Computational Neuroscience of Neurons and Circuits, EEG, Mathematical Modeling and Applied Robotics

Our research involves the development and analysis of computational models in order to study synaptic plasticity, associative memory and information processing in the cerebellum and inter-related circuits. Other work at the lab is on bio-robotics and neuromorphic hardware, neuroscience of yoga and Indian relaxation techniqies besides development of tools and pedagogical techniques for enhancing bioscience laboratory education.


[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. (Status - Ongoing)

[DST] Cognitive Science Research Initiative projects

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

Using EEG recordings to control a low-cost robotic arm by extracting left and right side motor imagery movement patterns,  we are developing and use deep learning and machine learning methods for predicting motor imagery. This is funded by DST, Govt of India. (Status - Ongoing)

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

Modeling realistic spiking neural networks of the rat cerebellum to understand computations of sensory and motor processing in brain circuits and to model population activities. Another focus is to implement abstractions in robots. This project is funded by DST, Govt of India. (Status - Ongoing)

Neurophysiological Recording and Modeling Fast-response Timing of Granule and Golgi Cell Responses for Cerebellar Function

Understanding information processing in the cerebellar circuit in order to model artificial networks able to perform analogous tasks in robotic control systems was the goal of this project that was completed on 31st March 2015. (Status - Completed)

Bio-inspired Processor Design for Cognitive Functions via Detailed Computational Modeling of Cerebellar Granular Layer

This completed project aimed at understanding cognitive functioning of cerebellar input layer and implement signal processing abilities into neural hardware using cerebellar architecture. The main goals included understanding cerebellum granule neuron’s role in signal propagation and information processing in a central neuronal network. The other major focus was on the analysis of cerebellar microcircuits for designing electronic neural processors. The project was completed on 31 Dec 2014.  (Status - Completed)

[DST-MAE]Indo-Italy POC 2012-2014

This project proposed to develop a cerebellum inspired pattern recognition algorithm for robotic data classification. The proposal was to exploit biophysical neural network models to the problem of pattern recognition and navigation in mobile robots to achieve practical algorithms for specific applications like surgery or disaster mitigation. The project used biological basis for design and function of a deep learning pattern classifier for motor articulation tasks. This was 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 was selected. Visits were made by researchers from Italy and PhD students from the lab visited Italy as part of this proposal. The project was completed on 31 July 2015. (Status - Completed)

[DBT]Computational Modelling and Prediction of Cerebellar Input Layer function, Timing and Plasticity for Understanding Neurophysiological Disorders

Using a multi-dimensional modelling approach, multi-scale models of single cells and networks were developed with NEURON simulator. Network activity was reconstructed based on experimental in vitro data and then used to match in vivo behavior. The main part of the project was to elaborate statistics of granular layer spontaneous activity and stimuli processing by rat cerebellum. Funded by the Department of Biotechnology (DBT), Government of India, the project was completed on 31 March 2015. (Status - Completed)

[Amrita Vishwa Vidyapeetham] Neuroscience of Yoga and Meditation

Inspired by our Chancellor Amma’s guidance, several practitioners see personal benefits to regular practices including yoga and meditation for stress relief. We wanted to look into behavioural adaptation and “wellness” behind practitioners and non-practitioners. As an effort to understand causality and functional connectivity changes induced by holistic stress relieving techniques related to Amrita Yoga and Meditation methods, we have commenced experimental studies and models based on surface EEG signals on yoga and meditation practitioners and non-practitioners. Specifically, we look into neural mechanisms underlying mediation reporting changes in spectral band frequencies during meditation that focus on concentration assessing pre and post behavioural modifications related to short term changes. Initiated in late 2016, this project is supported by Amrita Vishwa Vidyapeetham and Embracing The World. (Status - Ongoing)

[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. Over 320 online labs have been developed and are available freely from here.

Amrita University jointly participates with IIT Delhi, IIT Kanpur, IIT Bombay, IIT Madras, IIT Kharagpur, IIT Guwahati, IIT Roorkee, IIIT Hyderabad and Dayalbagh University. (Status - Completed)

[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. (Status - Completed)

[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. (Status - Completed)

[IC-IMPACTS and DBT] An innovative green technology for treating municipal and industrial wastewater entering rivers and streams

A minor role as one of the co-PIs through a data mining role in this DBT Indo-Canada project. This research project seeks to bring together biomass based biochars and hydrochars from rice husk waste product to remove heavy metals and other contaminants from industrial and domestic wastewater that makes its way untreated or only partially treated into rivers and streams. (Status - Ongoing)

[DST-JSPS] Indo-Japan POC 2013-2015

A joint project proposal for Exchange of Researchers has been awarded to Amrita team including us (as co-PI) 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. (Status - Completed)

[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. (Status - Completed)


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

A 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]

NIRF 2017