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Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/26719
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dc.contributor.authorHoward, Newtonen_UK
dc.contributor.authorHussain, Amiren_UK
dc.date.accessioned2018-02-16T00:47:55Z-
dc.date.available2018-02-16T00:47:55Z-
dc.date.issued2018-06-01en_UK
dc.identifier.urihttp://hdl.handle.net/1893/26719-
dc.description.abstractThis paper discusses the problems arising from the multidisciplinary nature of cognitive research and the need to conceptually unify insights from multiple fields into the phenomena that drive cognition. Specifically, the Fundamental Code Unit (FCU) is proposed as a means to better quantify the intelligent thought process at multiple levels of analysis. From the linguistic and behavioral output, FCU produces to the chemical and physical processes within the brain that drive it. The proposed method efficiently model the most complex decision-making process performed by the brain.en_UK
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.relationHoward N & Hussain A (2018) The Fundamental Code Unit of the Brain: Towards a New Model for Cognitive Geometry. Cognitive Computation, 10 (3), pp. 426-436. https://doi.org/10.1007/s12559-017-9538-5en_UK
dc.rights© The Author(s) 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectFundamental Code Unit (FCU)en_UK
dc.subjectCognitive Geometryen_UK
dc.subjectLong-term memory (LM)en_UK
dc.subjectLong term Potentiation/depression (LTP/LTD)en_UK
dc.titleThe Fundamental Code Unit of the Brain: Towards a New Model for Cognitive Geometryen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1007/s12559-017-9538-5en_UK
dc.citation.jtitleCognitive Computationen_UK
dc.citation.issn1866-9964en_UK
dc.citation.issn1866-9956en_UK
dc.citation.volume10en_UK
dc.citation.issue3en_UK
dc.citation.spage426en_UK
dc.citation.epage436en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEngineering and Physical Sciences Research Councilen_UK
dc.citation.date20/01/2018en_UK
dc.contributor.affiliationUniversity of Oxforden_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.scopusid2-s2.0-85040706830en_UK
dc.identifier.wtid498325en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dc.date.accepted2017-09-06en_UK
dcterms.dateAccepted2017-09-06en_UK
dc.date.filedepositdate2018-02-15en_UK
dc.relation.funderprojectDual Process Control Models in the Brain and Machines with Application to Autonomous Vehicle Controlen_UK
dc.relation.funderrefEP/I009310/1en_UK
rioxxterms.apcnot chargeden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorHoward, Newton|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.projectEP/I009310/1|Engineering and Physical Sciences Research Council|http://dx.doi.org/10.13039/501100000266en_UK
local.rioxx.freetoreaddate2018-02-15en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2018-02-15|en_UK
local.rioxx.filenameHowardHussain-CogComp-2018.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1866-9956en_UK
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