title: Spatiotemporal coding in the cortex: information flow-based learning in spiking neural networks.
abstract: We introduce a learning paradigm for networks of integrate-and-fire spiking neurons that is based on an information-theoretic criterion. This criterion can be viewed as a first principle that demonstrates the experimentally observed fact that cortical neurons display synchronous firing for some stimuli and not for others. The principle can be regarded as the postulation of a nonparametric reconstruction method as optimization criteria for learning the required functional connectivity that justifies and explains synchronous firing for binding of features as a mechanism for spatiotemporal coding. This can be expressed in an information-theoretic way by maximizing the discrimination ability between different sensory inputs in minimal time.
authors.affiliation: Corporate Technology, Siemens AG / ZT IK 4, Otto-Hahn-Ring 6, 81739 Munich, Germany. Gustavo.Deco@mchp.siemens.de
authors.forename: G
authors.initials: G
authors.lastname: Deco
authors.forename: B
authors.initials: B
authors.lastname: Schürmann
mesh_terms: D000200:Action Potentials / Q000502:physiology; D003344:Cortical Synchronization; D004192:Discrimination, Psychological; D007257:Information Theory; D007858:Learning; D016571:Neural Networks, Computer; D010775:Photic Stimulation