Disentangling signal and noise in neural responses through generative modeling.
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| Title: | Disentangling signal and noise in neural responses through generative modeling. |
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| Authors: | Kay K; Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America., Prince JS; Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America., Gebhart T; Department of Computer Science, University of Minnesota, Minneapolis, Minnesota, United States of America., Tuckute G; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America., Zhou J; Center for Computational Neuroscience (CCN), Flatiron Institute, New York, New York, United States of America., Naselaris T; Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.; Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America., Schütt HH; Department of Behavioural and Cognitive Sciences, Université du Luxembourg, Esch-Belval Esch-sur-Alzette, Luxembourg. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2025 Jul 21; Vol. 21 (7), pp. e1012092. Date of Electronic Publication: 2025 Jul 21 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40690484 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Disentangling signal and noise in neural responses through generative modeling. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Kay+K%22">Kay K</searchLink>; Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.<br /><searchLink fieldCode="AU" term="%22Prince+JS%22">Prince JS</searchLink>; Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.<br /><searchLink fieldCode="AU" term="%22Gebhart+T%22">Gebhart T</searchLink>; Department of Computer Science, University of Minnesota, Minneapolis, Minnesota, United States of America.<br /><searchLink fieldCode="AU" term="%22Tuckute+G%22">Tuckute G</searchLink>; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.<br /><searchLink fieldCode="AU" term="%22Zhou+J%22">Zhou J</searchLink>; Center for Computational Neuroscience (CCN), Flatiron Institute, New York, New York, United States of America.<br /><searchLink fieldCode="AU" term="%22Naselaris+T%22">Naselaris T</searchLink>; Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.; Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America.<br /><searchLink fieldCode="AU" term="%22Schütt+HH%22">Schütt HH</searchLink>; Department of Behavioural and Cognitive Sciences, Université du Luxembourg, Esch-Belval Esch-sur-Alzette, Luxembourg. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101238922%22">PLoS computational biology</searchLink> [PLoS Comput Biol] 2025 Jul 21; Vol. 21 (7), pp. e1012092. <i>Date of Electronic Publication: </i>2025 Jul 21 (<i>Print Publication: </i>2025). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Public+Library+of+Science%22">Public Library of Science </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101238922 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>1553-7358 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%221553734X%22">1553734X </searchLink><i>NLM ISO Abbreviation: </i>PLoS Comput Biol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40690484 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1371/journal.pcbi.1012092 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e1012092 Titles: – TitleFull: Disentangling signal and noise in neural responses through generative modeling. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kay K – PersonEntity: Name: NameFull: Prince JS – PersonEntity: Name: NameFull: Gebhart T – PersonEntity: Name: NameFull: Tuckute G – PersonEntity: Name: NameFull: Zhou J – PersonEntity: Name: NameFull: Naselaris T – PersonEntity: Name: NameFull: Schütt HH IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 07 Text: 2025 Jul 21 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1553-7358 Numbering: – Type: volume Value: 21 – Type: issue Value: 7 Titles: – TitleFull: PLoS computational biology Type: main |
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