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Complementary molecular models of learning and memory

dc.contributor.authorConrad, Michaelen_US
dc.date.accessioned2006-04-07T16:24:19Z
dc.date.available2006-04-07T16:24:19Z
dc.date.issued1976-12en_US
dc.identifier.citationConrad, Michael (1976/12)."Complementary molecular models of learning and memory." Biosystems 8(3): 119-138. <http://hdl.handle.net/2027.42/21626>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6T2K-49N8PT9-3T/2/634202544c6e8656bde142da434929d5en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/21626
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=1016695&dopt=citationen_US
dc.description.abstractThe functional capabilities of the brain are formally characterizable in terms of a finite system along with a memory space which it can manipulate. Two types of learning are possible: (1) modification-based learning, associated with alternate realizations of the finite system; (2) memory-based learning, associated with the assimilation, manipulation, and retrieval of memories. Constructive models which fulfill these conditions and which at the same time operate on the basis of molecular information processing principles have certain general features. We describe these features in terms of two interfaced submodels, the first for the finite system and the second for the memory space. The finite system may be realized by networks of neurons in which the specificity of enzyme molecules controls the nerve impulse. Such a realization is amenable to modification-based learning mediated by processes analogous to those of natural evolution and selective theories of antibody synthesis. The memory space is realizable by networks of neurons in which the conformation of dendritic receptor molecules controls the nerve impulse. In this case certain neurons firing in response to an external input undergo sensitization at the dendrites and in such a way that they are loadable and later callable by reference neurons, thereby allowing for reconstruction or manipulation of the firing pattern associated with this input. The overall construction makes a large number of biochemical, anatomical, physiological, and psychological predictions which are either testable or in good agreement with fact.en_US
dc.format.extent2993244 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleComplementary molecular models of learning and memoryen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelNatural Resources and Environmenten_US
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biologyen_US
dc.subject.hlbsecondlevelEcology and Evolutionary Biologyen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Computer and Communication Sciences, University of Michigan, Ann Arbor, MI 48104, U.S.A.en_US
dc.identifier.pmid1016695en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/21626/1/0000005.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0303-2647(76)90015-0en_US
dc.identifier.sourceBiosystemsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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