Cargando…
Identifying task-relevant spectral signatures of perceptual categorization in the human cortex
Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217881/ https://www.ncbi.nlm.nih.gov/pubmed/32398733 http://dx.doi.org/10.1038/s41598-020-64243-6 |
_version_ | 1783532679725056000 |
---|---|
author | Kuzovkin, Ilya Vidal, Juan R. Perrone-Bertolotti, Marcela Kahane, Philippe Rheims, Sylvain Aru, Jaan Lachaux, Jean-Philippe Vicente, Raul |
author_facet | Kuzovkin, Ilya Vidal, Juan R. Perrone-Bertolotti, Marcela Kahane, Philippe Rheims, Sylvain Aru, Jaan Lachaux, Jean-Philippe Vicente, Raul |
author_sort | Kuzovkin, Ilya |
collection | PubMed |
description | Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks’ selectivity for categorical information processing is still unknown. In this work we train Random Forest classification models to decode eight perceptual categories from broad spectrum of human intracranial signals (4–150 Hz, 100 subjects) obtained during a visual perception task. We then analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding and gain the insights into which parts of the recorded activity are actually characteristic of the visual categorization process in the human brain. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4–50 Hz) and high (50–150 Hz) frequency bands. By focusing on task-relevant neural activity and separating it into dissociated anatomical and spectrotemporal groups we uncover spectral signatures that characterize neural mechanisms of visual category perception in human brain that have not yet been reported in the literature. |
format | Online Article Text |
id | pubmed-7217881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72178812020-05-19 Identifying task-relevant spectral signatures of perceptual categorization in the human cortex Kuzovkin, Ilya Vidal, Juan R. Perrone-Bertolotti, Marcela Kahane, Philippe Rheims, Sylvain Aru, Jaan Lachaux, Jean-Philippe Vicente, Raul Sci Rep Article Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks’ selectivity for categorical information processing is still unknown. In this work we train Random Forest classification models to decode eight perceptual categories from broad spectrum of human intracranial signals (4–150 Hz, 100 subjects) obtained during a visual perception task. We then analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding and gain the insights into which parts of the recorded activity are actually characteristic of the visual categorization process in the human brain. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4–50 Hz) and high (50–150 Hz) frequency bands. By focusing on task-relevant neural activity and separating it into dissociated anatomical and spectrotemporal groups we uncover spectral signatures that characterize neural mechanisms of visual category perception in human brain that have not yet been reported in the literature. Nature Publishing Group UK 2020-05-12 /pmc/articles/PMC7217881/ /pubmed/32398733 http://dx.doi.org/10.1038/s41598-020-64243-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kuzovkin, Ilya Vidal, Juan R. Perrone-Bertolotti, Marcela Kahane, Philippe Rheims, Sylvain Aru, Jaan Lachaux, Jean-Philippe Vicente, Raul Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title | Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title_full | Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title_fullStr | Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title_full_unstemmed | Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title_short | Identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
title_sort | identifying task-relevant spectral signatures of perceptual categorization in the human cortex |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217881/ https://www.ncbi.nlm.nih.gov/pubmed/32398733 http://dx.doi.org/10.1038/s41598-020-64243-6 |
work_keys_str_mv | AT kuzovkinilya identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT vidaljuanr identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT perronebertolottimarcela identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT kahanephilippe identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT rheimssylvain identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT arujaan identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT lachauxjeanphilippe identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex AT vicenteraul identifyingtaskrelevantspectralsignaturesofperceptualcategorizationinthehumancortex |