Modeling spatio-temporal processing in cerebellar granular layer and effects of controlled inhibition

Sathyaa Subramaniyam (1) , Chaitanya Medini (1) , Bipin Nair (1) , Shyam Diwakar (1)

1 School of Biotechnology

The cerebellum input stage has been known to perform spatio-temporal transformations and combinatorial operations [1] [2] 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] [3]. 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 LTP 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.

Mots clés: Plasticity and functional specialization; Information coding; Biophysical models; Neuron models

Domaines: Neurosciences [q-bio.NC]; Neurosciences

Sathyaa Subramaniyam, Chaitanya Medini, Bipin Nair, Shyam Diwakar. Modeling spatio-temporal processing in cerebellar granular layer and effects of controlled inhibition. Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France. ⟨hal-00553408⟩