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Early sensory representation in cortex optimizes information content in small neural assemblies.
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
(English)Manuscript (preprint) (Other academic)
National Category
Computer Science
URN: urn:nbn:se:kth:diva-27643OAI: diva2:379496
QC 20101217Available from: 2010-12-17 Created: 2010-12-17 Last updated: 2010-12-20Bibliographically approved
In thesis
1. Some computational aspects of attractor memory
Open this publication in new window or tab >>Some computational aspects of attractor memory
2005 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

In this thesis I present novel mechanisms for certain computational capabilities of the cerebral cortex, building on the established notion of attractor memory. A sparse binary coding network for generating efficient representation of sensory input is presented. It is demonstrated that this network model well reproduces receptive field shapes seen in primary visual cortex and that its representations are efficient with respect to storage in associative memory. I show how an autoassociative memory, augmented with dynamical synapses, can function as a general sequence learning network. I demonstrate how an abstract attractor memory system may be realized on the microcircuit level -- and how it may be analyzed using similar tools as used experimentally. I demonstrate some predictions from the hypothesis that the macroscopic connectivity of the cortex is optimized for attractor memory function. I also discuss methodological aspects of modelling in computational neuroscience.

Place, publisher, year, edition, pages
Stockholm: KTH, 2005. viii, 76 p.
Trita-NA, ISSN 0348-2952 ; 0509
Datalogi, attractor memory, cerebral cortex, neural networks, Datalogi
National Category
Computer Science
urn:nbn:se:kth:diva-249 (URN)91-7283-983-X (ISBN)
2005-03-15, Sal E32, KTH, Lindstedtsvägen 3, Stockholm, 07:00
QC 20101220Available from: 2005-05-31 Created: 2005-05-31 Last updated: 2010-12-20Bibliographically approved

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Rehn, MartinSommer, Friedrich T.
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