Modeling neural network activity from single cell models

Research involves the development and analysis of computational models in order to study synaptic plasticity, associative memory and information processing in the cerebellum. Other work at the lab is on bio-robotics and neuromorphic hardware besides pedagogical techniques for enhancing biotechnology laboratory education.


[MHRD] Sakshat Amrita Virtual Labs

In partnership with the Government of India’s Sakshat initiative of the Ministry of Human Resource Development, these Amrita Virtual Labs, focus on helping students retain the real feel of a laboratory, while conducting the experiment from an internet-enabled computer terminal, much in the same way he or she would, in a real lab.

Amrita University jointly participates with IIT Delhi, IIT Kanpur, IIT Bombay, IIT Madras, IIT Kharagpur, IIT Guwahati, IIT Roorkee, IIIT Hyderabad and Dayalbagh University. Read more.

[DST] Cognitive Science Initiative – 2010 and 2011

Department of Science and Technology of the Government of India has awarded a new grant under the cognitive Science initiative (CSI).

Cognitive Science is the study of the processes by which the humans and other animals come to know properties of their external environment and convert that knowledge into action as well as relay that knowledge to others by means of communication. As a result, Cognitive Science has a vital role to play in several socially important areas such as mental health, social engineering, education and computer technology. It is assumed that Cognitive Science is one of the four pillars of the 21st Century along with Nano, Bio, and Information Technology. Of the four, Cognitive Science is the least represented in the Indian scientific scenario. In view of this, DST took special initiative for research in Cognitive Science in the 11th Five Year Plan. Cognitive Science Research Initiative (CSI) of DST promises to revolutionize research in various fields such as, a) nature and origin of mental disorders of psychological, social and neurochemical origin; b) design of better learning tools and educational paradigms; and design of better software technologies and artificial intelligence devices. In addition to promoting basic research and infrastructure in this area, human resource development has also been identified as an integral part for success of this initiative.

The main goals of this Amrita study will include understanding neuronal role in signal propagation and information processing in a central neuronal network. The other major focus will be on the analysis of cerebellar microcircuits for designing electronic neural processors. The targeted outcome in terms of mathematical modeling will be the reconstruction of salient network properties starting from their constitutive elements and predictions on the role of single neurons in the network. This study will include the connection between molecular mechanisms like plasticity with cognitive functions. Brain shows a seemingly linear mechanism and this work will explore the seemingly linear nature of brain and implement the processing power in an electronic device that could be used for a variety of machine learning, robotics, haptics and related bio-inspired applications. The design of a plausible neural architecture will be of greater advantage in understanding and using massive parallelism and redundancy compared to other architectures. Also this new design will allow us to model large systems of spiking neurons in real time.

The main work will be led by Dr. Shyam Diwakar and will be a collaborative study with Department of Electronics and Communication Engineering at Amrita School of Engineering. The co-investigator of this project is Prof. Bipin Nair. Two grants (funded separately in 2011(2010 call) and 2012 (2011 call)) support two different aspects of the work towards understanding the cognitive nature of the cerebellar circuit.

 [DST-MAE] Indo-Italy POC 2012-2014

A joint project proposal for Exchange of Researchers within the frame of the Executive Programme of Scientific and Technological Cooperation between the Republic of India and the Italian Republic for the years 2012 – 2014 has been selected. The project will enhance the research collaboration between the lab at Amrita University and University of Milan, University of Pavia and Italian Institute of Technology (Genova).

[DBT] Computational Modeling of a Neuronal Network 2012-2015

A new project has been sanctioned by DBT to mathematically model a neuronal network to understand physiological functions and the effects of disorders.

[NVIDIA] NVIDIA CUDA Teaching Center 2012-2014

A extension of the teaching center grant has been awarded by NVIDIA for promoting the use of CUDA GPGPUs in teaching and research. 

[DST-JSPS] Indo-Japan POC 2013-2015

A joint project proposal for Exchange of Researchers has been awarded to Amrita team including us and University of Tokyo. PI of this project are Dr. Maneesha Ramesh of Amrita Center for Wireless Networks & Applications, Amrita Vishwa Vidyapeetham, India and Prof. Masahiro Fujita of University of Tokyo, Japan.

[MHRD] QEEE Amrita Physics Lab

As part of the Quality Enhancement in Engineering Education (QEEE) program coordinated by Prof. Ashok Jhunjhunwala, Amrita Virtual Labs team (Coordinated by Dr. Shyam Diwakar) will use the Physics Virtual Labs to offer a new lab course to 40 colleges in India via the QEEE portal. The lab topic selected is oh Physics and will target undergraduate Physics students.

[MHRD] Virtual Labs Phase II

Sakshat Virtual Labs project has initiated a second phase funded by MHRD. Amrita (integration with IIITH coordinated by Dr. Shyam Diwakar) will look into setting up the existing virtual labs and some new content onto a Open-source platform allowing Akash-like mobile device to access the simulation and animation oriented virtual labs. This project is funded by Ministry of Human Resource Development, Government of India and is in partnership with IIT Delhi, IIT Bombay, IIT Kanpur, IIT Kharagpur, IIT Guwahati, IIT Rourkee, IIT Madras, Dayabagh University, IIIT Hyderabad, NIT Karnataka, COE Pune.

[DST] Modelling the cerebellar information code in large-scale realistic circuits - Towards pharmacological predictions and robotic abstractions

We are working on neural and circuit modeling to understand neural circuit computations. Using elaborate realistic spiking neural networks of the rat cerebellum and use them, together with the theoretical basis of central network computation, this project aims to look at population code in some neural circuits.

[DST] Designing a BMI-based robotic arm using EEG and motor articulation control

In this project which started in Feb 2016, we are using EEG recordings to control robotic arm by extracting left and right side motor imagery movement patterns. We will develop and use feature extraction methods to extract the required features from the pre-processed signal data.

[NVIDIA] NVIDIA GPU Research Center and GPU Teaching Center 2015-2017

A extension of the teaching center grant has been awarded by NVIDIA for promoting the use of CUDA GPGPUs in teaching and research. 



Software code and online material from papers and research topics within the lab.


LFPsim - A toolkit for modeling LFPs from detailed multicompartmental neurons and circuits implemented in NEURON enviornment.

LFPsim on ModelDB/GitHub

Reference: Modeling single neuron LFPs and extracellular potentials with LFPsim. Reference: Parasuram H, Nair B, D‘Angelo E, Hines M, Naldi G and Diwakar S (2016). Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim. Front. Comput. Neurosci. 10:65. doi: 10.3389/fncom.2016.00065

ReConv Algorithm – Jittered Repetitive convolution algorithm for generating evoked LFP in cerebellar granular layer

ReConv Algorithm to generate evoked LFP in cerebellar granular layer.

Reference: Diwakar S, Lombardo P, Solinas S, Naldi G, D’Angelo E (2011) Local Field Potential Modeling Predicts Dense Activation in Cerebellar Granule Cells Clusters under LTP and LTD Control. PLoS ONE 6(7): e21928. doi:10.1371/journal.pone.0021928 [PLoS One]

Cerebellar Granule neuron model (Published from UNIPV) – Modeldb

detailed multicompartmental model was used to study neuronal electroresponsiveness of cerebellar granule cells in rats. For details check article.

Reference: Diwakar S, Magistretti J, Goldfarb M, Naldi G, D`Angelo E (2009) Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells J Neurophysiol 101(2):519-32 [PubMed]