guest ::
| Home > Publications database > Cortical oscillations support sampling-based computations in spiking neural networks > print |
| Home > Publications database > Cortical oscillations support sampling-based computations in spiking neural networks > print |
| 001 | 906981 | ||
| 005 | 20240313103131.0 | ||
| 024 | 7 | _ | |a 10.1371/journal.pcbi.1009753 |2 doi |
| 024 | 7 | _ | |a 1553-734X |2 ISSN |
| 024 | 7 | _ | |a 1553-7358 |2 ISSN |
| 024 | 7 | _ | |a 2128/31012 |2 Handle |
| 024 | 7 | _ | |a altmetric:125369810 |2 altmetric |
| 024 | 7 | _ | |a pmid:35324886 |2 pmid |
| 024 | 7 | _ | |a WOS:000781624200007 |2 WOS |
| 037 | _ | _ | |a FZJ-2022-01794 |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Korcsak-Gorzo, Agnes |0 P:(DE-Juel1)176282 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Cortical oscillations support sampling-based computations in spiking neural networks |
| 260 | _ | _ | |a San Francisco, Calif. |c 2022 |b Public Library of Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1649423412_9480 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires visiting multiple interpretations of the available information or multiple solutions to an encountered problem. This gives rise to the so-called mixing problem: since all of these “valid” states represent powerful attractors, but between themselves can be very dissimilar, switching between such states can be difficult. We propose that cortical oscillations can be effectively used to overcome this challenge. By acting as an effective temperature, background spiking activity modulates exploration. Rhythmic changes induced by cortical oscillations can then be interpreted as a form of simulated tempering. We provide a rigorous mathematical discussion of this link and study some of its phenomenological implications in computer simulations. This identifies a new computational role of cortical oscillations and connects them to various phenomena in the brain, such as sampling-based probabilistic inference, memory replay, multisensory cue combination, and place cell flickering. |
| 536 | _ | _ | |a 5232 - Computational Principles (POF4-523) |0 G:(DE-HGF)POF4-5232 |c POF4-523 |f POF IV |x 0 |
| 536 | _ | _ | |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) |0 G:(EU-Grant)945539 |c 945539 |f H2020-SGA-FETFLAG-HBP-2019 |x 1 |
| 536 | _ | _ | |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) |0 G:(EU-Grant)785907 |c 785907 |f H2020-SGA-FETFLAG-HBP-2017 |x 2 |
| 536 | _ | _ | |a HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270) |0 G:(EU-Grant)720270 |c 720270 |f H2020-Adhoc-2014-20 |x 3 |
| 536 | _ | _ | |a ACA - Advanced Computing Architectures (SO-092) |0 G:(DE-HGF)SO-092 |c SO-092 |x 4 |
| 536 | _ | _ | |a Open-Access-Publikationskosten Forschungszentrum Jülich (OAPKFZJ) (491111487) |0 G:(GEPRIS)491111487 |c 491111487 |x 5 |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de |
| 700 | 1 | _ | |a Müller, Michael G. |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Baumbach, Andreas |0 0000-0002-9374-2729 |b 2 |
| 700 | 1 | _ | |a Leng, Luziwei |0 0000-0002-9344-8589 |b 3 |
| 700 | 1 | _ | |a Breitwieser, Oliver J. |0 0000-0002-1477-9110 |b 4 |
| 700 | 1 | _ | |a van Albada, Sacha J. |0 P:(DE-Juel1)138512 |b 5 |
| 700 | 1 | _ | |a Senn, Walter |0 0000-0003-3622-0497 |b 6 |
| 700 | 1 | _ | |a Meier, Karlheinz |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Legenstein, Robert |0 0000-0002-8724-5507 |b 8 |
| 700 | 1 | _ | |a Petrovici, Mihai A. |0 0000-0003-2632-0427 |b 9 |
| 773 | _ | _ | |a 10.1371/journal.pcbi.1009753 |g Vol. 18, no. 3, p. e1009753 - |0 PERI:(DE-600)2193340-6 |p 3, 1-41 |t PLoS Computational Biology |v 18 |y 2022 |x 1553-734X |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/906981/files/journal.pcbi.1009753.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:906981 |p openaire |p open_access |p driver |p VDB |p ec_fundedresources |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)176282 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)138512 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5232 |x 0 |
| 914 | 1 | _ | |y 2022 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-01-27 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2021-01-27 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-01-27 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2021-01-27 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2021-01-27 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b PLOS COMPUT BIOL : 2021 |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2022-04-12T10:24:26Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2022-04-12T10:24:26Z |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Peer review |d 2022-04-12T10:24:26Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2022-11-18 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2022-11-18 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2022-11-18 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-6-20090406 |k INM-6 |l Computational and Systems Neuroscience |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-6-20130828 |k IAS-6 |l Theoretical Neuroscience |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-10-20170113 |k INM-10 |l Jara-Institut Brain structure-function relationships |x 2 |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-6-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-10-20170113 |
| 981 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|