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김성필

Kim, Sung-Phil
Brain-Computer Interface Lab.
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dc.citation.startPage 890447 -
dc.citation.title FRONTIERS IN COMPUTATIONAL NEUROSCIENCE -
dc.citation.volume 16 -
dc.contributor.author Sihn, Duho -
dc.contributor.author Kim, Sung-Phil -
dc.date.accessioned 2023-12-21T14:10:59Z -
dc.date.available 2023-12-21T14:10:59Z -
dc.date.created 2022-06-28 -
dc.date.issued 2022-05 -
dc.description.abstract Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given that visual hierarchical structures contain both bottom-up and top-down pathways, the derived principles should encompass these bidirectional pathways. However, existing principles such as predictive coding do not provide an effective principle for bidirectional pathways. Therefore, we propose a novel computational principle for visual hierarchical structures as spatio-temporally efficient coding underscored by the efficient use of given resources in both neural activity space and processing time. This coding principle optimises bidirectional information transmissions over hierarchical structures by simultaneously minimising temporal differences in neural responses and maximising entropy in neural representations. Simulations demonstrated that the proposed spatio-temporally efficient coding was able to assign the function of appropriate neural representations of natural visual scenes to visual hierarchical structures. Furthermore, spatio-temporally efficient coding was able to predict well-known phenomena, including deviations in neural responses to unlearned inputs and bias in preferred orientations. Our proposed spatio-temporally efficient coding may facilitate deeper mechanistic understanding of the computational processes of hierarchical brain structures. -
dc.identifier.bibliographicCitation FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, v.16, pp.890447 -
dc.identifier.doi 10.3389/fncom.2022.890447 -
dc.identifier.issn 1662-5188 -
dc.identifier.scopusid 2-s2.0-85132305216 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/59008 -
dc.identifier.wosid 000808630000001 -
dc.language 영어 -
dc.publisher FRONTIERS MEDIA SA -
dc.title Spatio-Temporally Efficient Coding Assigns Functions to Hierarchical Structures of the Visual System -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Mathematical & Computational Biology; Neurosciences -
dc.relation.journalResearchArea Mathematical & Computational Biology; Neurosciences & Neurology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor efficient coding -
dc.subject.keywordAuthor hierarchical structure -
dc.subject.keywordAuthor neural response -
dc.subject.keywordAuthor neural representation -
dc.subject.keywordAuthor receptive field -
dc.subject.keywordAuthor selectivity -
dc.subject.keywordAuthor visual system -
dc.subject.keywordPlus SLOW FEATURE ANALYSIS -
dc.subject.keywordPlus RECEPTIVE-FIELDS -
dc.subject.keywordPlus SIMPLE CELLS -
dc.subject.keywordPlus FEEDBACK -
dc.subject.keywordPlus CORTEX -
dc.subject.keywordPlus RESPONSES -
dc.subject.keywordPlus REPRESENTATION -
dc.subject.keywordPlus ARCHITECTURE -
dc.subject.keywordPlus NEURONS -
dc.subject.keywordPlus MODELS -

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