Bio-inspired Processor Design for Cognitive Functions via Detailed Computational Modeling of Cerebellar Granular Layer
This project aims at understanding cognitive functioning of cerebellar input layer and implement signal processing abilities into neural hardware using cerebellar architecture. The main goals include understanding cerebellum granule neuron’s 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. When signals in the form of spike discharges enter in a neuronal network, they are processed depending on the local organization of neuronal connections and on neuronal and synaptic dynamics. The knowledge extracted through detailed biophysical modeling of cerebellar networks will help to understand cognitive/behavior properties in neuronal ensembles. This information will be then used to develop prototype hardware models in FPGA to understand neuronal processing for robotics and other applications.
Peer-reviewed Conference papers
Shyam Diwakar and Bharat Jayaraman, “Constrained Objects for Neuronal Modeling and Simulation,” Proceedings of the International symposium on Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, Oct 30-Nov 1, 2011
“Computational Neuroscience of Granule Neurons,” LAP Lambert Academic Publishing GmbH & Co. KG, Germany, 2011, ISBN: 978-3-8443-2488-4