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Modelling cortico basal-ganglionic loops and the development of sequential information encoding

By Ryuta Fukuda, Micheal Spratling, Denis Mareschal and Mark Johnson


A connectionist model consisting of thirty cortico-basal ganglionic loops was implemented. This model encodes temporal information into a spatial pattern of neuronal activations in the prefrontal cortex using neurophysiologically plausible activation functions and circuitry without learning. This neural architecture was used to model experiments with infants. Initial results suggest that the cortical basal ganglionic circuitry has an inherent ability to differentiate sequential information

Topics: Computational Neuroscience, Machine Learning, Neural Nets
Publisher: Lund University Cognitive Studies
Year: 2003
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