Mathematical Modeling and Information Theoretic Analysis of Cerebellum Input Layer Computations

Abstract

Exploring the neural phenomenon of stimulus perception and underlying mechanisms newlineof brain s processes is a crucial research question. Involvement of cerebellum internal newlinemodels for perceptual prediction has been received greater attention in the recent newlineyears. The input layer of the cerebellum, i.e., granule layer has emerged to have more newlinerelevant functions, than previously thought. According to classical hypotheses (Albus, newline1971; Eccles et al., 1967; Marr, 1969), the expansion recording of mossy fiber newlineinputs in the granular layer allows Purkinje cells to maximally discriminate the newlineparallel fiber inputs which enhances the learning process in Purkinje cell. Recent newlineexperimental evidences related to plasticity at the mossy fiber -granule cell synapse newlinesuggested the involvement of cerebellum granular layer in learning process (Roggeri newlineet al., 2008). Goal- directed behavioural studies suggested that granule cells also newlineencode non-sensory motor inputs(Wagner et al., 2017). Existence of most numerous newlinegranule cells in the cerebellum and its implications in the formation of unconscious newlineprocedural memory of the cerebellum is still an unresolved question. Even though in newlinevitro and a few in vivo granule neuron data are available through electrophysiological newlineexperiments, population activity is yet to be resolved at a finer scale due to the lack of newlineexperimental techniques to differentiate large population of granule neurons. newlineComputational modeling has been used as a powerful alternative to experimental newlinestudies. Granule cell has received greater attention in computational modeling studies newlinedue to its electronically compact structure, low dendritic arbor and the embarrassingly newlineparallel and independent computations that it performs on the inputs that it receives newlinefrom different brain regions. newlineThis study used realistic modeling approaches to understand granule neuron encoding newlineof mossy fiber inputs. Classical information theory (Shannon, 1948) was used here to newlinecharacterize the information capacity (entropy) of granule neurons...