Probabilistic Encoding and Decoding of Neural Activity in Rat Primary Visual Cortex

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Titel: Probabilistic Encoding and Decoding of Neural Activity in Rat Primary Visual Cortex
Autor(en): Bringmann, Holger Carl
Zusammenfassung: Abstract: According to the information processing paradigm in the Cognitive Sciences, one of the nervous system´s most important functions is to encode information about the environment. Understanding the neural code means understanding the relationship between brain states and real events in the outer world. In this work, a probabilistic Framework for encoding (i.e., mapping events to neural response) and decoding (i.e., reconstruction of events from neural responses) of neural activity is presented and applied to theoretical and empirical data. Reconstruction is based on a Bayesian filter method, allowing the propagation of multi modal densities and the use of non-linear stimulus dynamics.
Bibliografische Angaben: University of Osnabrück, Germany (2002): 40
URL: https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-201001304735
Schlagworte: Neural Code; Neural Coding; Neural Decoding; Rat Primary Visual Cortex; Bayes; Bayesian Filter; Integrate-and-Fire-Neurons; random walk; stimulus reconstruction
Erscheinungsdatum: 3-Sep-2009
Enthalten in den Sammlungen:UOS Hochschulschriften

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