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 Sir Visvesvaraya Young Faculty Research Fellowship by Department of Electronics and Information Technology, Govt. of India in April 2016. He also serves as a executive committee member for Indian Academy of Neurosciences since October 2014.   

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 University.

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.

Publications

Publication Type: Journal Article
Year of Publication Publication Type Title
2016 Journal Article S. Dr. Diwakar, Kumar, D., Radhamani, R., Sasidharakurup, H., Nizar, N., Dr. Achuthan, K., Prema Nedungadi, Raman, R., and Bipin G. Nair Dr., “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, pp. 8–15, 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. Via hands-on workshops and direct feedback using questionnaires, we studied the role of remote lab experiments as learning and teaching tools. Although less reliable than direct feedback, we also included online feedback to perceive blended and remote learning styles among various users. Student and teacher user groups suggested significant usage adaptability of experimental process and indicated usage of remote labs as supplementary tools for complementing laboratory education. Usage analysis implicated the role of online labs as interactive textbooks augmenting student interaction and positive correlates to learning. More »»
2016 Journal Article H. Parasuram, Bipin G. Nair Dr., D‘Angelo, E., Hines, M., Naldi, G., and Dr. Diwakar, S., “Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim”, Frontiers in Computational Neuroscience, vol. 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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2015 Journal Article H. Sasidharakurup, Radhamani, R., Kumar, D., Dr. Diwakar, S., Nizar, N., Nair, B., and Achuthan, K., “Using Virtual Laboratories as Interactive Textbooks: Studies on Blended Learning in Biotechnology Classrooms”, EAI Endorsed Transactions on e-Learning, vol. 15, no. 6, p. e4, 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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2015 Journal Article E. S. Dove, İ Barlas, Ö., Birch, K., Boehme, C., Borda-Rodriguez, A., Byne, W. M., Chaverneff, F., Coşkun, Y., Dahl, M. - L., Dereli, T., Dr. Diwakar, S., Elbeyli, L., Endrenyi, L., Eroğlu-Kesim, B., Ferguson, L. R., Güngör, K., Gürsoy, U., Hekim, N., Huzair, F., Kaushik, K., Kickbusch, I., Kıroğlu, O., Kolker, E., Könönen, E., Lin, B., Llerena, A., Malha, F., Bipin G. Nair Dr., Patrinos, G. P., Şardaş, S., Sert, Ö., Srivastava, S., Steuten, L. M. G., Toraman, C., Vayena, E., Wang, W., Warnich, L., and Özdemir, V., “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 Journal Article S. Ray, Dr. Diwakar, S., Srivastava, S., and Nair, B., “E-learning resources and virtual labs”, Nature India Special Issue: Proteomics Research in Ind, 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 Journal Article R. Raman, Dr. Achuthan, K., Prema Nedungadi, Dr. Diwakar, S., 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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2014 Journal Article S. Dr. Diwakar, Parasuram, H., Medini, Ca, Raman, R., Prema Nedungadi, Wiertelak, Ed, Srivastava, Se, Dr. Achuthan, K., and Bipin G. Nair Dr., “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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2013 Journal Article D. Malhotra, Dr. Diwakar, S., Ozdemir, V., Bipin G. Nair Dr., and Srivastava, S., “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.
2013 Journal Article A. Vijayan, Nutakki, C., Medini, C., Singanamala, H., Bipin G. Nair Dr., Achuthan, K., and Dr. Diwakar, S., “Classifying Movement Articulation for Robotic Arms via Machine Learning”, Journal of Intelligent Computing, vol. 4, no. 3, pp. 123-134, 2013.[Abstract]

<p>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 Naïve 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.</p>

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2012 Journal Article C. Medini, Bipin G. Nair Dr., D'Angelo, E., Naldi, G., and Dr. Diwakar, S., “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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2012 Journal Article S. Ray, Koshy, N. R., Dr. Diwakar, S., Bipin G. Nair Dr., and Srivastava, S., “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 Journal Article Bipin G. Nair Dr., Krishnan, R., Nizar, N., Radhamani, R., Rajan, K., Yoosef, A., Sujatha, G., Radhamony, V., Dr. Achuthan, K., and Dr. Diwakar, S., “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.
2012 Journal Article S. Dr. Diwakar, Dr. Achuthan, K., Prema Nedungadi, and Bipin G. Nair Dr., “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 Journal Article S. Ray, Koshy, N. R., Dr. Diwakar, S., Bipin G. Nair Dr., and Srivastava, S., “Community Page-Sakshat Labs: India's Virtual Proteomics Initiative”, PLoS-Biology, vol. 10, p. 1306, 2012.
2011 Journal Article Ha Parasuram, Bipin G. Nair Dr., Dr. Achuthan, K., and Dr. Diwakar, S., “Taking project tiger to the classroom: A virtual lab case study”, Communications in Computer and Information Science, vol. 191 CCIS, 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. More »»
2011 Journal Article S. Dr. 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. More »»
2011 Journal Article H. Parasuram, Bipin G. Nair Dr., Naldi, G., D’Angelo, E., and Dr. Diwakar, S., “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. More »»
2011 Journal Article S. Dr. Diwakar, Dr. Achuthan, K., Prema Nedungadi, and Bipin G. Nair Dr., “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. More »»
2011 Journal Article R. Raman, Prema Nedungadi, Dr. Achuthan, K., and Dr. Diwakar, S., “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 Journal Article S. Dr. Diwakar, “Computational Neuroscience of Granule Neurons: Biophysical modeling of single neuron and network functions of the cerebellum granular layer”, 2011.
2011 Journal Article S. Dr. 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 »»
2009 Journal Article S. Dr. Diwakar, Magistretti, J., Goldfarb, M., Naldi, G., 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]

Axonal Na channels ensure fast spike activation and back-propagation in cerebellar granule cells. J Neurophysiol 101: 519–532, 2009. First published December 10, 2008; doi: 10.1152/jn. 90382.2008. 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 ... More »»
2008 Journal Article F. Prestori, Rossi, P., Bearzatto, B., Lainé, J., Necchi, D., Dr. Diwakar, S., Schiffmann, S. N., Axelrad, H., and D'Angelo, E., “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. More »»
Publication Type: Conference Paper
Year of Publication Publication Type Title
2015 Conference Paper H. Sasidharakurup, Kumar, D., Radhamani, R., Nizar, N., Nair, B., Achuthan, K., and Dr. Diwakar, S., “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.
2015 Conference Paper B. Nair, Sasidharakurup, H., Radhamani, R., Kumar, D., Nizar, N., Achuthan, K., and Dr. Diwakar, S., “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.
2015 Conference Paper A. Vijayan, Medini, C., Palolithazhe, A., Muralidharan, B., Bipin G. Nair Dr., and Dr. Diwakar, S., “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 Conference Paper C. Medini, Vijayan, A., Zacharia, R. Maria, Rajagopal, L. Priya, Bipin G. Nair Dr., and Dr. Diwakar, S., “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 Conference Paper N. Melethadathil, Chellaiah, P., Bipin G. Nair Dr., and Dr. Diwakar, S., “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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2014 Conference Paper C. Medini, Vijayan, A., D'Angelo, E., Bipin G. Nair Dr., and Dr. Diwakar, S., “Computationally Efficient Bio-realistic Reconstructions of Cerebellar Neuron Spiking Patterns”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, Amrita University, 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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2014 Conference Paper S. Dr. Diwakar, Bodda, S., Nutakki, C., Vijayan, A., Achuthan, K., and Nair, B., “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 Conference Paper M. Nair, Subramanyan, K., Dr. Diwakar, S., and Nair, B., “Parameter optimization and nonlinear fitting for computational models in neuroscience on GPGPUs”, in International Conference on High Performance Computing and Applications (ICHPCA), 2014 , C. V. Raman College of Engineering, Bhubaneswar, 2014.[Abstract]

One of the main challenges in computational modeling of neurons is to reproduce the realistic behaviour of the neurons of the brain under different behavioural conditions. Fitting electrophysiological data to computational models is required to validate model function and test predictions. Various tools and algorithms exist to fit the spike train recorded from neurons to computational models. All these require huge computational power and time to produce biologically feasible results. Large network models rely on the single neuron models to reproduce population activity. A stochastic optimization technique called Particle Swam Optimisation (PSO) was used here to fit spiking neuron model called Adaptive Exponential Leaky Integrate and Fire (AdEx) model to the firing patterns of different types of neurons in the granular layer of the cerebellum. Tuning a network of different types of spiking neurons is computationally intensive, and hence we used Graphic Processing Units (GPU) to run the parameter optimisation of AdEx using PSO. Using the basic principles of swam intelligence, we could optimize the n-dimensional space search of the parameters of the spiking neuron model. The results were significant and we observed a 15X performance in GPU when compared to CPU. We analysed the accuracy of the optimization process with the increase in width of the search space and tuned the PSO algorithm to suit the particular problem domain. This work has promising roles towards applied modeling and can be extended to many other disciplines of model-based predictions.

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2014 Conference Paper R. Radhamani, Sasidharakurup, H., Kumar, D., Nizar, N., Nair, B., Achuthan, K., and Dr. Diwakar, S., “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 Conference Paper D. Kumar, Singanamala, H., Achuthan, K., Srivastava, S., Nair, B., and Dr. Diwakar, S., “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 Conference Paper A. Yoosef, Parasuram, H., Medini, C., Solinas, S., D'Angelo, E., Nair, B., and Dr. Diwakar, S., “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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2013 Conference Paper A. Vijayan, Singanamala, H., Bipin G. Nair Dr., Medini, C., Nutakki, C., and Dr. Diwakar, S., “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 Conference Paper J. Freeman, Nagarajan, A., Parangan, M., Kumar, D., Dr. Diwakar, S., and Achuthan, K., “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 Conference Paper K. Dr. Achuthan, Sreelatha, K. S., Surendran, S., Dr. Diwakar, S., Prema Nedungadi, Humphreys, S., Sreekala, C. O., Pillai, Z. S., Raman, R., Deepthi, A., Gangadharan, R., Appukuttan, S., Ranganatha, J., Sambhudevan, S., and Mahesh, S., “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 (Amrita 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. More »»
2011 Conference Paper Prema Nedungadi, Raman, R., Dr. Achuthan, K., and Dr. Diwakar, S., “Collaborative & Accessibility Platform for Distributed Virtual Labs”, in in press, IAJC-ASEE Joint International Conference on Engineering and Technology, Hartford, USA, 2011.
2011 Conference Paper Prema Nedungadi, Raman, R., Dr. Achuthan, K., and Dr. Diwakar, S., “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. More »»
2010 Conference Paper H. Parasuraman, Abdulmanaph, N., Nair, B., and Dr. Diwakar, S., “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 Conference Paper C. Medini, Subramaniyam, S., Nair, B., and Dr. Diwakar, S., “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 Conference Paper N. Abdulmanaph, James, P., Nair, B., and Dr. Diwakar, S., “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. More »»
2010 Conference Paper M. Parangan, Aravind, C., Parasuraman, H., Dr. Achuthan, K., Nair, B., and Dr. Diwakar, S., “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 Conference Paper Manitha B. Nair, Melethadathil, N., Nair, B., and Dr. Diwakar, S., “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. More »»
2010 Conference Paper S. Dr. Diwakar, Dr. Achuthan, K., and 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 Conference Paper N. Abdulmanaph, Parasuraman, H., Nair, Dr., B. G., Dr. Diwakar, S., 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. More »»
2010 Conference Paper S. Subramaniyam, Medini, C., Bipin G. Nair Dr., Dr. Diwakar, S., and , “Modeling spatio-temporal processing in cerebellar granular layer and effects of controlled inhibition”, 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.

More »»
2010 Conference Paper P. James, Abdulmanaph, N., Nair, B., and Dr. Diwakar, S., “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 »»
Publication Type: Conference Proceedings
Year of Publication Publication Type Title
2015 Conference Proceedings S. Dr. Diwakar, Chellaiah, P., Bipin G. Nair Dr., and Achuthan, K., “Theme Interception Sequence Learning: Deflecting Rubber-Hose Attacks Using Implicit Learning”, Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014, Advances in Intelligent Systems and Computing, vol. 1. Springer International Publishing, Switzerland, pp. 495-502, 2015.[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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Publication Type: Book Chapter
Year of Publication Publication Type Title
2014 Book Chapter R. Radhamani, Sasidharakurup, H., Sujatha, G., Nair, B., Achuthan, K., and Dr. Diwakar, S., “Virtual Labs Improve Student's Performance in a Classroom”, in E-Learning, E-Education, and Online Training, vol. 138, G. Vincenti, Bucciero, A., and de Carvalho, C. Vaz Springer International Publishing, 2014, 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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Pages

PROJECTs

 

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 University advanced neurological disorders' prediction using GPUs, March 17, 2016
  10. CIO report - How Amrita University 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 University 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 (link is external), HPC Asia, July 18, 2016.



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. Reviwer – BMC Neuroscience
  9. Reviewer - National Academy Science Letters
  10. Reviewer and TPC – eLEOT 2016, 3rd International Conference on e-Learning e-Education and Online Training, Dublin, Ireland.
  11. Reviewer and TPC - International Conference on Advances in Computing, Communications and Informatics (ICACCI-2016), Jaipur, 2016.
  12. Reviewer – WEEF 2015 Conference, World Engineering Education Forum 2015, 18th International Conference on Interactive Collaborative Learning, 20-24 September 2015, Florence. Italy.
  13. Reviewer and TPC – eLEOT 2015, 2nd International Conference on e-Learning e-Education and Online Training, Novedrate, Italy.
  14. Reviewer and TPC - International Conference on Computing in Mechanical Engineering (ICCME’15), Aug 10-13, India.
  15. Reviewer and TPC - International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, 2015.
  16. 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?
  17. Review committee - 2014 International Conference on Networks & Soft Computing
  18. International program committee member, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI-2014), 2014.
  19. International program committee member, 2012 International Conference on Advances in Computing, Communications and Informatics (ICACCI-2012), Chennai, India, Aug 3-5, 2012.
  20. International program committee member, International Conference on Technology Enhanced Education, Amritapuri, Kerala, India, Jan 3-5, 2012.
  21. Reviewer, Session chair and local organizer – International Conference on Biotechnology for Innovative Application (Amrita Bioquest 2013), Aug 10-13, 2013.
  22. International program committee member, International Conference on Computer Technology and Development 2011.
  23. Reviewer and Program committee member, International Conferences on Advances in Computing and Communications (ACC 2011), Kochi, India.
  24. Reviewer, international conference on computational intelligence ICCI 2010, (Coimbatore, India) Dec 9-11, 2010.
  25. Reviewer and session chair, IEEE BIC-TA (Liverpool, UK), 2010, Sept 8-10, 2010.           
  26. Program committee member and reviewer: 2nd Workshop on Emerging eLearning Web Technologies (EeLT 2009), April 27, 2009 at Poznan, Poland.
     

Talks

  1. 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.
  2. Talk - Using Cerebellar Architecture to Control Low-Cost Robotic Arms , International Symposium on the Neuromechanics of Human Movement, 4th – 6th October 2016, Heidelberg, Germany
  3. 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.
  4. 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. 
  5. 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. 
  6. Organizer Talk - Virtual Labs in India: Implementation and Case studies, National Nodal Center Conference, Amrita University, Amritapuri, Kollam, Kerala, India, May 6, 2016.  
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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
  12. 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.
  13. 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.
  14. 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. 
  15. 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. 
  16. Computational Modeling of Cerebellar Information Processing – Is my cerebellum a pattern recognition circuit?, Engineering hub, University of Lincoln, Lincoln, UK. June 30, 2014.
  17. 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.
  18. Invited Talk –Modeling Brain circuits and role of bioinspired computing, Malakara Catholic College, Kanyakumari Dt., TN. March 10, 2014.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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
  28. 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
  29. 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.
  30. Invited lecture. “Superman’s changing room – Virtualization and virtual labs”, International Conference on technology Enhanced Education, Amritapuri, Kerala, India, Jan 3-5, 2012.
  31. “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.
  32. “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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. LFP workshop: Modeling and interpretation of extracellular field potentials, January 15-16, 2009 at Oslo, Norway organized by INCF-Norway.

     

Links

Google ScholarDBLPINCF, MicrosoftLinkedInThe Neuron NetworkFrontiersOpenWetWare,BiomedExpertsAcademiaOrcidScopusMendeley, Researcher ID
 

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 University)
Amritapuri, Clappana P.O., Kollam, Kerala, India. Pin:690525
Tel +91 (0476-2896318 Extn:3116
Fax +91 (0)476-2899722

Faculty Details

Qualification:

Designation: 
Faculty Email: 
shyam@amrita.edu
Phone: 
+91 (0476-2896318)