title: Modelling cortico basal-ganglionic loops and the development of sequential information encoding creator: Fukuda, Ryuta creator: Spratling, Micheal creator: Mareschal, Denis creator: Johnson, Mark subject: Computational Neuroscience subject: Machine Learning subject: Neural Nets description: 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. publisher: Lund University Cognitive Studies contributor: Prince, Christopher G. contributor: Berthouze, Luc contributor: Kozima, Hideki contributor: Bullock, Daniel contributor: Stojanov, Georgi contributor: Balkenius, Christian date: 2003 type: Conference Poster type: PeerReviewed format: application/pdf identifier: http://cogprints.org/3348/1/Fukuda.pdf identifier: Fukuda, Ryuta and Spratling, Micheal and Mareschal, Denis and Johnson, Mark (2003) Modelling cortico basal-ganglionic loops and the development of sequential information encoding. [Conference Poster] relation: http://cogprints.org/3348/