S. Srivastava, Dr. Krishnashree Achuthan, and Dr. Bipin G. Nair, “Complementing neurophysiology education for developing countries via cost-effective virtual labs: Case studies and classroom scenarios”, Journal of Undergraduate Neuroscience Education, vol. 12, pp. A130-A139, 2014.[Abstract]

Classroom-level neuroscience experiments vary from detailed protocols involving chemical, physiological and imaging techniques to computer-based modeling. The application of Information and Communication Technology (ICT) is revolutionizing the current laboratory scenario in terms of active learning especially for distance education cases. Virtual web-based labs are an asset to educational institutions confronting economic issues in maintaining equipment, facilities and other conditions needed for good laboratory practice. To enhance education, we developed virtual laboratories in neuroscience and explored their first-level use in (Indian) University education in the context of developing countries. Besides using interactive animations and remotely-triggered experimental devices, a detailed mathematical simulator was implemented on a web-based software platform. In this study, we focused on the perceptions of technology adoption for a virtual neurophysiology laboratory as a new pedagogy tool for complementing college laboratory experience. The study analyses the effect of virtual labs on users assessing the relationship between cognitive, social and teaching presence. Combining feedback from learners and teachers, the study suggests enhanced motivation for students and improved teaching experience for instructors. © Faculty for Undergraduate Neuroscience.

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2014

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Hemalatha Sasidharakurup, Rakhi Radhamani, Gopika Sujatha, Akhila Shekhar, Dr. Krishnashree Achuthan, Prof. Prema Nedungadi, and Raghu Raman, “Usage and Diffusion of Biotechnology Virtual Labs for Enhancing University education in India’s Urban and Rural Areas”, E-Learning as a Socio-Cultural System: A Multidimensional Analysis, pp. 63-83, 2014.[Abstract]

Information and Communication Technology (ICT)-enabled virtual laboratories provide an online learning experience with the aid of computer-based instructional materials (animation, simulation, and remote-trigger experiments) for improving the active learning process. The project reported on in this chapter was set up in order to enhance university and college education, which is now becoming an advanced training environment for solving the geographical, social, and economic challenges faced in the interdisciplinary field of science education, especially in India. In order to study the role of biotechnology virtual laboratories in the current education system, a pedagogical survey, via workshops and online feedback, was carried out among several student and teacher groups of different Indian universities. This chapter reports how virtual labs in biotechnology can be used to improve teaching and learning experiences in an easy and understandable way with user interaction and how such tools serve to effectively reduce the problems of laboratory education especially in remote areas. The results obtained from user-feedback analysis suggest the use of virtual labs as a recommended component in blended education in large classroom scenarios for enhancing autonomous learning process and as an alternative to enhance lab education in geographically remote and economically challenged institutes.

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2013

Srivastava S, Özdemir V, Ray S, Panga J. R., Noronha S, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Online education: E-learning booster in developing world”, Nature, vol. 501, 2013.

2013

Asha Vijayan, Chaitanya Nutakki, Chaitanya Medini, Hareesh Singanamala, Dr. Bipin G. Nair, Krishnasree Achuthan, and Dr. Shyam Diwakar, “Classifying Movement Articulation for Robotic Arms via Machine Learning”, Journal of Intelligent Computing, vol. 4, no. 3, pp. 123-134, 2013.[Abstract]

Articulation via target-oriented approaches have been commonly used in robotics. Movement of a robotic arm can involve targeting via a forward or inverse kinematics approach to reach the target. We attempted to transform the task of controlling the motor articulation to a machine learning approach. Towards this goal, we built an online robotic arm to extract articulation datasets and have used SVM and NaÃ¯ve Bayes techniques to predict multi-joint articulation. For controlling the preciseness and efficiency, we developed pick and place tasks based on pre-marked positions and extracted training datasets which were then used for learning. We have used classification as a scheme to replace prediction-correction approach as usually attempted in traditional robotics. This study reports significant classification accuracy and efficiency on real and synthetic datasets generated by the device. The study also suggests SVM and Naive Bayes algorithms as alternatives for computational intensive prediction-correction learning schemes for articulator movement in laboratory environments.

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2013

Darpan Malhotra, Dr. Shyam Diwakar, Vural Ozdemir, Dr. Bipin G. Nair, and Sanjeeva Srivastava, “BIOQUEST India: A Global Biotechnology Forum for Knowledge-Based Innovation and Sustainable Development”, Current Pharmacogenomics and Personalized Medicine (Formerly Current Pharmacogenomics), vol. 11, pp. 8–11, 2013.[Abstract]

Introduction
Biotechnology and knowledge-based innovations are sought after by countries small and large for development and societal prosperity, not to forget for advancing the standards in medicine, health systems and services of nations. Key elements to this science and technology driven development agenda are exemplified by BIOQUEST India. This global biotechnology forum draws from local and regional advances in the Asia-Pacific and integrates it with key global scientific progress in life sciences.

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2012

Sandipan Ray, Nicole R Koshy, Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Sanjeeva Srivastava, “Community Page-Sakshat Labs: India's Virtual Proteomics Initiative”, PLoS-Biology, vol. 10, p. 1306, 2012.

2012

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Prema Nedungadi, and Dr. Bipin G. Nair, “Biotechnology Virtual Labs: Facilitating Laboratory Access Anytime-Anywhere for Classroom Education”, Innovations in Biotechnology Edited by Dr. Eddy C. Agbo, 2012.[Abstract]

<p>Biotechnology is becoming more popular and well identified as a mainline industry.Students have shown greater interest in learning the techniques. As a discipline, biotechnology has led to new advancements in many areas. Criminal investigation has changed dramatically thanks to DNA fingerprinting. Significant advances in forensic medicine, anthropology and wildlife management have been noticed in the last few years. Biotechnology has brought out hundreds of medical diagnostic tests that keep the blood safe from infectious diseases such as HIV and also aid detection of other conditions early enough to be successfully treated.</p>

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2012

Dr. Bipin G. Nair, Remya Krishnan, Nijin Nizar, Rakhi Radhamani, Karthika Rajan, Afila Yoosef, Gopika Sujatha, Vijilamole Radhamony, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Role of ICT-enabled visualization-oriented virtual laboratories in Universities for enhancing biotechnology education – VALUE initiative: Case study and impacts”, FormaMente, vol. VII, pp. 1-2, 2012.[Abstract]

Information and Communication Technology (ICT) enabled virtual labs have been setup in order to facilitate and enhance higher education. VALUE Biotechnology virtual labs were implemented as part of an ICT initiative and tested between several students and teacher groups. In this paper, we discuss about the application of virtualizing concepts and experiments in biotechnology, one of the fundamental area of biological sciences to impart quality education to meet the necessities of students. We found virtual labs, enhanced attention and student performance in biotechnology courses. The paper reports that applying virtualization techniques, biotechnology education could be intensified in terms of student attention and virtual lab can serve as an effective teaching pedagogy. The paper shows how virtual labs in biotechnology can be exploited to improve teaching and student performance. This study analyzes the trends of user behavior towards virtual laboratories and the usability of these laboratories as a learning and curriculum material. Findings from indicated biotechnology virtual laboratories encompass all the core subjects of their curriculum materials in an easy and understandable way with user-interaction and serve to reduce the problems of laboratory education especially in economically challenged and geographically remote areas. Virtual laboratories target a user-friendly outlook to modern laboratory education, aiding as an optional evaluation component for University teachers.

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2012

Sandipan Ray, Nicole R Koshy, Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Sanjeeva Srivastava, “Sakshat Labs: India's Virtual Proteomics Initiative”, PLoS biology, vol. 10, p. e1001353, 2012.[Abstract]

The article reports on the launch of Virtual Proteomics Lab (VPL) by India's Ministry of Human Resource Development (MHRD) as part of a comprehensive Virtual Lab Project with the goal of providing easily accessible and high-quality-education across the globe. The VPL can be found at Indian Institute of Technology (IIT) Bombay as a national project dedicated to high-throughput proteome separation and analysis techniques. The effort also aimed at making consolidated practical proteomics resource.

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2012

Chaitanya Medini, Dr. Bipin G. Nair, Egidio D'Angelo, Giovanni Naldi, and Dr. Shyam Diwakar, “Modeling spike-train processing in the cerebellum granular layer and changes in plasticity reveal single neuron effects in neural ensembles”, Computational intelligence and neuroscience, vol. 2012, p. 7, 2012.[Abstract]

<p>The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model and a biophysically-detailed model of the network were used to study signal recoding in the granular layer and to test observations like center-surround organization and time-window hypothesis in addition to effects of induced plasticity. Simulations suggest that simple neuron models may be used to abstract timing phenomenon in large networks, however detailed models were needed to reconstruct population coding via evoked local field potentials (LFP) and for simulating changes in synaptic plasticity. Our results also indicated that spatio-temporal code of the granular network is mainly controlled by the feed-forward inhibition from the Golgi cell synapses. Spike amplitude and total number of spikes were modulated by LTP and LTD. Reconstructing granular layer evoked-LFP suggests that granular layer propagates the nonlinearities of individual neurons. Simulations indicate that granular layer network operates a robust population code for a wide range of intervals, controlled by the Golgi cell inhibition and is regulated by the post-synaptic excitability.</p>

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2011

Dr. Shyam Diwakar, “Information processing in the cerebellum granular layer and changes in plasticity revealing single neuron effects in neural ensembles”, Frontiers in Computational Neuroscience, 2011.[Abstract]

In the current work, an estimate of information flow in terms of spikes in the cerebellum granular layer is discussed. Information transmission at the Mossy Fiber (MF)-Granule cell (GrC) synaptic relay is crucial to understand mechanisms of signal coding in the cerebellum [Albus, 1971][Marr, 1969]. To quantify the information transfer of a whole neuron, we used a computational model of a cerebellar granule cell [Diwakar, 2009], where the excitatory input space could be explored extensively. More »»

2011

Dr. Shyam Diwakar, “Computational Neuroscience of Granule Neurons: Biophysical modeling of single neuron and network functions of the cerebellum granular layer”, 2011.

2011

Raghu Raman, Prema Nedungadi, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Integrating Collaboration and Accessibility for Deploying Virtual Labs using VLCAP”, International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies , 2011.[Abstract]

The Virtual Labs Collaboration and Accessibility Platform (VLCAP) provides tools to further India’s National Mission project: the building of over 150 Virtual Labs (VL) for over 1450 multi-disciplinary undergraduate- and postgraduate-level experiments. VLCAP optimizes VL development and deployment costs and ensures a rich, consistent learning experience. Its multi-tier, scalable architecture allows VL builders to focus on their experiments. Its modules (VL workbench, collaborative content management, repositories) have axiomatically-designed interfaces that bring speed and efficiency to design. Its integration of user-management tasks (single sign-on, role-based access control, etc.) enhances flexibility without compromising security. The key accomplishments include its application of simulation VL and its provision of easily usable authoring tools, pre-configured templates, and management and assessment modules for instructors. VLCAP’s support of multiple deployment models, including the cloud, hosted, and mixed models, ensures scalable and reliable usage in hosted environments, and secure access for learners in remote locations.

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2011

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Prema Nedungadi, and Dr. Bipin G. Nair, “Enhanced facilitation of biotechnology education in developing nations via virtual labs: analysis, implementation and case-studies”, International Journal of Computer Theory and Engineering, vol. 3, pp. 1–8, 2011.[Abstract]

Methods for educating students in biotechnology require intensive training in laboratory procedures. Laboratory procedures cost Universities in terms of equipment and experienced guidance which often come short in many developing countries. Universities need revitalizing approach and well-adapted curriculum especially in terms of laboratory practice. For enhanced education at the level of University-level laboratory courses such as those in biology or biotechnology, one of the key elements is the need to allow the student to familiarize laboratory techniques in par with regular theory. The Sakshat Amrita virtual biotechnology lab project focusing on virtualizing wet-lab techniques and integrating the learning experience has added a new dimension to the regular teaching courses at the University. Establishing virtual labs requires both domain knowledge and virtualizing skills via programming, animation and device-based feedback. This paper reports a cost-effective process used in virtualizing real biotechnology labs for education at Universities. The major challenge in setting up an effective knowledge dissemination for laboratory courses was not only the scientific approach of biotechnology, but included the virtualization aspects such as usage/design scalability, deliverability efficiency, network connectivity issues, security and speed of adaptability to incorporate and update changes into existing experiments. This paper also discusses an issue-specific case-study of a functional virtual lab in biotechnology and its many issues and challenges.

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2011

Harilal Parasuram, Dr. Bipin G. Nair, Giovanni Naldi, D’Angelo, E., and Dr. Shyam Diwakar, “A modeling based study on the origin and nature of evoked post-synaptic local field potentials in granular layer”, Journal of Physiology-Paris, vol. 105, no. 1-3, pp. 71–82, 2011.[Abstract]

Understanding population activities of underlying neurons reveal emergent behavior as patterns of information flow in neural circuits. Evoked local field potentials (LFPs) arise from complex interactions of spatial distribution of current sources, time dynamics, and spatial distribution of dipoles apart underlying conductive properties of the extracellular medium. We reconstructed LFP to test and parameterize the molecular mechanisms of cellular function with network properties. The sensitivity of LFP to local excitatory and inhibitory connections was tested using two novel techniques. In the first, we used a single granule neuron as a model kernel for reconstructing population activity. The second technique consisted using a detailed network model. LTP and LTD regulating the spatiotemporal pattern of granular layer responses to mossy fiber inputs was studied. The effect of changes in synaptic release probability and modulation in intrinsic excitability of granule cell on LFP was studied. The study revealed cellular function and plasticity were represented in LFP wave revealing the activity of underlying neurons. Changes to single cell properties during LTP and LTD were reflected in the LFP wave suggesting the sparse recoding function of granule neurons as spatial pattern generators. Both modeling approaches generated LFP in vitro (Mapelli and D'Angelo, 2007) and in vivo (Roggeri et al., 2008) waveforms as reported in experiments and predict that the expression mechanisms revealed in vitro can explain the LFP changes associated with LTP and LTD in vivo.

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2011

Dr. Shyam Diwakar, Lombardo, P., Solinas, S., Naldi, G., and D'Angelo, E., “Local field potential modeling predicts dense activation in cerebellar granule cells clusters under LTP and LTD control”, PLoS ONE, vol. 6, 2011.[Abstract]

Local field-potentials (LFPs) are generated by neuronal ensembles and contain information about the activity of single neurons. Here, the LFPs of the cerebellar granular layer and their changes during long-term synaptic plasticity (LTP and LTD) were recorded in response to punctate facial stimulation in the rat in vivo. The LFP comprised a trigeminal (T) and a cortical (C) wave. T and C, which derived from independent granule cell clusters, co-varied during LTP and LTD. To extract information about the underlying cellular activities, the LFP was reconstructed using a repetitive convolution (ReConv) of the extracellular potential generated by a detailed multicompartmental model of the granule cell. The mossy fiber input patterns were determined using a Blind Source Separation (BSS) algorithm. The major component of the LFP was generated by the granule cell spike Na + current, which caused a powerful sink in the axon initial segment with the source located in the soma and dendrites. Reproducing the LFP changes observed during LTP and LTD required modifications in both release probability and intrinsic excitability at the mossy fiber-granule cells relay. Synaptic plasticity and Golgi cell feed-forward inhibition proved critical for controlling the percentage of active granule cells, which was 11% in standard conditions but ranged from 3% during LTD to 21% during LTP and raised over 50% when inhibition was reduced. The emerging picture is that of independent (but neighboring) trigeminal and cortical channels, in which synaptic plasticity and feed-forward inhibition effectively regulate the number of discharging granule cells and emitted spikes generating "dense" activity clusters in the cerebellar granular layer. © 2011 Diwakar et al.

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2009

Dr. Shyam Diwakar, Magistretti, J., Goldfarb, M., Giovanni Naldi, and D’Angelo, E., “Axonal Na channels ensure fast spike activation and back-propagation in cerebellar granule cells”, J Neurophysiol, vol. 101, pp. 519–532, 2009.[Abstract]

In most neurons, Na+ channels in the axon are complemented by others localized in the soma and dendrites to ensure spike back-propagation. However, cerebellar granule cells are neurons with simplified architecture in which the dendrites are short and unbranched and a single thin ascending axon travels toward the molecular layer before bifurcating into parallel fibers. Here we show that in cerebellar granule cells, Na+ channels are enriched in the axon, especially in the hillock, but almost absent from soma and dendrites. The impact of this channel distribution on neuronal electroresponsiveness was investigated by multi-compartmental modeling. Numerical simulations indicated that granule cells have a compact electrotonic structure allowing excitatory postsynaptic potentials to diffuse with little attenuation from dendrites to axon. The spike arose almost simultaneously along the whole axonal ascending branch and invaded the hillock the activation of which promoted spike back-propagation with marginal delay (<200 micros) and attenuation (<20 mV) into the somato-dendritic compartment. These properties allow granule cells to perform sub-millisecond coincidence detection of pre- and postsynaptic activity and to rapidly activate Purkinje cells contacted by the axonal ascending branch.

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2008

F. Prestori, Rossi, P., Bearzatto, B., Lainé, J., Necchi, D., Dr. Shyam Diwakar, Schiffmann, S. N., Axelrad, H., and Egidio D'Angelo, “Altered neuron excitability and synaptic plasticity in the cerebellar granular layer of juvenile prion protein knock-out mice with impaired motor control”, The Journal of neuroscience, vol. 28, pp. 7091–7103, 2008.[Abstract]

Although the role of abnormal prion protein (PrP) conformation in generating infectious brain diseases (transmissible spongiform encephalopathy) has been recognized, the function of PrP in the normal brain remains mostly unknown. In this investigation, we considered the effect of PrP gene knock-out (PrP0/0) on cerebellar neural circuits and in particular on granule cells, which show intense PrP expression during development and selective affinity for PrP. At the third postnatal week, when PrP expression would normally attain mature levels, PrP0/0 mice showed low performance in the accelerating rotarod and runway tests and the functioning of 40% of granule cells was abnormal. Spikes were slow, nonovershooting, and nonrepetitive in relation with a reduction in transient inward and outward membrane currents, and also the EPSPs and EPSCs had slow kinetics. Overall, these alterations closely resembled an immature phenotype. Moreover, in slow-spiking PrP0/0 granule cells, theta-burst stimulation was unable to induce any long-term potentiation. This profound impairment in synaptic excitation and plasticity was associated with a protracted proliferation of granule cells and disappeared at P40–P50 along with the recovery of normal motor behavior (Büeler et al., 1992). These results suggest that PrP plays an important role in granule cell development eventually regulating cerebellar network formation and motor control.

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2007

M. Goldfarb, Schoorlemmer, J., Williams, A., Dr. Shyam Diwakar, Wang, Q., Huang, X., Giza, J., Tchetchik, D., Kelley, K., Vega, A., and , “Fibroblast growth factor homologous factors control neuronal excitability through modulation of voltage-gated sodium channels”, Neuron, vol. 55, pp. 449–463, 2007.[Abstract]

Neurons integrate and encode complex synaptic inputs into action potential outputs through a process termed “intrinsic excitability.” Here, we report the essential contribution of fibroblast growth factor homologous factors (FHFs), a family of voltage-gated sodium channel binding proteins, to this process. Fhf1−/−Fhf4−/− mice suffer from severe ataxia and other neurological deficits. In mouse cerebellar slice recordings, WT granule neurons can be induced to fire action potentials repetitively (∼60 Hz), whereas Fhf1−/−Fhf4−/− neurons often fire only once and at an elevated voltage spike threshold. Sodium channels in Fhf1−/−Fhf4−/− granule neurons inactivate at more negative membrane potential, inactivate more rapidly, and are slower to recover from the inactivated state. Altered sodium channel physiology is sufficient to explain excitation deficits, as tested in a granule cell computer model. These findings offer a physiological mechanism underlying human spinocerebellar ataxia induced by Fhf4 mutation and suggest a broad role for FHFs in the control of excitability throughout the CNS.

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### Publication Type: Book

Year of Publication Title

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, Adoption of Virtual Laboratories in India, Learning Assessments and Roles of ICT Skill Learning Tools, Arthur Tatnall, Springer, accepted. 2018.

2006

Dr. Soman K. P., Dr. Shyam Diwakar, and Ajay, V., DATA MINING: THEORY AND PRACTICE . PHI Learning Pvt. Ltd., 2006.

2006

K. P. Soman, Dr. Shyam Diwakar, and AJAY, V., DATA MINING: THEORY AND PRACTICE . PHI Learning Pvt. Ltd., 2006.[Abstract]

Data Mining is an emerging technology that has made its way into science, engineering, commerce and industry as many existing inference methods are obsolete for dealing with massive datasets that get accumulated in data warehouses. This comprehensive and up-to-date text aims at providing the reader with sufficient information about data mining methods and algorithms so that they can make use of these methods for solving real-world problems. The authors have taken care to include most of the widely used methods in data mining ... More »»

### Publication Type: Book Chapter

Year of Publication Title

2018

Dr. Shyam Diwakar, Chaitanya Nutakki, Sandeep Bodda, Arathi Rajendran, Asha Vijayan, and Dr. Bipin G. Nair, “Mathematical Modelling of Cerebellar Granular Layer Neurons and Network Activity: Information Estimation, Population Behaviour and Robotic Abstractions”, in Mathematical and Theoretical Neuroscience: Cell, Network and Data Analysis, Giovanni Naldi and Nieus, T., Eds. Cham: Springer International Publishing, 2018, pp. 61–85.[Abstract]

Recent studies show cerebellum having a crucial role in motor coordination and cognition, and it has been observed that in patients with movement disorders and other neurological conditions cerebellar circuits are known to be affected. Simulations allow insight on how cerebellar granular layer processes spike information and to understand afferent information divergence in the cerebellar cortex. With excitation-inhibition ratios adapted from in vitro experimental data in the cerebellum granular layer, the model allows reconstructing spatial recoding of sensory and tactile patterns in cerebellum. Granular layer population activity reconstruction was performed with biophysical modeling of fMRI BOLD signals and evoked local field potentials from single neuron and network models implemented in NEURON environment. In this chapter, evoked local field potentials have been reconstructed using biophysical and neuronal mass models interpreting averaged activity and constraining population behavior as observed in experiments. Using neuronal activity and correlating blood flow using the balloon and modified Windkessel model, generated cerebellar granular layer BOLD response. With the focus of relating neural activity to clinical correlations such models help constraining network models and predicting activity-dependent emergent behavior and manifestations. To reverse engineering brain function, cerebellar circuit functions were abstracted into a spiking network based trajectory control model for robotic articulation.

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2016

Sandipan Ray, Sanjeeva Srivastava, Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Vural Ozdemir, “Delivering on the Promise of Bioeconomy in the Developing World: Link It with Social Innovation and Education”, in Biomarker Discovery in the Developing World: Dissecting the Pipeline for Meeting the Challenges, Sanjeeva Srivastava, Ed. New Delhi: Springer India, 2016, pp. 73–81.[Abstract]

In developing countries where numerous factors such as rapid population growth and entrenched social problems hinder equitable economic growth and education, research and development (R{&amp;}D) are often neglected as well. But the importance of R{&amp;}D extends beyond science. The capacity to generate and advance their scientific scholarship is important for all countries – for such independent scientific thinking skills might also empower the citizens' capacity and will to think democratically in a global interdependent world. Social innovation is explained here as a form of responsible innovation that brings together funders, scientists, and knowledge user communities to address long-standing and/or entrenched societal problems. Moreover, in social innovation, the user communities such as citizens can also contribute to the scientific design and funding beyond a passive role to merely adopt innovations developed by scientific experts. The overall success of developing nations thus rests on building successful linkages of the education ecosystem with social innovation and bioeconomy. To this end, E-learning endeavors and the virtual biotechnology labs are novel initiatives that are rapidly transforming society in the developing world. Distance education and E-learning and open learning endeavors are certainly advantageous for the resource-limited developing countries, where the numbers of potential learners are much higher than the number of well-experienced teachers and educational institutes capable of providing the required infrastructures for basic and advanced scientific education. India, in particular, has had strikingly innovative and forward-looking investments in biotechnology distributed learning practices that can illuminate the global society of scientists and citizens. In this chapter we will highlight the fundamental need and present scenario of virtual laboratories in advanced sophisticated life science education in the developing world.

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2015

Dr. Shyam Diwakar, “Computational Modeling of Neuronal Dysfunction at Molecular Level Validates the Role of Single Neurons in Circuit Functions in Cerebellum Granular Layer”, in Validating Neuro-Computational Models of Neurological and Psychiatric Disorders, Springer, 2015, pp. 189–220.[Abstract]

Using mathematical modelling, we attempted to reconstruct the information transmission at the granular layer of the cerebellum, a circuit whose functions and dysfunctions remain yet to be explored in detail. Information transmission at the Mossy Fiber (MF)—Granule cell (GrC) synaptic relay is crucial to understand mechanisms of signal coding in the cerebellum and related impacts of connectivity mechanisms. Using biophysically detailed multi-compartmental models, simple spiking neurons we reconstructed granular layer micro-circuitry and estimated both single neuron behaviour and network activity in terms of center-surround patterns, as observed during sensory and tactile stimulation. The chapter also includes local field potential reconstructions to show plasticity mechanisms at the molecular level is reflected at the network activity level, indicating network LFP in the granular layer is a regulated activity signal arising from the underlying granule cells and the feed-forward inhibition from the Golgi cells. The role of selective inhibition by Golgi cells for coincidence detection is presented. Exploring the EPSP-spike complex in granular neurons revealed potential mechanisms for sparse recoding in cerebellum and quantification of information encoding in individual neurons of the cerebellar granular layer. We also look into two specific forms of neuronal dysfunction with ataxia-like behaviour in knockout mice models and in NMDAR-related autism. While network activity was severely affected, the amplitude of damage is critical of the mechanisms at the cellular or molecular level. The study further enhances our understanding of specific coding geometries in the cerebellum and spatio-temporal processing in a primary circuit of the cerebellum. More »»

### Publication Type: Conference Paper

Year of Publication Title

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Sasidharakurup H., Nutakki C., Rajendran A., Venugopal P., Sumon M., Navaneethkumar L., and Madhu H, “Spectral Correlations in Speaker-Listener Behavior During a Focused Duo Conversation using EEG”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted)., 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Sasidharakurup H., Pradeep M., Bhaskaran M., Priya A., Pradeep E., and Kadavath S., “Modeling of Glutamate Pathway in Alzheimer's Disease using Biochemical Systems Theory”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted). , 2018.

2018

Rajendran A., Abdulsalam A., Mohan D, Thazepurayil J., Prabhat S, Dr. Shyam Diwakar, and Dr. Bipin G. Nair, “Trajectory tracking using a Bio-inspired neural network for a low cost robotic articulator”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted). , 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Rajendran A., and Presannan A, “Reproducing the firing properties of a cerebellum deep cerebellar nucleus with a multi compartmental morphologically realistic biophysical model”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted)., 2018.

2018

Dr. Shyam Diwakar, A., K., A., S., Dr. Krishnashree Achuthan, A., P., P, S., and D., K., “Mathematical Models as Bioscience Educational Informatics Tools”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted), 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Sasi V, Ramachandran L. P., Gunasekaran S., Edakkepravan H., and Nutakki C., “Torque Analysis of Male-Female Gait and Identification using Machine Learning”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, Sept 19-22, 2018 (accepted)., 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Manjusha Nair, Krishnan M, Edison L, Radhamani R., Nizar N., and Kumar D, “Experimental Recording and Computational Analysis of EEG signals for a Squeeze Task: Assessments and Impacts for Applications”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, 2018.

2018

Dr. Shyam Diwakar, Nutakki C., Radhakrishnan S., and Dr. Bipin G. Nair, “Modeling Nitric Oxide Induced Neural Activity and Neurovascular Coupling in a Cerebellum Circuit”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, 2018.

2018

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Radhamani R., Divakar A, Nair A, Sivadas, Mohan G, Nizar N., and Achuthan K., “Virtual Laboratories in Biotechnology are Significant Educational Informatics Tools”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India, 2018.

2018

Dr. Shyam Diwakar, Radhamani R., Nizar N., Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, “Using Learning Theory for Assessing Effectiveness of Laboratory Education Delivered via a Web-based Platform”, in International Conference on Remote Engineering and Virtual experimentation (REV 2018), Dusseldorf, Germany, 2018.

2017

Nijin Nizar, Rakhi Radhamani, Dhanush Kumar, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Implementation of analog electrical neurons as virtual labs for neuroscience education”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Over the last few years, research was aimed to investigate neuromorphic computing methodologies for understanding the functions and behavior of biological neurons on a real-time basis. In neuron electrical models, the principles of computational neuroscience is translated on to analog hardware and the circuits reproduces the bio-physical properties of neurons. Our aim was to implement analog neuron models based on Hodgkin-Huxley formalism, and to deploy it as an educational platform for understanding the cellular and behavioral neuroscience. We have taken multiple analog hardware models and implemented its corresponding equivalent for studying the pedagogical concepts such as spiking, bursting, effects of ion channels, effect of pharmacological agents on spiking properties. We implemented remote electrical laboratories for science and engineering education bridging computing systems and neural studies. Initial implementation of the remote labs were done with commercial software which was later replaced with Free and Open Source Software (FOSS) architecture. Pedagogical analysis indicated, effectiveness in the usage of analog neuron model as a learning material for complementing neuroscience education in universities. Post-deployment studies on students and teachers includes perceived use of remote experimentation in a blended classroom scenario.

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2017

J. Alphonse, Chaitanya Medini, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “An open-source computational neuroscience virtual laboratory tool for simulating spiking neurons and circuits”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Neuronal models and real-time simulations of large-scale neural networks allow hypothesis testing of physiological data and for predicting neurological disorders. Simulators using web technologies serve as educational tools in addition to allowing experimentalists make predictions on experimental hypotheses. In this paper, we have developed a web-based neuron and network simulator to model spatio-temporal computations in animal nervous systems. Neuronal models including Hodgkin-Huxley (HH), Adaptive Exponential (AdEx) integrate and fire model and Izhikevich model were incorporated. All models were implemented using JavaScript and python with visualization using HTML5. Single neuron responses and a small-scale network dynamics corresponding to experimentally-known stimuli patterns were simulated. The simulator allows configuring neuronal dynamics through the GUI and can also allow modeling complex dynamics by interfacing with BRIAN for more large-scale and complex simulations. This web technology-based simulation environment may be used by neurophysiologists to simulate experimental protocols and modeling simple circuit dynamics with or without backend programming.

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2017

Manjusha Nair, Akshaya Puthenpeed Suresh, Anjana Manoharan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Information theoretic visualization of spiking neural networks”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Visualization is a flexible way to analyze simulated data and serves as a means for scientific discovery. Large scale neural simulations using high performance and distributed computing techniques produce huge amount of data for which visual analysis is generally difficult to perform. In this paper, a spiking neuron simulation environment was created to model and simulate networks of neurons of the cerebellum. Traditional visualization techniques were used to highlight relevant findings from small scale cerebellar networks. Time varying volume visualization using traditional techniques was found infeasible as network size increased. New data abstractions were required to depict the data that changes over time. With large scale cerebellar networks, Information theoretic methods were used to reduce dimensionality and to extract valuable information from data. We suggested that, information theory can be used as an efficient scientific data analysis and visualization tool to evaluate and validate computational models of cerebellar like structures.

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2017

Manjusha Nair, Krishnapriya Ushakumari, Athira Ramakrishnan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Comparing parallel simulation of single and multi-compartmental spiking neuron models using gpgpu”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Characterizing neural responses and behavior require large scale simulation of brain circuits. Spatio-temporal information processing in large scale neural simulations often require compromises between computing resources and realistic details to be represented. In this work, we compared the implementations of point neuron models and biophysically detailed neuron models on serial and parallel hardware. GPGPU like architectures provide improved run time performance for multi compartmental Hodgkin-Huxley (HH) type neurons in a computationally cost effective manner. Single compartmental Adaptive Exponential Integrate and Fire (AdEx) model implementations, both in CPU and GPU outperformed embarrassingly parallel implementation of multi compartmental HH neurons. Run time gain of CPU implementation of AdEx cluster was approximately 10 fold compared to the GPU implementation of 10-compartmental HH neurons. GPU run time gain for Adex against GPU run time gain for HH was around 35 fold. The results suggested that careful selection of the neural model, capable enough to represent the level of details expected, is a significant parameter for large scale neural simulations.

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2017

Hemalatha Sasidharakurup, Pyaree Dash, Asha Vijayan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computational modelling of apoptosis in parkinson's disease using biochemical systems theory”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

In this study, we present a computational model of Parkinson's disease (PD) that includes different biological interactions that leads to neural cell death with the use of biochemical systems theory. The model incorporates a set of important pathways in PD including dopaminergic pathway, mitochondrial pathway and P53 - DNA damage pathway. Modeling signaling pathways and simulations were performed using biochemical systems theory. Initial concentrations have been taken from experimental data in literature and were used to model the changes. Results generated by dopaminergic diseased pathway show 45% decrease in dopamine, compared to normal condition. In addition, the activity of MOMP, Caspase 9 and Apoptosome expression in diseased condition within mitochondrial pathway model have been observed in the results. The expression levels of BAX and MOMP were reconstructed and simulations suggest oligomerization of BAK leads to the elevation of MOMP. An increase in oxidative stress and apoptosis level also has been observed in the PD condition, compared to the control allowing comparisons between normal and diseased conditions with these mathematical models.

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2017

Chaitanya Nutakki, Jyothisree Narayanan, Aswathy Anitha Anchuthengil, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Classifying gait features for stance and swing using machine learning”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Structured gait patterns are currently used as a biometric technique to recognize individuals and in building appropriate exoskeleton technologies. In this study, the features involved in gait were extracted and analyzed. Multiple accelerometers were used to collect the data which was then used to identify gait at various axial positions form healthy volunteers with total of 60 trails. Using machine learning optimal feature sub-selection we analyze data to implicate the optimal methods for analysis of swing phase and stance phase in a closed room environment. Study reports that the accelerometer data could classify based on the accuracy and the efficiency of the learning algorithms. Through feature ranking, results suggest gait can be attributed to a combination of Brachium of arm, Antecubitis, Carpus, Coxal, Femur and Tarsus (Shoulder, Elbow, Wrist, Hip, Knee, and Ankle). This gait study may help analyzing conditions during control and movement-related disease.

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2017

A. Rajendran, Anuja Thankamani, Nishamol Nirmala, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computational neuroscience of substantia nigra circuit and dopamine modulation during parkinson's disease”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Several interconnected brain circuits such as cerebellum, cerebral cortex, thalamus and basal ganglia process motor information in many species including mammals. Interconnection between basal ganglia and cerebellum through thalamus and cortex may influence the pathways involved in basal ganglia processing. Malfunctions in the neural circuitry of basal ganglia influenced by modifications in the dopaminergic system, which are liable for an array of motor disorders and slighter cognitive issues in Parkinson's disease. Both basal ganglia and cerebellum receives input from and send output to the cerebral cortex and these structures influence motor and cognitive operations through cerebellar-thalamo-basal ganglia-cortical circuit. This interconnected circuit (basal ganglia-cerebellum) helps to understand the role of cerebellum in motor dysfunction during Parkinson's disease. To develop models of unsupervised learning as in brain circuits, we modelled sub thalamic nucleus, internal and external parts of Globus pallidus, fast spiking striatal neuron and medium spiny neuron in striatum using Adaptive Exponential Integrate and Fire model. Simulations highlight the correlation between firing of GPe and level of dopamine and the changes induced during simulated Parkinson's disease. Such models are crucial to understand the motor processing and for developing spiking based deep learning algorithms.

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2017

S. Bodda, R. K. Palathingal, V. Sankar, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling population network activity using lfpsim, spiking neurons and neural mass models”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Local Field Potentials arising (LFP) from neural circuits are crucial to understand neural ensemble activity and can act as a link between molecular, cellular and circuit neuroscience. Additionally, mathematical estimations of LFPs allow the study of circuit functions and dysfunctions. In this study, we used mathematical reconstructions of LFP in rat cerebellum Crus IIa using spiking neuronal models and mass models based on lumped parameters to reconstruct the averaged ensemble activity. Comparing experimentally validated reconstructions of evoked LFPs using detailed multi-compartmental models, spiking neurons and lumped mass models suggest variations at the translational levels of biophysical mechanisms in granular layer. With the focus of reconnecting multiple information roles, our simulations studies indicate multi-compartmental detailed models allow estimations on the role of transmembrane currents, spiking neuron models suggest contributions of action potentials while mass models reveal averaged activity behaviour underlying Crus IIa evoked LFPs.

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2017

Asha Vijayan, Vivek Gopan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Comparing robotic control using a spiking model of cerebellar network and a gain adapting forward-inverse model”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.[Abstract]

Internal models inspired from the functioning of cerebellum are being increasingly used to predict and control movements of anthropomorphic manipulators. A major function of cerebellum is to fine tune the body movements with precision and are comparative to capabilities of artificial neural network. Several studies have focused on encoding the real-world information to neuronal responses but temporal information was not given due importance. Spiking neural network accounts to conversion of temporal information into the adaptive learning process. In this study, cerebellum like network was reconstructed which encodes spatial information to kinematic parameters, self-optimized by learning patterns as seen in rat cerebellum. Learning rules were incorporated into our model. Performance of the model was compared to an optimal control model and have evaluated the role of bioinspired models in representing inverse kinematics through applications to a low cost robotic arm developed at the lab. Artificial neural network of Kawato was used to compare with our existing model because of their similarity to biological circuit as seen in a real brain. Kawato's paired forward inverse model has used to train for fast movement based tasks which resembles human based motor tasks. Result suggest kinematics of a 6 DOF robotic arm was internally represented and this may have potential application in neuroprosthesis.

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2017

Melathadathil N, Pazhanivelu S, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Using Machine learning to understand data analysis- A case study of a private health care organization”, in 6th International Conference in Advances in Computing, Communications and Informatics (ICACCI-17), 2017.

2017

Dr. Bipin G. Nair, Dr. Shyam Diwakar, and A. Rajendran, “Pattern Abstraction and Sensory Encoding of Auditory and Visual Stimuli in Cerebellum Granular Layer Network”, in XXXV Annual Meeting of Indian Academy of Neurosciences (IAN), Ravenshaw University, Cuttack, Odisha, India, 2017.

2017

Nutakki C., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling Neurovascular coupling for fMRI BOLD reconstructions”, in XXXV Annual Meeting of Indian Academy of Neurosciences (IAN), Ravenshaw University, Cuttack, Odisha, India, 2017.

2017

D. Kumar, K. Achuthan, Nair, B., and Dr. Shyam Diwakar, “Online bio-robotics labs: Open hardware models and architecture”, in International Conference on Robotics and Automation for Humanitarian Applications, RAHA 2016 - Conference Proceedings, 2017.[Abstract]

This paper is on free and open source software architecture (FOSS) for remote labs in order to address the affordability and scalability of robotic education technology for sustainable deployments. The proposed Raspberry Pi-Arduino-based model architecture ensures lower cost while allowing some scalability, interoperability, portability and interchangeability to the low-cost online laboratory. Remotely controlled lab provides training skills in bio-inspired robotics. Our previous studies had shown that the implementation of remotely controlled online labs in the curriculum improved active learning among students, collaboration, and augmented problem solving skills. The preliminary implementation involved proprietary software, as the remote experiment accessibility platform, which was later replaced with FOSS technology. The advantages with FOSS included a significantly lower cost and scalability for concurrent usage. The paper also reports on usage analysis and common issues in both cases of implementations. © 2016 IEEE. More »»

2017

C. Nutakki, Vijayan, A., Sasidharakurup, H., Nair, B., K. Achuthan, and Dr. Shyam Diwakar, “Low-cost robotic articulator as an online education tool: Design, deployment and usage”, in International Conference on Robotics and Automation for Humanitarian Applications, RAHA 2016 - Conference Proceedings, 2017.[Abstract]

Humanitarian challenges in developing nations such as low cost prosthesis for the physically challenged, have also led to substantial progress in robotics. In this paper, we implemented and deployed a low-cost remotely controlled robotic articulator, as an education tool for university students and teachers. This tool is freely available online and is being employed to generate robotic datasets for novel algorithms. Using a server-client methodology and a browser-based user interface, the online lab allows learners to access and perform basic kinematics experiments and study robotic articulation. These experiments were developed for allowing students to enhance laboratory skills in robotics and improve practical experience without concerns for equipment access restrictions or cost. © 2016 IEEE. More »»

2016

M. S, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “A Multi-Institutional Comparative Study of Laboratories”, in Proceedings of International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT 2016), Chennai, 2016.

2016

P. Chellaiah, Sandeep Bodda, Rahul Lal, Clinton Madhu, Vaibhav Zamare, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “EEG-based assessment of image sequence-based user authentication in computer network security”, in 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India, 2016.[Abstract]

User authentication is crucial in security systems. Although, there are many complex and secure passkey-based authentication mechanisms, majority of users prefer employing simple passwords that are viable to rubber-hose attacks. Image sequence based passwords were introduced to overcome some of the issues with textual passwords. The objective of this work was to evaluate cognitive and memory performance in image-based user authentication systems. Via EEG recordings during image sequence training task, we observed increased activity of α rhythms in F3 and FC5 channel bins and augmented levels of β rhythms in F3 and O1 channels, suggesting users personalized authentication more than in alpha-numeric password-based logins, linking potential roles of implicit and explicit sequence learning in improving human user authentication.

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2016

Sandeep Bodda, Harikrishnan Chandranpillai, Pooja Viswam, Swathy Krishna, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Categorizing imagined right and left motor imagery BCI tasks for low-cost robotic neuroprosthesis”, in 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India, 2016.[Abstract]

Focusing on low-cost articulation control for neuroprosthesis, electroencephalography (EEG)-based brain computer interfaces require rapid and reliable discrimination of EEG patterns associated with motor imagery generated via imagined or real movement. The objective of this study was to characterize EEG signals of two different motor imagery tasks used to control a robotic articulator. With one-sided hand movement imagination resulting in EEG changes located contra and ipsilateral areas, time-courses of two different imagery tasks were investigated via instantaneous band power changes. We compared the features extracted from the EEG patterns with standard machine learning algorithms. We report frequency-based categorization of visualized imagery more relevant than machine learning methods.

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2016

Rakhi Radhamani, Dhanush Kumar, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementing and deploying magnetic material testing as an online laboratory”, in Intelligent Systems Technologies and Applications 2016, Cham, 2016.[Abstract]

Hysteresis loop tracing (HLT) experiment is an undergraduate experiment for physics and engineering students to demonstrate magnetic properties of ferrite materials. In this paper, we explore a new approach of setting- up triggered testing of magnetic hysteresis via a remotely controlled loop tracer. To aid student learners, through an experimental design, we focused on factors such as analytical expression of mathematical model and modeling of reversible changes, which were crucial for learning hysteresis components. The goal was to study the phenomena of magnetic hysteresis and to calculate the retentivity, coercivity and saturation magnetization of a material using a hybrid model including simulation and remotely controlled hysteresis loop tracer. The remotely controlled equipment allowed recording the applied magnetic field (H) from an internet-enabled computer. To analyze learning experiences using online laboratories, we evaluated usage of online experiment among engineering students (N=200) by organized hands-on workshops and direct feedback collection. We found students adapted to use simulations and remotely controlled lab equipment augmenting laboratory skills, equipment accessibility and blended learning experiences.

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2016

Chaitanya Medini, Anjitha Thekkekuriyadi, Surya Thayyilekandi, Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling basal ganglia microcircuits using spiking neurons”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.[Abstract]

Basal ganglia and cerebellum have been implicated in critical roles related to control of voluntary motor movements for action selection and cognition. Basal ganglia primarily receive inputs from cortical areas as well as thalamic regions, and their functional architecture is parallel in nature which link several brain regions like cortex and thalamus. Striatum, substantia nigra, pallidum form different neuronal populations in basal ganglia circuit which were functionally distinct supporting sensorimotor, cognitive and emotional-motivational brain functions. In this paper, we have modelled and simulated basal ganglia neurons as well as basal ganglia circuit using integrate and fire neurons. Firing behaviour of subthalamic nucleus and global pallidus externa show how they modulate spike transmission in the circuit and could be used to model circuit dysfunctions in Parkinson's disease.

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2016

Chaitanya Medini, Arathi G. Rajendran, Aiswarya Jijibai, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computational characterization of cerebellum granule neuron responses to auditory and visual inputs”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.[Abstract]

The multimodal nature of sensory and tactile inputs to cerebellum is of significance for understanding brain function. Granule neuron properties in modifying auditory and visual stimuli was mathematically modeled in this study. Cerebellum granule neuron is a small electrotonically compact neuron and is among the largest number of neurons in the cerebellum. Granule neurons receives four excitatory inputs from four different mossy fibers. We mathematically reconstructed the firing patterns of both auditory and visual responses and decode the mossy fiber input patterns from both modalities. A detailed multicompartment biophysical model of granule neuron was used and in vivo behavior was modeled with short and long bursts. The cable compartmental model could reproduce input-output behavior as seen in real neurons to specific inputs. The response patterns reveal how auditory and visual patterns are encoded by the mossy fiber-granule cell relay and how multiple information modalities are processed by cerebellum granule neuron as responses of auditory and visual stimuli.

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2016

Bodda S, Parasuram H., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computing LFP From Biophysical Models of Neurons and Neural Microcircuits”, in Proceedings of 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI 2016), Jaipur, India, 2016.

2016

Chaitanya Nutakki, Ahalya Nair, Chaitanya Medini, Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computational reconstruction of fMRI-BOLD from neural activity”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.[Abstract]

In this paper, we model function magnetic resonance imaging signals generated by neural activity (fMRI). fMRI measures changes in metabolic oxygen in blood in brain circuits based on changes in biophysical factors like concentration of total cerebral blood flow, oxy-hemoglobin and deoxy-hemoglobin content. A modified version of the Windkessel model by incorporating compliance has been used with a balloon model to generate cerebellar granular layer and visual cortex blood oxygen-level dependent (BOLD) responses. Spike raster patterns were adapted from a biophysical granular layer model as input. The model fits volume changes in blood flow to predict the BOLD responses in the cerebellum granular layer and in visual cortex. As a comparison, we tested the balloon model and the modified Windkessel model with the mathematically reconstructed BOLD response under the same input condition. Delayed compliance contributed to BOLD signal and reconstructed signals were compared to experimental measurements indicating the usability of the approach. The current study allows to correlate dynamic changes of flow and oxygenation during brain activation which connects single neuron and network activity to clinical measurements.

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2016

Sasidharakurup H, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling of Biochemical Pathways in Parkinson's Disease”, in XXXIV Annual Meeting of Indian Academy of Neurosciences (IAN), National Brain Research Center, Manesar, India, 2016.

2016

Rajendran A., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling and Parallelization of Cerebellar Microcircuit for Combinatorial Operation”, in XXXIV Annual Meeting of Indian Academy of Neurosciences (IAN), 2016.

2016

Bodda S, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Mathematical Modelling of Post Synaptic Evoked Local Field Potential Using Neural Mass Model”, in XXXIV Annual Meeting of Indian Academy of Neurosciences (IAN), National Brain Research Center, Manesar, India, 2016.

2016

Nutakki C., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computational Reconstruction of fMRI BOLD from Cerebellar Input Layer”, in XXXIV Annual Meeting of Indian Academy of Neurosciences (IAN), National Brain Research Center, Manesar, India, 2016.

2016

Dhanush Kumar, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Online bio-robotics labs: Open hardware models and architecture”, in 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA), Kollam, India, 2016.[Abstract]

This paper is on free and open source software architecture (FOSS) for remote labs in order to address the affordability and scalability of robotic education technology for sustainable deployments. The proposed Raspberry Pi-Arduino-based model architecture ensures lower cost while allowing some scalability, interoperability, portability and interchangeability to the low-cost online laboratory. Remotely controlled lab provides training skills in bio-inspired robotics. Our previous studies had shown that the implementation of remotely controlled online labs in the curriculum improved active learning among students, collaboration, and augmented problem solving skills. The preliminary implementation involved proprietary software, as the remote experiment accessibility platform, which was later replaced with FOSS technology. The advantages with FOSS included a significantly lower cost and scalability for concurrent usage. The paper also reports on usage analysis and common issues in both cases of implementations.

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2016

Rakhi Radhamani, Nijin Nizar, Dhanush Kumar, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Low cost neuro-inspired robots for sustainable laboratory education”, in International Conference on Robotics and Automation for Humanitarian Applications, RAHA 2016 - Conference Proceedings, Kollam, India, 2016.[Abstract]

Today's technological innovations accelerate the persistence of robots for humanitarian purposes. As a significant component, the emerging role of robotics and educational technologies has been growing instantly. Several attempts have been introduced in the education sector to promote robotics education, but successful implementation of learning platforms still pose challenges. This paper highlights deployment studies based on a low cost bio-inspired robotics laboratory. The experiments were developed as part of a National Mission on Education through ICT, and provided free access to users all over the world. The present study seeks to examine the role of low cost remotely controlled neuro-inspired robotics labs as an educational tool. Our goal was to analyze the diffusion of remotely controlled robotics labs as a new pedagogy for augmenting laboratory education, by enhancing skill training among students, aiding as a teaching element and promoting distant education thereby bringing a sustainable development in robotics based education. Feedback data was collected from 100 science and engineering students, 50 university professors and 100 online users from distant locations to analyze remote robotics labs as an adaptable tool in education. The study suggested perceived usefulness of low cost robotics platform as a supplementary learning and teaching tool for enhancing robotics education. The study also promotes the perceived usage of robotics for vocational skills and as a technology education platform for learners. © 2016 IEEE.

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2016

A. Sridharan, Hemalatha Sasidharakurup, Kumar, D., Nijin Nizar, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Implementing a Web-Based Simulator with Explicit Neuron and Synapse Models to Aid Experimental Neuroscience and Theoretical Biophysics Education”, in Proceedings of the International Conference on Signal, Networks, Computing, and Systems, New Delhi, 2016, vol. 396, pp. 57-66.[Abstract]

In this paper, we implemented a virtual laboratory of neurons and synapses via dynamical models on a web-based platform to aid neurophysiology and computational neuroscience education. Online labs are one of the best alternatives to many universities confronting socio-economic issues in maintaining infrastructure for good laboratory practice. The neural network virtual laboratory was implemented using HTML5 and JQuery, which allowed users to access the lab as a browser-based app. The simulator allows reconstructions of population code and biophysics of single neuron firing dynamics and hence will allow experimentalists to explore its use for hypothesis-based predictions. Such tools as educational aids allow an interrelationship of cognitive, social, and teaching presence. We found students could easily reproduce the common voltage and current clamp protocols on such models without significant instructor assistance and the platform was developed to allow further extensions like raster plots, network computations using extensions to code modules. With new technologies, we foresee a potential redesign of the use of such virtual labs for large-scale modeling as teaching and learning tools in blended learning environments.

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2016

Chaitanya Nutakki, Asha Vijayan, Hemalata Sasidharakurup, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Low-Cost Robotic Articulator as an Online Education tool: Design, Deployment and Usage”, in Proceedings of IEEE International Conference on Robotics and Automation for Humanitarian Applications, Amrita Vishwa Vidyapeetham, Kollam, Kerala, 2016.[Abstract]

Humanitarian challenges in developing nations such as low cost prosthesis for the physically challenged, have also led to substantial progress in robotics. In this paper, we implemented and deployed a low-cost remotely controlled robotic articulator, as an education tool for university students and teachers. This tool is freely available online and is being employed to generate robotic datasets for novel algorithms. Using a server-client methodology and a browser-based user interface, the online lab allows learners to access and perform basic kinematics experiments and study robotic articulation. These experiments were developed for allowing students to enhance laboratory skills in robotics and improve practical experience without concerns for equipment access restrictions or cost.

More »»

2015

Medini C., Basabdatta B., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Comparing Firing Properties of Two Interconnected Circuits to Understand Information Processing at Afferent Pathways”, in Proceedings of the Integrated Systems Neuroscience (ISN) workshop, University of Manchester, UK, 2015.

2015

Harilal Parasuram, Dr. Bipin G. Nair, Giovanni Naldi, Egidio D'Angelo, and Dr. Shyam Diwakar, “Exploiting point source approximation on detailed neuronal models to reconstruct single neuron electric field and population LFP”, in 2015 International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015.[Abstract]

Extracellular electrodes record local field potential as an average response from the neurons within the vicinity of the electrode. Here, we used neuronal models and point source approximation techniques to study the compartmental contribution of single neuron LFP and the attenuation properties of extracellular medium. Cable compartmental contribution of single neuron LFP was estimated by computing electric potential generated by localized ion channels. We simulated the electric potential generated from axon-hillock region contributed significantly to the single neuron extracellular field. Models of cerebellar granule neuron and L5 pyramidal neuron were used to study single neuron extracellular field potentials. Attenuation properties of the extracellular medium were studied via the granule cell model. A computational model of a rat Crus-IIa cerebellar granular layer, built with detailed anatomical and physiological properties allowed reconstructing population LFP. As with single neurons, the same technique was able to reconstruct the T and C waves of evoked postsynaptic in vivo LFP trace. In addition to role of attenuation on the width of signals, plasticity was simulated via modifications of intrinsic properties of underlying neurons and population LFP validated experimental data correlating network function to underlying single neuron activity.

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2015

Chaitanya Medini, Giovanni Naldi, Dr. Bipin G. Nair, Egidio D'Angelo, and Dr. Shyam Diwakar, “Reconstructing fMRI BOLD signals arising from cerebellar granule neurons - comparing GLM and balloon models”, in 2015 International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015.[Abstract]

Understanding the relationship between fMRI BOLD and underlying neuronal activity has been crucial to connect circuit behavior to cognitive functions. In this paper, we modeled fMRI BOLD reconstructions with general linear model and balloon modeling using biophysical models of rat cerebellum granular layer and stimuli spike trains of various response times. Linear convolution of the hemodynamic response function with the known spiking information reconstructed activity similar to experimental BOLD-like signals with the limitation of short stimuli trains. Balloon model through Volterra kernels gave seemingly similar results to that of general linear model. Our main goal in this study was to understand the activity role of densely populated clusters through BOLD-like reconstructions given neuronal responses and by varying response times for the whole stimulus duration.

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2015

Arathi G. Rajendran, Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Analyzing Mutual Information and Synaptic Efficacy at Mossy Fiber –Granule Cell Relay in Rat Cerebellum”, in Proceedings of the International symposium on Translational Neuroscience & XXXIII Annual Conference of the Indian Academy of Neurosciences, Panjab University, Chandigarh , 2015.

2015

Sandeep Bodda, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “EEG-Based Assessment and Categorisation for Imagery Based Movement and Mental Tasks”, in Proceedings of the International symposium on Translational Neuroscience & XXXIII Annual Conference of the Indian Academy of Neurosciences,, Panjab University, Chandigarh , India, 2015.[Abstract]

Focusing on rapid and reliable discrimination of EEG patterns associated with motor imagery and to evaluate the cognitive and memory performance of human user authentication in image-based password systems. This study presents a methodology which uses a nonlinear pattern recognition to study the spatial distribution of EEG patterns accompanying higher cortical functions. The multivariate decision rules associate EEG patterns differentiating performance of motor and mental tasks. These patterns discriminate between the tasks are consistent with, and extend the results of, univariate analysis of spectral intensities. Commercial EEG setup (Lievesley et al., 2011) was used to extract EEG patterns from 14 electrodes. Raw EEG signals were pre-processed using Surface Laplacian filter, Band pass filter (Babiloni et al., 2000; Blanchard and Blankertz, 2004; Cincotti et al., 2001; Dornhege et al., 2003). Fast Fourier Transform, power spectrum density and independent component analysis to extract features (Hosni et al., 2007; Olesen, 2012). The main focus have been discrimination of α and β rhythms for mental and motor imagery tasks. In this study we used EEG recordings of motor task and image based password authentication system to evaluate cognitive and memory performance of human user authentication in image-based password systems. Also we characterized the EEG signals of two different motor imagery tasks for applying as brain-based control of a robotic articulator. Time courses of two different imagery and mental tasks were investigated by the calculation of instantaneous band power changes and patterns and compared whether the quantification of these features could be classified using machine learning classifiers. We observed the variance change of 4.28 and 3.05 % allowing discrimination α - β components. We also found machine learning was not significantly reliable to discriminate both movement imagery data and image-based authentication tasks unlike α -β categorisation

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2015

Rakhi Radhamani, Hemalatha Sasidharakurup, Dhanush Kumar, Nijin Nizar, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Role of Biotechnology simulation and remotely triggered virtual labs in complementing university education”, in 2015 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL), Thessaloniki, Greece, 2015.[Abstract]

Blended learning has been popularized in many universities in the last decade due to the rapid advances in computer technologies and relative increase in the usage of internet connectivity. A major constraint in providing high quality laboratory resources in some universities and in economically challenged countries is high costs, training personnel, training time and maintenance-related issues. Virtual and remote labs complement the real laboratory resources with virtually defined techniques including simulations, animations, remote triggering of the actual equipment and videos that facilitate user interactions. Our goal was to analyze the effectiveness of biotechnology virtual labs in integrating learning process among school and university students of ages 12-15 years and 17-24 years respectively within India. These labs were developed as part of a National mission on Education through ICT. We also focused on the use of virtual and remote labs as a new pedagogy for distance and mobile learning courses and the context of usage outside scheduled classroom timings. The evaluation of biotechnology virtual labs was performed via surveys, including online and manual feedback reports for analyzing the learning process of various student groups. Studies amongst students of different age groups suggested that virtualization helped their active learning in a traditional classroom scenario. Feedback from student users also indicated virtual and remote labs aided, mobile learning by improving their academic performance, after using virtual and remote labs (post usage) as education platform. Feedback statistics showed 90% of students used biotechnology virtual lab techniques and that helped them to get an actual feel of the experiment. All participants scored more than 70% in the post-test, improving the class average from the pre-test scenario. 91% of teachers who participated in the workshops indicated that they could use virtual and remote labs in their daily teaching pro- ess as teaching material thereby reducing their lecture preparation time. Feedback analysis also indicated improved student performance enhancing laboratory education.

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2015

Dhanush Kumar, Hemalatha Sasidharakurup, Rakhi Radhamani, Nijin Nizar, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Mobile Learning and Biotechnology Education via Remote Labs: Deployment-based study on Real Time Shared Resources”, in 9th International Conference on Interactive Mobile and Communication Technologies and Learning 2015, Mediterranean Palace Hotel, Thessaloniki, Greece., 2015.[Abstract]

With recent advances in ICT, virtual and remote laboratories have become ubiquitous as a complementary tool allowing student users to access a mobile platform and utilize real-time shared equipment over the internet. In this paper, we explore the role of biotechnology remotely controlled labs in augmenting student education via allowing real time shared resources. We deployed 23 virtual laboratories with 218 virtual experiments in biotechnology to provide an online laboratory experience that allowed students and teachers to share and augment conceptual and practical knowledge. Student users reported high usability and repeatability of experimental process and suggested virtual labs as complementing tool for augmenting student’s perception in an active learning scenario. Hybrid approaches in mobile learning indicated student users preferred a blended learning role via classrooms. We also observed that performance in examinations improved with those students using remote labs. We also evaluated the role of virtual labs as a teaching tool for university teachers.

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2015

Manjusha Nair, Shan Surya, Revathy S Kumar, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Efficient simulations of spiking neurons on parallel and distributed platforms: Towards large-scale modeling in computational neuroscience”, in 2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS), Trivandrum, India, 2015.[Abstract]

Human brain communicates information by means of electro-chemical reactions and processes it in a parallel, distributed manner. Computational models of neurons at different levels of details are used in order to make predictions for physiological dysfunctions. Advances in the field of brain simulations and brain computer interfaces have increased the complexity of this modeling process. With a focus to build large-scale detailed networks, we used high performance computing techniques to model and simulate the granular layer of the cerebellum. Neuronal firing patterns of cerebellar granule neurons were modeled using two mathematical models Hodgkin-Huxley (HH) and Adaptive Exponential Leaky Integrate and Fire (AdEx). The performance efficiency of these modeled neurons was tested against a detailed multi-compartmental model of the granule cell. We compared different schemes suitable for large scale simulations of cerebellar networks. Large networks of neurons were constructed and simulated. Graphic Processing Units (GPU) was employed in the pleasantly parallel implementation while Message Passing Interface (MPI) was used in the distributed computing approach. This allowed to explore constraints of different parallel architectures and to efficiently load balance the tasks by maximally utilizing the available resources. For small scale networks, the observed absolute speedup was 6X in an MPI based approach with 32 processors while GPUs gave 10X performance gain compared to a single CPU implementation. In large networks, GPUs gave approximately 5X performance gain in processing time compared to the MPI implementation. The results enabled us to choose parallelization schemes suitable for large-scale simulations of cerebellar circuits. We are currently extending the network model based on large scale simulations evaluated in this paper and using a hybrid - heterogeneous MPI based multi-GPU architecture for incorporating millions of cerebellar neurons for assessing physiolo- ical disorders in such circuits.

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2015

Manjusha Nair, Prasanth Madhu, Vyshnav Mohan, Arathi G Rajendran, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “GPGPU implementation of information theoretic algorithms for the analysis of granular layer neurons”, in 2015 International Conference on Computing and Network Communications (CoCoNet), IEEE, 2015.[Abstract]

Methods originally developed for communication systems are widely used in computational neuroscience to understand the information representation and processing performed by neurons and neural circuits in the brain. Information theoretic quantities Entropy and Mutual Information (MI) have been used in neuroscience as a metric to estimate the efficiency of information representation by neurons. These quantities are used here to measure the stimulus discrimination reliability of the cerebellar granule neurons using simulated response trains produced by a multi-compartmental model of Wistar rat neuron. With &nbsp;1011 granule neurons in the cerebellum, understanding spatio-temporal processing in such structures demands efficient, fast algorithms. Since the serial version of the algorithm had multiple estimation loops which increased the process time considerably with the problem size, we re-implemented the MI algorithm in GPGPU hardware as an efficient way of parallelizing the MI computations. Task-level parallelism and GPU optimizations were used to improve the process time. Estimates on GPGPUs showed 15X time efficiency compared to the CPU version of the algorithm. In order to understand learning inside the cerebellar circuit, synaptic plasticity conditions were simulated in the neuron model. We were able to quantify the stimulus discrimination reliability of granule neurons under control, LTP and LTD conditions and the analysis revealed that stimulus discrimination capability of the neuron was increased during high plasticity state.

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2015

Chaitanya Nutakki, Asha Vijayan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementing Cerebellar Biophysics for Trajectory planning in Robotic arms”, in Proceedings of the International symposium on Translational Neuroscience & XXXIII Annual Conference of the Indian Academy of Neurosciences, Panjab University, Chandigarh , India, 2015.

2015

Nidheesh Melethadathil, Priya Chellaiah, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Classification and Clustering for Neuroinformatics: Assessing the efficacy on reverse-mapped NeuroNLP data using standard ML techniques”, in Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, India, 2015.[Abstract]

NeuroinformaticsNatural Language Processing (NeuroNLP) relies on clustering and classification for information categorization of biologically relevant extraction targets and for interconnections to knowledge-related patterns in event and text mined datasets. The accuracy of machine learning algorithms depended on quality of text-mined data while efficacy relied on the context of the choice of techniques. Although developments of automated keyword extraction methods have made differences in the quality of data selection, the efficacy of the Natural Language Processing (NLP) methods using verified keywords remain a challenge. In this paper, we studied the role of text classification and document clustering algorithms on datasets, where features were obtained by mapping to manually verified MESH terms published by National Library of Medicine (NLM). In this study, NLP data classification involved comparing 8techniques and unsupervised learning was performed with 6 clustering algorithms. Most classification techniques except meta-based algorithms namely stacking and vote, allowed 90% or higher training accuracy. Test accuracy was high (=>95%) probably due to limited test dataset. Logistic Model Trees had 30-fold higher runtime compared to other classification algorithms including Naive Bayes, AdaBoost, Hoeffding Tree. Grouped error rate in clustering was 0-4%. Runtime-wise, clustering was faster than classification algorithms on MESH-mapped NLP data suggesting clustering methods as adequate towards Medline-related datasets and text-mining big data analytic systems. © 2015 IEEE.

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2015

Chaitanya Medini, Asha Vijayan, Ritu Maria Zacharia, Lekshmi Priya Rajagopal, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Spike Encoding for Pattern Recognition: Comparing Cerebellum Granular Layer Encoding and BSA algorithms”, in Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, India, 2015.[Abstract]

Spiking neural encoding models allow classification of real world tasks to suit for brain-machine interfaces in addition to serving as internal models. We developed a new spike encoding model inspired from cerebellum granular layer and tested different classification techniques like SVM, Naïve Bayes, MLP for training spiking neural networks to perform pattern recognition tasks on encoded datasets. As a precursor to spiking network-based pattern recognition, in this study, real world datasets were encoded into spike trains. The objective of this study was to encode information from datasets into spiking neuron patterns that were relevant for spiking neural networks and for conventional machine learning algorithms. In this initial study, we present a new approach similar to cerebellum granular layer encoding and compared it with BSA encoding techniques. We have also compared the efficiency of the encoded dataset with different datasets and with standard machine learning algorithms. © 2015 IEEE.

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2015

Asha Vijayan, Chaitanya Medini, Anjana Palolithazhe, Bhagyalakshmi Muralidharan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling Pattern Abstraction in Cerebellum and Estimation of Optimal Storage Capacity”, in Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, India, 2015.[Abstract]

Precise fine-tuning of motor movements has been known to be a vital function of cerebellum, which is critical for maintaining posture and balance. Purkinje cell (PC) plays a prominent role in this fine-tuning through association of inputs and output alongside learning through error correction. Several classical studies showed that PC follows perceptron like behavior, which can be used to develop cerebellum like neural circuits to address the association and learning. With respect to the input, the PC learns the motor movement through update of synaptic weights. In order to understand how cerebellar circuits associate spiking information during learning, we developed a spiking neural network using adaptive exponential integrate and fire neuron model (AdEx) based on cerebellar molecular layer perceptron-like architecture and estimated the maximal storage capacity at parallel fiber-PC synapse. In this study, we explored information storage in cerebellar microcircuits using this abstraction. Our simulations suggest that perceptron mimicking PC behavior was capable of learning the output through modification via finite precision algorithm. The study evaluates the pattern processing in cerebellar Purkinje neurons via a mathematical model estimating the storage capacity based on input patterns and indicates the role of sparse encoding of granular layer neurons in such circuits. © 2015 IEEE.

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2015

Dr. Bipin G. Nair, Hemalata Sasidharakurup, R. Radhamani, Dhanush Kumar, N. Nizar, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Assessing Students and Teachers Experience on Simulation and Remote Biotechnology Virtual labs: A Case Study with a Light Microscopy Experiment”, in Proceedings of 2nd International Conference on e-Learning e-Education and Online Training (eLEOT 2015), Novedrate, Italy, 2015.[Abstract]

With recent trends of using Information and Communication Technologies in education, virtual labs have become more prevalent in classrooms of most schools and universities, especially in South India. The purpose of this paper was to perform a comparative analysis of virtual learning components such as animations, simulations and real-time remotely controlled experiments. As a part of this study, we conducted a series of biotechnology virtual lab workshops for University-level users within India and collected feedback related to the usage of virtual labs via direct approach. The survey amongst the students and teachers suggested simulation-based labs were more preferred in enhancing teaching and learning strategy compared to graphics-mediated animations and remotely controlled experiments. This paper also reports some of the issues faced by virtual lab users. Studies indicated that even though the web-based technologies are a new venture in education, it still poses adaptability issues. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

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2015

Hemalata Sasidharakurup, Dhanush Kumar, R. Radhamani, N. Nizar, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Role of ICT enabled Virtual Laboratories in Biotechnology Education: Case studies on blended and remote learning”, in Proceedings of 18th International Conference on Interactive Collaborative Learning, Florence, Italy, 2015.[Abstract]

Virtual labs are popularized as a visual education tool that offers diverse analysis of experiments through different components like graphics mediated animations, mathematically modeled simulations, user-interactive emulations, remote-triggered experiments and the use of augmented perception haptic devices. With the advances in ICT-based education, virtual labs have become a novel platform that helps users to engage in their proactive learning process. Our goal was to analyze the effective role of biotechnology virtual labs in improving academic performance of students and complementing classroom education. We tested the adaptability, perceived usefulness and ease of use of biotechnology virtual labs on different user groups in sciences and engineering. This study focuses mainly on the student and teacher groups from different universities across India. Feedback data was collected via a direct approach using organized workshops conducted in the year 2014-2015. 85% of participants suggested perceived usefulness of biotechnology virtual labs helped them to improve their academic performance compared to a traditional classroom scenario. Most users indicated the learning materials provided by virtual lab system were easy to understand, thus suggesting the better adaptability of ICT-enabled techniques amongst different users. This augments the role of virtual labs for remote learners all over the world. For India, such learning methods have helped overcome limitations seen in classroom-based education such as equipment accessibility, location and other economic issues. Through these studies, we construe the usage of virtual labs as a next-gen interactive textbook and as a media-rich learning source of distance and blended education.

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2014

Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Large-Scale Simulations of Cerebellar Microcircuit Relays using Spiking Neuron on GPUs.”, in Proceedings of the Eleventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, University of Cambridge, Cambridge, UK, 2014.[Abstract]

This paper uses scientific computing techniques in understanding cerebellar networks and attempts to model functional behavior of circuits via computational neuroscience. Since highly parallel programmable processors like Graphic Processing Units (GPUs) deliver a high compute capacity at low cost, we modeled granular layer neurons of the rat cerebellum on GPUs and reconstructed a network microcircuit of granular layer for predicting computational properties in such circuits. The main objective of this work was to reconstruct models apt for large scale simulations, involving thousands of neurons while maintaining an acceptable degree of biological details. The hypothesis relating to spatio-temporal information processing in the input layer of the cerebellum has been tested using mathematical modeling. The role of mossy fiber excitation and the modulatory role of Golgi cell inhibition on the granule cells were analyzed. A scalable network consisting of up to 2 million neurons were simulated in millisecond time-scale and the performance efficiency of GPUs over CPUs was compared. The main goal was to understand the scalability issues while implementing such large scale networks and to optimize shared memory access. In GPUs, multi-core parallelization allowed efficient management of computational overheads imposed by synaptic dynamics. We also briefly investigated the performance improvements focusing on decreasing memory access times and the role of optimization techniques. This work is a proof-of-concept implementation apt for densely-packed microcircuits of electrotonically compact neurons with targets to optimize real-time performance and scalability.

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2014

Melethadathil N., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Facilitating Neuroscience Surveys using a Meta Path based Neuroinformatics Text-Mining Platform”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

D. Kumar, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Deploying realistic neuron analogues for patch clamp technique education”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

Sasidharakurup H., Radhamani R., Nizar N., Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Neuroscience Virtual Lab decreases teaching time and improves students’ perception in blended learning environment”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

Manjusha Nair, Rajendran A. G., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Analysis and Quantification of Neural Information Processing during Cerebellar Plasticity”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

A. Yoosef, Arathi G. Rajendran, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Parallelization of Cerebellar Granular Layer Circuitry Model for Physiological Predictions”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

Chaitanya Nutakki, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modelling of robotic arm kinematics using cerebellum based internal model”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

Bodda S., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Extracting motor imagery for computer -brain interactions: Using F4 F3 channels for robotic manipulation”, in Proceedings of the International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences, NIMHANS, Bangalore , India, 2014.

2014

Nutakki C., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Robotic arm controlling using spiking neuron network models”, in Proceedings of the International Conference on Recent Advances in Cognition and Health, Banaras Hindu University, Varanasi, 2014.

2014

Bodda S., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Using surface EEG to explore computer brain interactions for robotic manipulation”, in Proceedings of the International Conference on Recent Advances in Cognition and Health, Banaras Hindu University, Varanasi, India, 2014.

2014

Medini C., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Blood Oxygenation Level Dependent (BOLD) Signal Reconstructions on Large Scale Cerebellar Microcircuits to Predict Neuronal Dysfunction”, in Proceedings of the International Conference on Recent Advances in Cognition and Health, Banaras Hindu University, Varanasi, India, 2014.

2014

Parasuram H., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Studying cerebellar dysfunction at single neuron and circuit level”, in Proceedings of the International Conference on Recent Advances in Cognition and Health, Banaras Hindu University, Varanasi, India, 2014.

2014

R. Radhamani, Hemalatha Sasidharakurup, Sujatha, G., Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Virtual Labs Improve Student's Performance in a Classroom”, in E-Learning, E-Education, and Online Training, 2014, vol. 138, pp. 138-146.[Abstract]

With the world wide acceptance of virtual educational technologies, it has been shown that they play a vital role in the scientific arena. The purpose of this paper was to analyze the role of Biotechnology virtual laboratories in integrating student’s learning ability and introducing it as an effective instructional tool in biotechnology courses. A post-usage survey was conducted among the users and included questions about perceptions of virtual laboratories, its role in virtualization of sophisticated instruments. The survey suggested virtual labs usage enhanced autonomous and guided educational methods. Comparing groups on usage of virtual labs against a control (traditional lab), our studies suggest improved performance in students using virtual labs. Usage analysis and surveys indicated that biotechnology virtual labs are significant elements in adaptive learning process in blended classroom environment.

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2014

A. Yoosef, Harilal Parasuram, Chaitanya Medini, Sergio Solinas, Egidio D'Angelo, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Parallelization of a Computational Model of a Biophysical Neuronal Circuitry of Rat Cerebellum”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, New York, NY, USA, 2014.[Abstract]

Rapid progress in biophysical neural network modelling has been observed in the last years as a focus within computational neuroscience. Detailed multi-compartmental neuron models that were built to simulate physiological aspects of cerebellar neurons and microcircuits involve hundreds of equations. Simulating several hundreds of neurons is computationally expensive. Storage of data and run-time evaluations also prove to be major challenges in this kind of scenario, which limits the researchers.

In this paper, we use detailed models of neurons reconstructing the biophysics of cable properties and action ion channel models to generate a neural micro circuitry of cerebellum input layer. We report the process of adapting and profiling a parallel, MPI-based version of the network model on NEURON for large-scale simulations. Using multi-split and distributed approaches, our model was parallelized on multi-core, multi-processor systems. A spatio-temporal activation pattern, called the centre-surround was elicited in the model validating the biophysical role of synaptic inhibition modulating excitatory activation, usually observed during sensory or tactile stimulation. Performance tests were carried out on two heterogeneous computing clusters. We see a significant reduction of computational cost in terms of power and time while simulating parallelized code although the most apt method depended on network size and nature of synaptic connections. We find 'embarrassingly parallel' method augmented efficiency in terms of processor core usage and also decreased simulation time.

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2014

D. Kumar, Hareesh Singanamala, Dr. Krishnashree Achuthan, Sanjeeva Srivastava, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementing a Remote-Triggered Light Microscope: Enabling Lab Access via VALUE Virtual Labs”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, New York, NY, USA, 2014.[Abstract]

Biotechnology and biology education has been known to show declining student interest due to classroom environments and instructor teaching styles, hence we introduced virtual labs as an interactive self-learning material in a blended environment. With ICT-based education becoming ubiquitous, virtual and remote triggered labs have become a novel platform that helps users to engage in a proactive learning process. A promisingly new trend in virtual labs-based education is the development of remote laboratories that are available over the internet and can be accessed by students and teachers. We implemented and deployed a low-cost light microscope using a simple front-end to enable users to have any time-anywhere access. This paper reports the implementation, deployment and user-case studies on the learning and usage based on the remote-triggered virtual lab. This study also focuses on the analysis of using remote-triggered experiments as supplementary laboratory resources for overcoming the problems faced in a traditional lab environment. The study used online feedback surveys for evaluating the learning outcome and the flexibility of user-interactions with the remote labs and reports the status of usage of remote triggered techniques in biology courses. The statistical analysis suggests that remote labs are an easy learning and interactive platform for users from different places.

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2014

R. Radhamani, Hemalatha Sasidharakurup, Dinesh Kumar, Nijin Nizar, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Explicit Interactions by Users Form a Critical Element in Virtual Labs Aiding Enhanced Education – A Case Study from Biotechnology Virtual Labs”, in Technology for Education (T4E), 2014 IEEE Sixth International Conference on, 2014.[Abstract]

Virtual laboratories are ICT tools that are becoming more prevalent in classroom education complementing the lack of resources or tutors while enabling anytime-anywhere student participation scenarios. Specifically disciplines such as biotechnology, which are interaction rich, have seen several types of virtual labs. In this paper, we explore an analysis of student feedback post virtual labs sessions suggesting virtual labs improve teaching and learning experiences via user-interactions. Feedback was collected from undergraduate and postgraduate level students belonging to biotechnology programs. We look at two objectives namely perceived usefulness and the role of interactions on the virtual platform and simulators, in addition to animations. Most data were collected using direct approach via organized workshops. This approach allowed us to extract useful information without concerns of sparseness and unsolicited data compared to remote feedback. Our studies on feedback analysis indicate that student users interpret results in animation based virtual labs. However, a larger percentage of users suggest student usage and performance improved only with interactive simulators rather than animations. Although further tests are being performed, our preliminary studies on 200 participants suggest novel virtual labs models must include a simulation or emulations of lab environment in order to enhance student laboratory skills.

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2014

Dr. Shyam Diwakar, Sandeep Bodda, Chaitanya Nutakki, Asha Vijayan, Dr. Krishnashree Achuthan, and Dr. Bipin G. Nair, “Neural Control using EEG as a BCI Technique for Low Cost Prosthetic Arms”, in In Proceedings of the International Conference on Neural Computation Theory and Applications (NCTA-2014), Rome, Italy, 2014.[Abstract]

There have been significant advancements in brain computer interface (BCI) techniques using EEG-like methods. EEG can serve as non-invasive BMI technique, to control devices like wheelchairs, cursors and robotic arm. In this paper, we discuss the use of EEG recordings to control low-cost robotic arms by extracting motor task patterns and indicate where such control algorithms may show promise towards the humanitarian challenge. Studies have shown robotic arm movement solutions using kinematics and machine learning methods. With iterative processes for trajectory making, EEG signals have been known to be used to control robotic arms. The paper also showcases a case-study developed towards this challenge in order to test such algorithmic approaches. Non-traditional approaches using neuro-inspired processing techniques without implicit kinematics have also shown potential applications. Use of EEG to resolve temporal information may, indeed, help understand movement coordination in robotic arm.

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2014

Chaitanya Medini, Asha Vijayan, Egidio D'Angelo, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Computationally Efficient Bio-realistic Reconstructions of Cerebellar Neuron Spiking Patterns”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, Amrita Vishwa Vidyapeetham, Coimbatore, India, 2014.[Abstract]

Simple spiking models have been known to replicate detailed mathematical models firing properties with reliable accuracy in spike timing. We modified the adaptive exponential integrate and fire mathematical model to reconstruct different cerebellar neuronal firing patterns. We were able to reconstruct the firing dynamics of various types of cerebellar neurons and validated with previously published experimental studies. To model the neurons, we exploited particle swarm optimization to fit the parameters. The study showcases the match of electroresponsiveness of the neuronal models to data from biological neurons. Results suggest that models are close reconstructions of the biological data since frequency and spike-timing closely matched known values and were similar to those in previously published detailed computationally intensive biophysical models. Such spiking models have a number of applications including design of large-scale circuit models in order to understand physiological dysfunction and for various computational advantages.

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2013

Vijilamole Radhamony, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Biochemistry Virtual Lab: For Complementing Lab Practicals”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Remya Krishnan, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Impacts of Virtual Cell Biology Experiments on Non-Biotechnology Users”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

A. Shekar, Hemalatha Sasidharakurup, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Bioinformatics Virtual Lab: Analysis of Student – Content Interaction”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Sujatha G, Dr. Shyam Diwakar, and Dr. Bipin G. Nair, “Exploring Molecular Biology Education through Virtual Labs”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Radhamani R., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Biotechnology Virtual Labs: Usage Case Studies”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Mithula Parangan, Dhanush Kumar, Hareesh Singanamala, Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, “Setting a Low-Cost Remote-triggered Biotechnology Laboratory: Case Study on Light Microscopy”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Hareesh Singanamala, Dhanush Kumar, Mithula Parangan, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Remote Laboratory: Controlling a Robotic Articulator”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Dhanush Kumar, Mithula Parangan, Hareesh Singanamala, Dr. Shyam Diwakar, Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, “Remote Triggered Biotechnology Labs: Implementation Issues and Challenges”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Small Scale Modeling of Cerebellar Networks Using GPUs”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Krishna Chaitanya Medini, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modelling hemodynamic response function (HRF) to predict BOLD response of cerebellum granular layer using simple spiking models”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Nutakki C., Singanamala H, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Forward Kinematics and Inverse Kinematics Algorithms for Controlling Bio Inspired Robotic Articulators”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Bodda S, Dr. Shyam Diwakar, and Dr. Bipin G. Nair, “Analysis of Motor Tasks from EEG for Robotic Arm Control”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

Harilal Parasuram, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Studying plasticity effects in cerebellum granular layer micro circuitry using local field potential reconstruction”, in Proceedings of International symposium on Neurosciences & XXXI Annual Conference of Indian Academy of Neurosciences, University of Allahabad, Allahabad, 2013.

2013

Asha Vijayan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “A cerebellum-like approach for neuromorphic hardware based on bio-realistic model of cerebellar microcircuitry”, in Proceedings of International workshop on Hippocampus: From synapses to behaviour, INCF workshop - IISER, Pune, India, 2013.

2013

Krishna Chaitanya Medini, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Integrating spiking models for BOLD Reconstruction”, in Proceedings of International workshop on Hippocampus: From synapses to behaviour, INCF workshop – IISER, Pune, India, 2013.

2013

Afila Yoosef, Nair, B., and Dr. Shyam Diwakar, “Parallelization of Bio physical Neural circuit models”, in Amrita Bioquest , 2013.

2013

Chaitanya Medini, Nair, B., and Dr. Shyam Diwakar, “Modeling Hemodynamic Response function ( HRF) to predict BOLD response of cerebellum ”, in Amrita Bioquest, 2013.

2013

Harilal Parasuram, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implications of algorithms on LFP reconstruction in cerebellar granular layer”, in International Conference on Biotechnology for innovative applications, Amrita Vishwa Vidyapeetham, Kerala, 2013.

2013

R. Joseph Sebastian, S, U., Menona, V. S., R, M. M., Nair, B., and Dr. Shyam Diwakar, “Structure-Function based Automated Document Analysis System in Neuroinformatic”, in Amrita Bioquest, 2013.

2013

Asha Vijayan, Chaitanya Medini, Hareesh Singanamala, Chaitanya Nutakki, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Classification of robotic arm movement using SVM and Naïve Bayes classifiers”, in Proceedings of Third International Conference on Innovative Computing Technology (INTECH 2013), London, 2013.[Abstract]

Target-oriented approaches have been commonly used in robotics. In 3D space, movement of a robotic arm depends on the target position which can either follow a forward or inverse kinematics approach to reach the target. Predicting the movement of a robotic arm requires prior learning through methods such as transformation matrices or other machine learning techniques. In this paper, we built an online robotic arm to extract movement datasets and have used machine learning algorithms to predict robotic arm articulation. For efficient training, small training datasets were used for learning purpose. Classification is used as a scheme to replace prediction-correction approach and to test whether the method can function as a replacement of usual forward kinematics schemes or predictor-corrector methods in directing a remotely controlled robotic articulator. This study reports significant classification accuracy and efficiency on real and synthetic datasets generated by the device. The study also suggests linear SVM and Naïve Bayes algorithms as alternatives for computational intensive learning schemes while predicting articulator movement in laboratory environments.

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2012

Manjusha Nair and Dr. Shyam Diwakar, “Quantifying stimulus information in spike trains during plasticity”, in INCF workshop, India, 2012.

2012

Parasuram H. and Dr. Shyam Diwakar, “Constraining extracellular matrix by modeling local field potential”, in INCF workshop, India, 2012.

2012

J. Freeman, Nagarajan, A., Parangan, M., Kumar, D., Dr. Shyam Diwakar, and Dr. Krishnashree Achuthan, “Remote triggered photovoltaic solar cell lab: Effective implementation strategies for Virtual Labs”, in Technology Enhanced Education (ICTEE), 2012 IEEE International Conference on, Kerala, 2012.[Abstract]

Remote triggered laboratories are an excellent way to provide access to costly labs and equipment for students in areas without such facilities. A novel remote triggered photovoltaic solar cell experiment is presented here. This experiment enables the student to learn in a hands-on, practical way about the fundamental characteristics of photovoltaic solar cells. The experiment has a web interface in which the student can turn a number of light bulbs on and off, adjust the load voltage of the solar cell, and view the experiment in real-time via a web-cam. In addition, the characteristics of the solar cells under these various conditions are measured and displayed on the web interface in a spreadsheet and are plotted in a novel and learning-effective manner. This experiment has been hosted on our Virtual Labs website for over a year, with a large number of students using the site. This paper presents implementation strategies and methods used which have proven effective for Virtual Labs, along with a technical description of the experiment and the system used to create and host the experiment.

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2011

Dr. Bipin G. Nair, Dr. Shyam Diwakar, Parasuram H., Medini C, Manjusha Nair, Melethadathil N., Naldi G., and D’Angelo E., “Modeling evoked local field potentials in the cerebellum granular layer and plasticity changes reveal single neuron effects in neural ensembles”, in Acta Physiologica, 2011.

2011

Dr. Shyam Diwakar, “ Information processing in the cerebellum granular layer and changes in plasticity revealing single neuron effects in neural ensemble”, in Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, 2011.[Abstract]

In the current work, an estimate of information flow in terms of spikes in the cerebellum granular layer is discussed. Information transmission at the Mossy Fiber (MF) - Granule cell (GrC) synaptic relay is crucial to understand mechanisms of signal coding in the cerebellum [Albus,1971] [Marr, 1969]. To quantify the information transfer of a whole neuron, we used a computational model of a cerebellar granule cell [Diwakar, 2009], where the excitatory input space could be explored extensively. MFs convey afferent signals to GrCs following sensory stimulation. Plasticity was simulated in the granule cell model by changing the intrinsic excitability and release probability of the cells. Information coding in neurons or brain cells occur as excitatory post-synaptic potentials (EPSPs) and as spikes. The role of both EPSPs and spikes as information content relating the neuron’s response to given input stimuli was explored. LTP favored generation of spikes whereas LTD favored EPSPs as expected, although the percentage of spikes was higher at low release probabilities than the percentage of EPSPs at higher release probabilities. The role of selective inhibition by Golgi cells for coincidence detection is presented.

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2011

Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Information Coding in Single Granule Neuron of the Cerebellum”, in Proceedings of the International symposium on Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, 2011.

2011

Wayland A, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Electroresponsiveness of cerebellar granule neuron and regulation of spatio-temporal processing in the cerebellar granular layer”, in Proceedings of the International symposium on Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, 2011.

2011

Melethadathil N., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Neuroinformatics database for multi-level physiological mapping based on sematic clustering”, in Proceedings of the International symposium on Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, 2011.

2011

Parasuram H., Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Using detailed biophysical models to reconstruct cerebellar post-synaptic evoked local field potential reveals single neuron effects in population code”, in Proceedings of the International symposium on Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, 2011.

2011

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Prema Nedungadi, and Dr. Bipin G. Nair, “VirtualLabs: Pervasive education & scenes from an ICT perspective”, in Proceedings of the 5TH GUIDE INTERNATIONAL CONFERENCE 2011, Rome, 2011.

2011

Medini C and Dr. Shyam Diwakar, “Modeling cerebellar granular layer microcircuitry reveals role of single neurons in spatiotemporal encoding”, in INCF workshop, India, 2011.

2011

Prema Nedungadi, Raghu Raman, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Virtual Labs Collaborative & Accessibility Platform (VLCAP)”, in Proceedings of The 2011 IAJC-ASEE International Conference , 2011.[Abstract]

India has embarked on a National Mission project to build over 150 Virtual Labs (VL) targeting over 1450 experiments mapped to the under graduate and postgraduate curriculum. Due to the lack of user centric tools and mechanisms for VL authors, it became crucial to architect a Virtual Labs Collaborative and Accessibility Platform (VLCAP) for use by the large scientific community building multi-disciplinary VL.With multi-tier, scalable architecture at its core, the technology platform allows VL builders to focus on particular logic of their experiments. The axiomatic design of the user interfaces built into the various modules including VL workbench, collaborative content management, repositories and so on assists in functional use of the elements while reducing the overall development time of VL by individual users. Integration of common tasks in user management, such as single sign-on, role based access control etc. enhances flexibility without compromising on security.

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2011

Prema Nedungadi, Raman, R., Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Collaborative & Accessibility Platform for Distributed Virtual Labs”, in in press, IAJC-ASEE Joint International Conference on Engineering and Technology, Hartford, USA, 2011.

2011

Dr. Krishnashree Achuthan, K.S. Sreelatha, S. Surendran, Dr. Shyam Diwakar, Prof. Prema Nedungadi, S. Humphreys, Dr. Sreekala C. O., Dr. Zeena S. Pillai, Raghu Raman, A. Deepthi, Rathish Gangadharan, Dr. Saritha A., Jyothi Ranganatha, Sreedha Sambhudevan, and Suma Mahesh, “The VALUE @ Amrita Virtual Labs Project: Using Web Technology to Provide Virtual Laboratory Access to Students”, in Global Humanitarian Technology Conference (GHTC), 2011 IEEE, 2011, pp. 117-121.[Abstract]

In response to the Indian Ministry of Human Resource Development (MHRD) National Mission on Education through Information and Communication Technology (NME-ICT) Initiative, the Virtual and Accessible Laboratories Universalizing Education (VALUE @ Amrita) Virtual Labs Project was initiated to provide laboratory-learning experiences to college and university students across India who may not have access to adequate laboratory facilities or equipment. These virtual laboratories require only a broadband Internet connection and standard web browser. Amrita Vishwa Vidyapeetham University is part of a consortium of twelve institutions building over two hundred virtual labs covering nine key disciplines in science and engineering. This National Mission project hopes to reach out to India's millions of engineering and science students at both undergraduate and postgraduate levels. The Virtual Labs Project is providing virtual laboratory experiments that directly support the All India Council for Technical Education (AICTE) and the University Grants Commission (UGC) model curricula for engineering and sciences undergraduate and postgraduate programs.

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2010

M. Parangan, C. Asok, H. Parasuraman, Dr. Krishnashree Achuthan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling Action Potentials and Bursting Phenomena using Analog Electrical Neurons”, in Proceedings of ACM A2CWIC (in press), 2010.

2010

P. James, N. Abdulmanaph, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Exploring input-output characteristics of the cerebellar granule neuron: role of synaptic inhibition, spike timing and plasticity”, in Proceedings of Neurocomp (Lyon, France), 2010.

2010

P. James, Abdulmanaph, N., Nair, B., and Dr. Shyam Diwakar, “Exploring input-output characteristics of the cerebellar granule neuron: role of synaptic inhibition”, in Cinquième conférence plénière fran caise de Neurosciences Computationnelles, ''Neurocomp'10'', Lyon, France, 2010.[Abstract]

Understanding functional role of bursts firing is vital in understanding coding of sensory information [1]. Regulating the burst is related to stimulus properties and neural heterogeneities [2].The granule cells form the largest neuronal population in the mammalian brain and regulate information transfer along the major afferent systems to the cerebellum. Understanding how the granule cell processes information appears critical to understand the cerebellar function. We used a mathematical model of cerebellar granule cell to explore information transmission in mossy fibre - granule cell synapse of the cerebellum. The impact of plasticity changes in excitatory synaptic release probability and variation in intrinsic excitability of granule cell was studied combining the modulatory effects of inhibition. We explored the changes in pre and post synaptic factors to study spiking properties and report their influence on first spike latency and spike amplitude, revealing the indicators of information encoding in individual neurons More »»

2010

S. Subramaniyam, Chaitanya Medini, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and , “Modeling spatio-temporal processing in cerebellar granular layer and effects of controlled inhibition on plasticity”, in Cinquième conférence plénière française de Neurosciences Computationnelles,'Neurocomp'10', 2010.[Abstract]

The cerebellum input stage has been known to perform spatio-temporal transformations and combinatorial operations [1] [2] on input signals. In this paper, we developed a model to study information transmission and signal recoding in the cerebellar granular layer and to test observations like center-surround organization and time-window hypothesis [1] [3]. Detailed biophysical models were used to study synaptic plasticity and its effect in generation and modulation of spikes in the granular layer network. Our results indicated that spatio-temporal information transfer through the granular network is controlled by synaptic inhibition [1]. Spike amplitude and number of spikes were modulated by LTP and LTD. Both in vitro and in vivo simulations indicated that inhibitory input via Golgi cells acts as a modulator and regulates the post synaptic excitability.

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2010

N. Abdulmanaph, Harilal Parasuraman, Dr. Bipin G. Nair, Dr. Shyam Diwakar, and , “Modeling granular layer local field potential using single neuron and network based approaches to predict LTP/LTD in extracellular recordings”, in Cinquième conférence plénière française de Neurosciences Computationnelles,'Neurocomp'10', 2010.[Abstract]

Local field potentials (LFPs) are recorded as waveforms of extracellular activity that arise from complex interactions of spatial distribution of current sources, time dynamics, spatial distribution of dipoles apart underlying conductive properties of the extracellular medium. We reconstructed granular layer post-synaptic LFP by two different approaches in order to test and parameterize the molecular mechanisms of cellular function with network properties. In the first, we used a single granule neuron as a model kernel for reconstructing population activity. The second approach consisted using a detailed network model. LTP and LTD could regulate the spatiotemporal pattern of granular layer responses to mossy fibre inputs. The effect of changes in synaptic release probability and modulation in intrinsic excitability of granule cell on LFP was studied. The study revealed cellular function was represented in LFP wave revealing the activity of underlying neurons. Changes to cell during LTP and LTD were reflected by LFP wave as an indicator of the function of granule neurons as spatial pattern generators. Both modeling approaches generated LFP in vitro [16] and in vivo [17] waveforms as reported in experiments.

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2010

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, and Prof. Prema Nedungadi, “Biotechnology virtual labs- integrating wet-lab techniques and theoretical learning for enhanced learning at universities”, in DSDE 2010 - International Conference on Data Storage and Data Engineering, Bangalore, 2010, pp. 10-14.[Abstract]

For enhanced education at the level of University courses such as those in biology or biotechnology, one of the key elements is the need of time and expertise to allow the student to familiarize laboratory techniques in par with regular theory. The Sakshat Amrita virtual biotechnology lab project focusing on virtualizing wet-lab techniques and integrating the learning experience has added a new dimension to the regular teaching courses at the University. Establishing virtual labs requires both domain knowledge and virtualizing skills via programming, animation and device-based feedback. Challenges in the biotechnology sector in setting up a laboratory that integrates both the feel and phenomenon includes the medley of multiple techniques. This paper reports one such cost-effective process used in virtualizing a real biotechnology lab at the University-level. The major challenge in setting up an effective knowledge dissemination for laboratory courses was not only the scientific approach of biotechnology, but included the virtualization aspects such as usage/design scalability, deliverability efficiency, network connectivity issues, security and speed of adaptability to incorporate and update changes into existing experiments. This paper also discusses an issue-specific case-study of a functional virtual lab in biotechnology and its many issues and challenges. © 2010 IEEE. More »»

2010

Dr. Manitha B. Nair, Melethadathil, N., Dr. Bipin G. Nair, Dr. Shyam Diwakar, and Manjusha Nair, “Information processing via post-synaptic EPSP-spike complex and model-based predictions of induced changes during plasticity in cerebellar granular neuron”, in Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore, 2010.[Abstract]

Understanding functional role of spike bursts in the brain circuits is vital in analyzing coding of sensory information. Information coding in neurons or brain cells happen as spikes or action potentials and excitatory post-synaptic potentials (EPSPs). Information transmission at the Mossy fiber- Granule cell synaptic relay is crucial to understand mechanisms of signal coding in the cerebellum. We analyzed spiking in granule cells via a detailed computational model and computed the spiking-potentiation contributing to signal recoding in granular layer. Plasticity is simulated in the granule cell model by changing the intrinsic excitability and release probability of the cells. Excitatory post synaptic potentials and spikes on varying Golgi cell (GoC) inhibition and Mossy fiber(MF) excitation were analyzed simultaneously with the effect of induced plasticity changes based on the timing and amplitude of the postsynaptic signals. It is found that a set of EPSPs reaching maximum threshold amplitude are converted to less number of high amplitude EPSPs or spikes. Exploring the EPSP-spike complex in granular neurons reveal possible mechanisms and quantification of information encoding in individual neurons of the cerebellar granular layer. Therefore, our study is potentially an important estimation of cerebellar function. © 2010 ACM.

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2010

M. Parangan, Aravind, C., Parasuraman, H., Dr. Krishnashree Achuthan, Nair, B., and Dr. Shyam Diwakar, “Action potential and bursting phenomena using analog electrical neuron”, in Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore, 2010.[Abstract]

A neuron or nerve cell has passive components due to resistive-capacitive nature of circuitry and active current components contributed by ion channels. Biophysical neurons represent active and passive components by differential equations. The differential equations of the biophysical model were integrated by making arithmetic operations on voltage model circuits. Analog neuronal model using voltage integrator circuits is the main focus of this paper. The work involves two circuit models and also addresses design and passive properties of analog neuron model along with the effects of Na+ and K+ ionic channels. In the first simpler circuit, an action potential was generated. In the enhanced second model, sodium and potassium currents were generated separately along with action potential. Impacts of noise and various geometrical signals on the action potential and ionic channels were studied to analyze the effects of membrane resistance and capacitance changes in membrane potential and ionic channels. Besides its use in neuromorphic network research, the model has been successfully in virtual labs and for teaching practice. © 2010 ACM. More »»

2010

H. Parasuraman, N. Abdulmanaph, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Reconstructing extracellular local field potential in cerebellar granular layer networks”, in Proceedings 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010, Changsha, 2010, pp. 1504-1509.[Abstract]

Local field potentials (LFPs) arise from complex interactions of spatial distribution of current sources, time dynamics, spatial distribution of dipoles apart underlying conductive properties of the extracellular medium. We reconstruct LFP in order to test and parameterize the molecular mechanisms of cellular function with network properties. The sensitivity of LFP to local excitatory and inhibitory connections was tested using two novel approaches. In the first, we used a single granule neuron as a model kernel for reconstructing population activity. The second approach consisted using a detailed network model. L TP and LTD could regulate the spatiotemporal pattern of granular layer responses to mossy fiber inputs. The effect of changes in synaptic release probability and modulation in intrinsic excitability of granule cell on LFP was studied. The study revealed cellular function was represented in LFP wave revealing the activity of underlying neurons. Changes to cell during L TP and LTD were reflected by LFP wave as an indicator of the function of granule neurons as spatial pattern generators. Both modeling approaches generated LFP in vitro [16] and in vivo [17] waveforms as reported in experiments. © 2010 IEEE.

More »»

2010

C. Medini, S. Subramaniyam, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Modeling cerebellar granular layer excitability and combinatorial computation with spikes”, in Proceedings 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010, Changsha, 2010, pp. 1495-1503.[Abstract]

The cerebellum input stage has been known to perform combinatorial operations [1] [3] on input signals. In this paper, we developed a model to study information transmission and signal recoding in the cerebellar granular layer and to test observations like center-surround organization and time-window hypothesis [1] [2]. We also developed simple neuron models for abstracting timing phenomena in large networks. Detailed biophysical models were used to study synaptic plasticity and its effect in generation and modulation of spikes in the granular layer network. Our results indicated that spatio-temporal information transfer through the granular network is controlled by synaptic inhibition [1]. Spike amplitude and number of spikes were modulated by L TP and LTD. Both in vitro and in vivo simulations indicated that inhibitory input via Golgi cells acts as a modulator and regulates the post synaptic excitability. © 2010 IEEE.

More »»

2010

N. Abdulmanaph, P. James, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Characterizing information transmission in cerebellar granule neuron”, in Proceedings 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010, Changsha, 2010, pp. 1487-1494.[Abstract]

At the cellular scale, single-neurons process information mainly through spikes or action potentials [1]. Although the types of synaptic plasticity and the range of times cales over which they operate suggest that synapses have a more active role in information processing, the parameter space still remains unexplored. We used a mathematical model of cerebellar granule cell to explore information transmission in mossy fibre - granule cell synapse of the cerebellum. The impact of plasticity changes in excitatory synaptic release probability and variation in intrinsic excitability of granule cell was studied combining the modulatory effects of inhibition. We explore the changes in pre and post synaptic factors and report their influence on first spike latency and spike amplitude, revealing the indicators of information encoding in individual neurons [2]. © 2010 IEEE.

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2008

Dr. Shyam Diwakar, Naldi, G., and D’Angelo, E., “Computational modeling predicts activation patterns and plasticity in the cerebellar circuit”, in FENS, Geneva, Switzerland, 2008.

2008

Dr. Shyam Diwakar, Naldi, G., and D’Angelo, E., “Computational modeling of extracellular local field potentials predicts activation patterns and plasticity in the cerebellar circuit”, in GRC Sensory coding and Natural environment conference at Barga, Italy, 2008.

2008

Dr. Shyam Diwakar, Naldi, G., and D’Angelo, E., “Computational modeling of LFP and predictions on granular layer plasticity”, in Front. Neuroinform. Conference Abstract: Neuroinformatics, 2008.[Abstract]

Extracellular field potentials of brain network activity exhibit special characteristics at ms scale (Gold et al., JNphysiol, 2006, 95, 3113-3128), that can be used to predict several intracellular parameters including width and number of action potentials (Csicsvari et al., JNphysiol, 2003, 90, 1314-1323). A detailed multicompartmental model of a cerebellar granule cell was developed from available single compartmental model (D'Angelo et al., J Nsc, 2001, 21, 759-770) and was used to simulate responses to mossy-fibers excitation, which were then used to reconstruct the extracellular potentials. The cell model was developed with NEURON (Hines et al, Neural Comput, 1997, 9, 1179-1209) and comprised 52 compartments with an explicit representation of the axon ascending branch(Full parallel fiber simulations gave similar results). The spike originated in the axon and invaded at high speed the somato-dendritic compartment, which was iso-potential. The model nicely reproduced spike retrograde propagation and Na+ currents in patch-clamp experiments.

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2007

Dr. Shyam Diwakar, Naldi, G., and D’Angelo, E., “Computational modeling predicts activation patterns and plasticity in the cerebellar circuit”, in SINS, Society of Italian Neuroscience at Verona, Italy, 2007.

2006

Dr. Shyam Diwakar, Naldi, G., and D’Angelo, E., “Reconstructing Extracellular field potentials with a multi-compartmental cerebellar granule cell model”, in Node and Network meeting organized by University of Pavia, Pavia, Italy, 2006.

2004

Dr. Shyam Diwakar, “Does the glomerulus function as a multiclass support vector machine? –Modeling the olfactory system from a machine learning perspective”, in joint international conference on Neuroscience organized by IAN SNCI, Hyderabad, India , 2004.

### Publication Type: Conference Proceedings

Year of Publication Title

2018

Dr. Shyam Diwakar, Balachandran A., Nutakki C., Sandeep Bodda, and Dr. Bipin G. Nair, “Experimental Recording and Assessing Gait Phases Using Mobile Phone Sensors and EEG”, Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India. 2018.

2014

L. Ramakrishnan, Aarathi Krishna, Asha Vijayan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Implementing cerebellar neural network in FPGA”, International symposium on Translational Neuroscience & XXXII Annual Conference of the Indian Academy of Neurosciences. NIMHANS, Bangalore, India, 2014.

2014

Dr. Shyam Diwakar, Priya Chellaiah, Dr. Bipin G. Nair, and Dr. Krishnashree Achuthan, “Theme Interception Sequence Learning: Deflecting Rubber-Hose Attacks Using Implicit Learning”, In Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) Springer International Publishing. Springer International Publishing, Switzerland, pp. 495-502, 2014.[Abstract]

Existing cryptographic systems use strong passwords but several techniques are vulnerable to rubber-hose attacks, wherein the user is forced to reveal the secret key. This paper specifies a defence technique against rubber-hose attacks by taking advantage of image sequence-based theme selection, dependent on a user’s personal construct and active implicit learning. In this paper, an attempt to allow the human brain to generate the password via a computer task of arranging themed images through which the user learns a password without any conscious knowledge of the learned pattern. Although used in authentication, users cannot be coerced into revealing the secret key since the user has no direct knowledge on the choice of the learned secret. We also show that theme interception sequence learning tool works significantly well with mixed user age groups and can be used as a secondary layer of security where human user authentication remains a priority.

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2013

Asha Vijayan, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Inverse Kinematics with cerebellar spiking neurons”, Amrita Bioquest . 2013.

2012

Asha Vijayan and Dr. Shyam Diwakar, “Cerebellar neural dynamics with spiking neurons show generalization for inverse kinematics problem, INCF workshop”, INCF workshop. 2012.

2011

H. Parasuram, Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Taking project tiger to the classroom: A virtual lab case study”, Communications in Computer and Information Science, vol. 191 CCIS. Kochi, pp. 337-348, 2011.[Abstract]

Understanding how population dynamics change over time is critical to many practical problems as pest control, endangered species protection etc. Teaching population ecology is not easy since data is usually collected over a very long period. This paper discusses a specific tiger population case study relating to growth rate predictions using an online virtual lab. Studying tiger populations and introduction of such data in classrooms help in creating awareness and support new pedagogies to estimate animal population dynamics. We have used online virtual labs which are ready-made tools to perform simple experiments and analysis. An important and usually complex case of population analysis as in tiger populations in India is studied in this paper. Although some major parameters like food, transient movement, and ecosystem details have been ignored, predicted data for tiger population follows closely to actual data for previous years and even predicts the growth rate with a small standard deviation of 10%. Our results with tiger populations come close to the actual census values. We propose the use of simple mathematical models to make assessment of transient animal populations such as tigers, and sharks. Also use of such ready-made pro-academic online tools encourages new studies and an enhanced pedagogy to population ecology for mathematicians, biotechnologists, wildlife institute personnel among many other cross-disciplinary scientists. © 2011 Springer-Verlag.

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## In Media (News)

1. Podcast - Audio interview, Indian uses mathematics for disease detection, Indian Science Journal, April 9, 2016.
2. Times of India - Indian scientist develops computer models to map brain disorders, April 9, 2016.
3. Business Standard - Indian scientist develops computer models to map brain disorders, April 9, 2016.
4. Indian Science Journal - Indian scientist develops computer models to map brain disorders, April 9, 2016.
5. Sify News - Indian scientist develops computer models to map brain disorders, April 9, 2016.
6. Free Press Journal - Indian scientist develops computer models to map brain disorders, April 9, 2016.
7. ANI News - Indian scientist develops computer models to map brain disorders, April 9, 2016.
8. NVIDIA publishes a tech report on GPUs for modeling brain circuits.
9. Computer World India - How Amrita advanced neurological disorders' prediction using GPUs, March 17, 2016
10. CIO report - How Amrita advanced neurological disorders' prediction using GPUs, March 17, 2016
11. The Hindu Business Line - Nvidia eyes India opportunities as digitisation picks up pace, April1, 2016.
12. Express Pharma Interview - The Tesla Platform includes comprehensive system management tools, April 1, 2016
13. MIS Asia - How Amrita advanced neurological disorders' prediction using GPUs, June 28. 2016.
14. Lifeboat Blog  - Link to MIS Asia post, June 28, 2016.
15. Social Discussion: How GPU Tech Is Bringing A Paradigm Shift In Healthcare Research And Cure, HPC Asia, July 18, 2016.
16. Exploring the Science of Meditation – Does Meditation Aid Brain and Mental Health? Indian Science Journal, Oct 21, 2016
17. Scientists identify mechanism that regulates rhythmic brain waves – the rhythm that makes memories permanent, Indian Science Journal, Jan 5, 2017

## Invited roles

1. Regional Associate Editor - International Journal of Online Engineering (iJOE).
2. Reviewer – Frontiers in Neuroinformatics
3. Reviewer - Frontiers in Computational Neuroscience
4. Reviewer – Journal of Physiology
5. Reviewer – Journal of Computational Intelligence and Neuroscience, Hindawi
6. Reviewer – Journal of Universal Computer Sciences
7. Reviewer - OMICS: A Journal of Integrative Biology
8. Reviewer – BMC Neuroscience
9. Reviewer – Neural Computing and Applications, Springer
10. Reviewer- Computers and Education, Elsevier
11. Reviewer - National Academy Science Letters
12. Reviewer and TPC – eLEOT 2016, 3rd International Conference on e-Learning e-Education and Online Training, Dublin, Ireland.
13. Reviewer and TPC - International Conference on Advances in Computing, Communications and Informatics (ICACCI-2016), Jaipur, 2016.
14. Reviewer – WEEF 2015 Conference, World Engineering Education Forum 2015, 18th International Conference on Interactive Collaborative Learning, 20-24 September 2015, Florence. Italy.
15. Reviewer and TPC – eLEOT 2015, 2nd International Conference on e-Learning e-Education and Online Training, Novedrate, Italy.
16. Reviewer and TPC - International Conference on Computing in Mechanical Engineering (ICCME’15), Aug 10-13, India.
17. Reviewer and TPC - International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, 2015.
18. Session chair and speaker – EEG/MEG analysis and applications 1, International Joint Conference on Neural Networks IJCNN 2015 and IJCNN workshop W04, Computational Neurology and Psychiatry: Do we need it?
19. Review committee - 2014 International Conference on Networks & Soft Computing
20. International program committee member, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI-2014), 2014.
21. International program committee member, 2012 International Conference on Advances in Computing, Communications and Informatics (ICACCI-2012), Chennai, India, Aug 3-5, 2012.
22. International program committee member, International Conference on Technology Enhanced Education, Amritapuri, Kerala, India, Jan 3-5, 2012.
23. Reviewer, Session chair and local organizer – International Conference on Biotechnology for Innovative Application (Amrita Bioquest 2013), Aug 10-13, 2013.
24. International program committee member, International Conference on Computer Technology and Development 2011.
25. Reviewer and Program committee member, International Conferences on Advances in Computing and Communications (ACC 2011), Kochi, India.
26. Reviewer, international conference on computational intelligence ICCI 2010, (Coimbatore, India) Dec 9-11, 2010.
27. Reviewer and session chair, IEEE BIC-TA (Liverpool, UK), 2010, Sept 8-10, 2010.
28. Program committee member and reviewer: 2nd Workshop on Emerging eLearning Web Technologies (EeLT 2009), April 27, 2009 at Poznan, Poland.

## Talks

1. Invited Talk - Cerebellum: Modeling, Dynamics and Motor learning, The 5th Bangalore Cognition Workshop - Where Minds meet the brain, Indian Institute of Science, Bengaluru, June 17-29, 2018.
2. Invited Talk - Modeling the Brain - Cerebellum, Motor Control and Neurological Predictions, Amrita Institute of Medical Sciences, May 4, 2018.
3. Invited Talk - Cerebellum, motor learning and neurological conditions: biophysics of single neurons to microcircuits abstractions, Dept of Biosciences, IIT Bombay, April 16, 2018.
4. Invited Talk - Modeling, OER, and Open Models - Work at Amrita, RIKILT, Ministry of Economic Affairs and the Netherlands Food and Consumer Product Safety Authority (NVWA), Wageningen, The Netherlands, March 26, 2018.
5. Invited Talk - Challenges for OER and Open Medical Models - Case studies from big data and virtual laboratory environments at National Conference on Open Data and Data Repositories (NCODDR), organized by Cochin University of Science And Technology (CUSAT), March 6, 2018.
6. Talk - Using Learning Theory for Assessing Effectiveness of Laboratory Education Delivered via a Web-based Platform , International Conference on Remote Engineering and Virtual experimentation (REV 2018), Dusseldorf, Germany, March 21-24, 2018.
7. Invited Talk - Modeling of neurovascular coupling, neural activity and BOLD, From cell physiology to integrated signals and emerging brain functions, School of Brain Cells & Circuits "Camillo Golgi", Nov 29- Dec 3, 2017, Erice, Italy.
8. Talk and conference workshop - Computational Neuroscience of cerebellum and interconnected circuits, Workshop on Bioinspired modeling and Computational Neuroscience - From neurons, circuits to models and devices (BioCompNeuro'17) (Organiser and Workshop Chair), co-affiliated with Sixth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2017), Sept 16-19, 2017, Manipal, India.
9. Talk - Computations and cerebellum: Modeling Cerebellar Neurons and their behavioral dynamics, Aug 23, 2017, Indian Institute of Technology Madras, Chennai, India.
10. Talk - Computational neuroscience of cerebellum: cellular and circuit roles, timing and plasticity, Aug 17, 2017, Indian Institute of Technology Hyderabad, Hyderabad, India.
11. Talk - Connecting Data to Clinical Predictions: Using Computational Neuroscience for bridging Modern Medicine to Ayurvedic explorations, Amrita Samyogam 2017- International Conference on Integrative Ayurveda and Modern Medicine, Aug 6-7, 2017, Amrita Institute of Medical Sciences and Research, Kochi, India.
12. Talk - From Data to Models and onto Robotics, Robotsavam 2017, techfest on robotics organized by Department of Electronics and Communication Engineering, Amrita School of Engineering, July 30, 2017, Amrita Vishwa Vidyapeetham, Amritapuri campus, Kollam, India.
13. Talk - From our Present to a better Future, One-day Workshop for Young Faculty Research Fellow under Visvesvaraya PhD scheme organized by Medial Labs Asia and MeitY, Government of India at Indian Institute of Science, Bengaluru, India, July 28, 2017.
14. Invited Talk - Computational Neurosciences of Cerebellar Circuit Disorders: Interpretations in the cerebellar granular layer microcircuit, School of Brain Cells & Circuits "Camillo Golgi", Dec 1-5, 2016, Erice, Italy.
15. Talk - Computational Neuroscience of Circuit Function and Dysfunction: a Cerebellum Perspective, Symposium 8, Neurocognitive networks in health, disease and recovery, XXXIV Annual Meeting of Indian Academy of Neurosciences (IAN), National Brain Research Center, Manesar, India, Oct 19-21, 2016.
16. Talk - Using Cerebellar Architecture to Control Low-Cost Robotic Arms , International Symposium on the Neuromechanics of Human Movement, 4th – 6th October 2016, Heidelberg, Germany
17. Invited Talk -Computations in the cerebellar granular layer microcircuit: from Population responses to robotic abstractions, INdAM  Meeting  “NeuroMath, Mathematical and Computational Neuroscience: cell, network and data analysis”, Sept 11- 17, 2016, Cortona, Italy.
18. Invited Talks - On the Exploratory Roles of a Computational Engineer (IT Association), What do Brain Circuits predict Future Electronics to be (ECE Association), Inauguration events, Sri Ramakrishna Engineering College, Coimbatore, Aug 3, 2016.
19. Talk - Erasmus Mundus India4EU II contributions (As Indian Coordinator), India4EU II Final meeting organized by Politecnico di Torino (EU coordinator) at Univ of Porto, Portugal from May 23-25, 2016.
20. Organizer Talk - Virtual Labs in India: Implementation and Case studies, National Nodal Center Conference, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, Kerala, India, May 6, 2016.
21. Invited Talk - Virtual Labs in India, Online Labs workshop organized by International Association of Online Engineering (IAOE) and the Global Online Laboratory Consortium (GOLC), Third International Conference on Transformations in Engineering Education, College of Engineering, Pune, Jan 10, 2016.
22. Invited Talk: From Network Models to Applications and Vice-versa: Cerebellum Network Models and their Abstractions, School of Brain Cells and Circuits "Camillo Golgi", Nov 29-Dec 3, 2015, Ettore Majorana Foundation and Centre for Scientific Culture, Erice, Sicily, Italy.
23. Invited Talk: Experiential Learning and Sustainable Development Goals - Case Stories from Amrita's Live In Labs on How Professors and Students are bringing Immediate Societal Impact, Department of Mathematics, University of Milan, Nov 23, 2015, Milan, Italy.
24. Talk: Mobile Learning and Biotechnology Education via Remote Labs: Deployment-based study on Real Time Shared Resources, 9th International Conference on Interactive Mobile and Communication Technologies and Learning 2015, 19-20 November 2015, Mediterranean Palace Hotel, Thessaloniki, Greece.
25. Talk: Role of Biotechnology Simulation and Remotely Triggered Virtual labs in Complementing University Education, 9th International Conference on Interactive Mobile and Communication Technologies and Learning 2015, 19-20 November 2015, Mediterranean Palace Hotel, Thessaloniki, Greece
26. Talk: Role of ICT enabled Virtual Laboratories in Biotechnology Education: Case studies on blended and remote learning, Proceedings of 18th International Conference on Interactive Collaborative Learning, 2015 World Engineering Education Forum, Florence, Italy, September 20-24, 2015.
27. Invited Talk: Cerebellum-like spatial-temporal pattern recognition circuits using spiking neurons and their role in bio-robotics, International Symposium on Emerging Topics in Circuits and Systems (SET-CAS'15), Special session at the fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Aug 10-13, 2015, Kochi, India.
28. Talk and Session chair: Exploiting Point Source Approximation on Detailed Neuronal Models to Reconstruct Single Neuron Electric Field and Population LFP,  IEEE International Joint Conference on Neural Networks (IJCNN) 2015, Killarney, Ireland, July 12-17, 2015.
29. Talk: Computational Neuroscience of Cerebellar Disorders – Studies of plasticity, timing and dysfunction from a cerebellar granular layer perspective, Computational Neurology and Psychiatry: do we need it? Workshop W04 at International Joint Conference on Neural Networks IJCNN 2015, Killarney, Ireland, 2015.
30. Computational Modeling of Cerebellar Information Processing – Is my cerebellum a pattern recognition circuit?, Engineering hub, University of Lincoln, Lincoln, UK. June 30, 2014.
31. Large-Scale Simulations of Cerebellar Microcircuit Relays using Spiking Neuron on GPUs, Presentation at the  Eleventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, University of Cambridge, Cambridge, UK, June 26-28, 2014.
32. Invited Talk –Modeling Brain circuits and role of bioinspired computing, Malakara Catholic College, Kanyakumari Dt., TN. March 10, 2014.
33. Invited Talk: Computational Modeling of Cerebellar Disorders – Studies of plasticity, timing and dysfunction from a cerebellar granular layer perspective. APSN Neuroscience School and International Conference on Neurochemistry of Ageing Brain, CSIR-IICB, Kolkata, Jan 27-Feb 1, 2014.
34. Invited Talk: Using machine learning towards Neuroinformatics: Analyzing structure-function relationships in data, National Conference on ‘Data Mining Applications in Genomics and Proteomics’, Bharathiar University, Coimbatore, January 24, 2014.
35. Invited Talk: On the Effectiveness of Virtual Labs in Universities - Case studies from an Indian National Mission Project, VI International GUIDE Conference 2013: The Global Economic Crisis and its consequences on the national educational systems: Can online education contribute to overcoming the crisis?, Athens, Oct 3-4, 2013.
36. Organizer Talk: Population activity in the Brain: Abstractions and Applications, DELSA workshop, Amrita Bio Quest 2013: International Conference on Biotechnology for Innovative Applications, Amritapuri, Kollam, Kerala, India, Aug 12, 2013.
37. Organizer Talk: Computational Neuroscience of Single Neuron and Population activity in the Brain: Abstractions and Applications, Amrita Bio Quest 2013: International Conference on Biotechnology for Innovative Applications, Amritapuri, Kollam, Kerala, India, Aug 10-14, 2013.
Talk: Population activity in the Brain: Abstractions and Applications, International workshop –“From Cellular to Circuit and Brain Functions: Passing through Mathematical Models”, Amrita Institute of Medical Sciences, Kochi, Kerala, India, Aug 10, 2013.
38. Invited talk. Modeling single neuron and population activity in the brain: A perspective from scientific computing, 21 June 2013, National Seminar on Scientific Computing, IIITMK, Trivandrum, Kerala, India.
39. Invited talk. Estimation of Information Flow in Neural Circuits using Mutual Information and Related Techniques, 21 May 2013, Faculty Development Program, SCMS School of Engineering and Technology, Karukuttu, Ernakulam, Kerala, India.
40. Invited talk. Computational Neuroscience of Cerebellar Disorders –Studies of plasticity, timing and dysfunction from a cerebellar granular layer perspective, International Conference on Advances in Molecular Mechanisms of Neurological Disorders, 21-23 February 2013, AIIMS, New Delhi, India.
41. Invited talk. Computations in the cerebellar granular layer microcircuit: Timing, plasticity and extracellular field reconstructions, School of Computer and Systems Sciences and School of Computational and Integrative Sciences Jawaharlal Nehru University New Delhi -67, India, Jan 14, 2013
42. Invited talk. Computations in the cerebellar granular layer: Timing, plasticity and extracellular field reconstructions, Moreno Bote Lab, Foundation Sant Joan de Deu, Barcelona, Spain, Nov 6, 2012
43. Invited keynote lecture. “Communication analogies and computing via neuromorphic engineering – a perspective from bio-inspired robotics", 2012 International Conference on Advances in Computing, Communications and Informatics (ICACCI-2012), Chennai, India, Aug 3-5, 2012.
44. Invited lecture. “Superman’s changing room – Virtualization and virtual labs”, International Conference on technology Enhanced Education, Amritapuri, Kerala, India, Jan 3-5, 2012.
45. “A modeling based study on the origin and nature of evoked post-synaptic local field potentials in granular layer”, Department of Mathematics ‘Federigo Enriques’, University of Milan, Dec 6, 2011.
46. “Virtual Labs: Pervasive education & scenes from an ICT perspective”, Proceedings of the 5TH GUIDE INTERNATIONAL CONFERENCE 2011, “E-learning innovative models for the integration of education, technology and research”, Università degli Studi “Guglielmo Marconi”, Rome, 18 – 19 November 2011.
47. Shyam Diwakar and Bharat Jayaraman, Constrained Objects for Neuronal Modeling and Simulation, International symposium on `Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, Oct 30-Nov 1, 2011.
48. Demo presentation: Virtual labs and computational neuroscience – Education and pedagogies. Bernstein Conference 2011, Bernstein Center Freiburg . Hansastraße 9A . D-79104 Freiburg, October 4-6, 2011.
49. Demo presentation, Virtual Labs – Pervasive education and future scenes from an ICT scenario, International Conference on Advances in Computing and Communications (ACC-2011), Kochi, India, July 22-24, 2011.
50. Invited lecture, Department of Mathematics, University of Milan, Milano, Italy, Dec 9, 2010. Title: Mathematics, virtualization and technical education – An Amrita case study into understanding neuroscience via virtual labs and mathematical models.
51. Neurotalk 2010,Track 2-3: Neuromathematics, Neurophysics, Neuroinformatics and Computation Neurobiology, Singapore EXPO, Singapore, June 25, 2010, Title: Neuronal Models and Exploration of Network Properties: A Case Study into Cerebellar Granular Layer Models and Local Field Potential Modeling.TKK, Helsinki, India and EU, Organized by TKK University, Oct 5, 2009.
52. LFP workshop: Modeling and interpretation of extracellular field potentials, January 15-16, 2009 at Oslo, Norway organized by INCF-Norway.

## Memberships

• Senior Member - Institute of Electrical and Electronics Engineers (IEEE).
• Life member - Indian Academy of Neurosciences (IAS)
• Senior Member - International Association of Computer Science and Information Technology (IACSIT)
• Member - Organization for Computational Neurosciences (OCNS)
• Member - International Society of Neurochemistry (ISN)
• Member - Institute for Systems and Technologies of Information, Control and Communication (INSTICC)
• Member - European Alliance for Innovation
• Life Member - Computer Society of India

## Contact

Dr Shyam Diwakar
School of Biotechnology
Amrita Vishwa Vidyapeetham (Amrita Vishwa Vidyapeetham)
Amritapuri, Clappana P.O., Kollam, Kerala, India. Pin:690525
Tel +91 (0476-2896318 Extn:3116
Fax +91 (0)476-2899722