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A model of cortical associative memory based on a horizontal network of connected columns
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0003-0281-9450
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-2358-7815
1998 (English)In: Network, ISSN 0954-898X, E-ISSN 1361-6536, Vol. 9, no 2, 235-264 p.Article in journal (Refereed) Published
Abstract [en]

An attractor network model of cortical associative memory functions has been constructed and simulated. By replacing the single cell as the functional unit by multiple cells in cortical columns connected by long-range fibers, the model is improved in terms of correspondence with cortical connectivity. The connectivity is improved, since the original dense and symmetric connectivity of a standard recurrent network becomes sparse and asymmetric at the cell-to-cell level. Our simulations show that this kind of network, with model neurons of the Hodgkin-Huxley type arranged in columns, can operate as an associative memory in much the same way as previous models having simpler connectivity. The network shows attractor-like behaviour and performs the standard assembly operations despite differences in the dynamics introduced by the more detailed cell model and network structure. Furthermore, the model has become sufficiently detailed to allow evaluation against electrophysiological and anatomical observations. For instance, cell activities comply with experimental findings and reaction times are within biological and psychological ranges. By introducing a scaling model we demonstrate that a network approaching experimentally reported neuron numbers and synaptic distributions also could work like the model studied here.

Place, publisher, year, edition, pages
BRISTOL: IOP PUBLISHING , 1998. Vol. 9, no 2, 235-264 p.
Keyword [en]
CAT VISUAL-CORTEX, CROSS-CORRELATION ANALYSIS, PRIMATE TEMPORAL CORTEX, COMPUTER-BASED MODEL, NEURAL NETWORKS, STRIATE CORTEX, CEREBRAL-CORTEX, POSTSYNAPTIC POTENTIALS, INTRACELLULAR ANALYSIS, REALISTIC SIMULATIONS
National Category
Neurosciences Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-51127DOI: 10.1088/0954-898X/9/2/006ISI: 000073823200006PubMedID: 9861988OAI: oai:DiVA.org:kth-51127DiVA: diva2:463444
Note
QC 20111213Available from: 2011-12-09 Created: 2011-12-09 Last updated: 2017-12-08Bibliographically approved

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