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dc.contributor.authorSeung, H. Sebastian
dc.date.accessioned2015-03-25T17:12:16Z
dc.date.available2015-03-25T17:12:16Z
dc.date.issued2009-04
dc.identifier.issn08966273
dc.identifier.issn1097-4199
dc.identifier.urihttp://hdl.handle.net/1721.1/96185
dc.description.abstractMany theories of neural networks assume rules of connection between pairs of neurons that are based on their cell types or functional properties. It is finally becoming feasible to test such pairwise models of connectivity, due to emerging advances in neuroanatomical techniques. One method will be to measure the functional properties of connected pairs of neurons, sparsely sampling pairs from many specimens. Another method will be to find a “connectome,” a dense map of all connections in a single specimen, and infer functional properties of neurons through computational analysis. For the latter method, the most exciting prospect would be to decode the memories that are hypothesized to be stored in connectomes.en_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.neuron.2009.03.020en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceElsevieren_US
dc.titleReading the Book of Memory: Sparse Sampling versus Dense Mapping of Connectomesen_US
dc.typeArticleen_US
dc.identifier.citationSeung, H. Sebastian. “Reading the Book of Memory: Sparse Sampling Versus Dense Mapping of Connectomes.” Neuron 62, no. 1 (April 2009): 17–29. © 2009 Elsevier Inc.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.mitauthorSeung, H. Sebastianen_US
dc.relation.journalNeuronen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSeung, H. Sebastianen_US
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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