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Publication Type : Conference Paper
Thematic Areas : Learning-Technologies, Medical Sciences, Biotech
Publisher : Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting .
Source : Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011 (2011)
Campus : Amritapuri
School : School of Biotechnology, School of Engineering
Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology
Department : Electronics and Communication, biotechnology
Year : 2011
Abstract : In the current work, an estimate of information flow in terms of spikes in the cerebellum granular layer is discussed. Information transmission at the Mossy Fiber (MF) - Granule cell (GrC) synaptic relay is crucial to understand mechanisms of signal coding in the cerebellum [Albus,1971] [Marr, 1969]. To quantify the information transfer of a whole neuron, we used a computational model of a cerebellar granule cell [Diwakar, 2009], where the excitatory input space could be explored extensively. MFs convey afferent signals to GrCs following sensory stimulation. Plasticity was simulated in the granule cell model by changing the intrinsic excitability and release probability of the cells. Information coding in neurons or brain cells occur as excitatory post-synaptic potentials (EPSPs) and as spikes. The role of both EPSPs and spikes as information content relating the neuron’s response to given input stimuli was explored. LTP favored generation of spikes whereas LTD favored EPSPs as expected, although the percentage of spikes was higher at low release probabilities than the percentage of EPSPs at higher release probabilities. The role of selective inhibition by Golgi cells for coincidence detection is presented.
Cite this Research Publication : Dr. Shyam Diwakar, “ Information processing in the cerebellum granular layer and changes in plasticity revealing single neuron effects in neural ensemble”, in Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, 2011.