Publication Type : Conference Paper
Thematic Areas : Biotech, Learning-Technologies, Medical Sciences
Publisher : 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)
Source : Proceedings 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010, Changsha, p.1495-1503 (2010)
Url : https://ieeexplore.ieee.org/abstract/document/5645274/
ISBN : 9781424464388
Keywords : Biophysical model, Computation theory, Granular layer, In-vitro, Information transmission, Inhibition, Input signal, Large networks, Modelling, network, Network layers, Neuron model, Plasticity, Recoding, Spatiotemporal information, Spike amplitudes, Synaptic plasticity, Time windows
Campus : Amritapuri
School : School of Biotechnology
Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology
Department : biotechnology, Computational Neuroscience Laboratory
Year : 2010
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.
Cite this Research Publication : Medini, S. Subramaniyam, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “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 (Liverpool, UK), Changsha, 2010, pp. 1495-1503
