Cerebellum as a kernel machine: A novel perspective on expansion recoding in granule cell layer
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bae, Hyojin | - |
dc.contributor.author | Park, Sa-Yoon | - |
dc.contributor.author | Kim, Sang Jeong | - |
dc.contributor.author | Kim, Chang-Eop | - |
dc.date.accessioned | 2023-01-21T04:40:10Z | - |
dc.date.available | 2023-01-21T04:40:10Z | - |
dc.date.created | 2023-01-21 | - |
dc.date.issued | 2022-12 | - |
dc.identifier.issn | 1662-5188 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/86747 | - |
dc.description.abstract | Sensorimotor information provided by mossy fibers (MF) is mapped to high-dimensional space by a huge number of granule cells (GrC) in the cerebellar cortex's input layer. Significant studies have demonstrated the computational advantages and primary contributor of this expansion recoding. Here, we propose a novel perspective on the expansion recoding where each GrC serve as a kernel basis function, thereby the cerebellum can operate like a kernel machine that implicitly use high dimensional (even infinite) feature spaces. We highlight that the generation of kernel basis function is indeed biologically plausible scenario, considering that the key idea of kernel machine is to memorize important input patterns. We present potential regimes for developing kernels under constrained resources and discuss the advantages and disadvantages of each regime using various simulation settings. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | FRONTIERS MEDIA SA | - |
dc.relation.isPartOf | FRONTIERS IN COMPUTATIONAL NEUROSCIENCE | - |
dc.title | Cerebellum as a kernel machine: A novel perspective on expansion recoding in granule cell layer | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000907819100001 | - |
dc.identifier.doi | 10.3389/fncom.2022.1062392 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, v.16 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85145875709 | - |
dc.citation.title | FRONTIERS IN COMPUTATIONAL NEUROSCIENCE | - |
dc.citation.volume | 16 | - |
dc.contributor.affiliatedAuthor | Bae, Hyojin | - |
dc.contributor.affiliatedAuthor | Park, Sa-Yoon | - |
dc.contributor.affiliatedAuthor | Kim, Chang-Eop | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | cerebellum | - |
dc.subject.keywordAuthor | expansion recoding | - |
dc.subject.keywordAuthor | kernel machine | - |
dc.subject.keywordAuthor | radial basis (RBF) neural network | - |
dc.subject.keywordAuthor | granule cell layer | - |
dc.subject.keywordPlus | ADAPTIVE-FILTER MODEL | - |
dc.subject.keywordPlus | MIXED SELECTIVITY | - |
dc.subject.keywordPlus | ARM MOVEMENTS | - |
dc.subject.keywordPlus | REPRESENTATIONS | - |
dc.subject.keywordPlus | MECHANISMS | - |
dc.subject.keywordPlus | SPARSENESS | - |
dc.subject.keywordPlus | CIRCUIT | - |
dc.subject.keywordPlus | NETWORK | - |
dc.subject.keywordPlus | DENSE | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Neurosciences & Neurology | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Neurosciences | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.