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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.

Completed PhD.


Other Projects

[MHRD] Virtual Labs Phase II

Sakshat Virtual Labs project(link is external) 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)

[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] 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

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 Neurophysio 101(2):519-32 [PubMed]

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