Neural Signaling of Probabilistic Vectors.
Recent work combining cognitive neuroscience with computational modeling suggests that distributed patterns of neural firing may represent probability distributions. This article asks, what makes it the case that distributed patterns of firing, as well as carrying information about (correlating with...
| Publicado en: | Philosophy of Science Vol. 81; no. 5; pp. 902 - 914 |
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| Formato: | Artículo |
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Cambridge University Press
Dec2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=99660769&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 99660769 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00318248 PSC jtl: Philosophy of Science issn: 00318248 maglogo: N pubinfo: dt: Dec2014 vid: 81 iid: 5 pid: 15979 pub: Cambridge University Press artinfo: ui: 99660769 10.1086/678354 ppf: 902 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P size: 310KB tig: atl: Neural Signaling of Probabilistic Vectors. aug: au: Shea, Nicholas su: Cognitive neuroscience Skyrms, Brian Action potentials Biopotentials (Electrophysiology) Neural transmission sug: subj: Cognitive neuroscience Skyrms, Brian Action potentials Biopotentials (Electrophysiology) Neural transmission ab: Recent work combining cognitive neuroscience with computational modeling suggests that distributed patterns of neural firing may represent probability distributions. This article asks, what makes it the case that distributed patterns of firing, as well as carrying information about (correlating with) probability distributions over worldly parameters, represent such distributions? In examples of probabilistic population coding, it is the way information is used in downstream processing so as to lead to successful behavior. In these cases content depends on factors beyond bare information, contra Brian Skyrms's view that representational content can be fully characterized in information-theoretic terms. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Philosophy of Science is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Philosophy of Science holder: Cambridge University Press dt: @attributes: year: 2014 holdings: @attributes: islocal: N |
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