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Fine-scale computations for adaptive processing in the human brain
Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetr...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688307/ https://www.ncbi.nlm.nih.gov/pubmed/33170124 http://dx.doi.org/10.7554/eLife.57637 |
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author | Zamboni, Elisa Kemper, Valentin G Goncalves, Nuno Reis Jia, Ke Karlaftis, Vasilis M Bell, Samuel J Giorgio, Joseph Rideaux, Reuben Goebel, Rainer Kourtzi, Zoe |
author_facet | Zamboni, Elisa Kemper, Valentin G Goncalves, Nuno Reis Jia, Ke Karlaftis, Vasilis M Bell, Samuel J Giorgio, Joseph Rideaux, Reuben Goebel, Rainer Kourtzi, Zoe |
author_sort | Zamboni, Elisa |
collection | PubMed |
description | Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing. |
format | Online Article Text |
id | pubmed-7688307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-76883072020-11-30 Fine-scale computations for adaptive processing in the human brain Zamboni, Elisa Kemper, Valentin G Goncalves, Nuno Reis Jia, Ke Karlaftis, Vasilis M Bell, Samuel J Giorgio, Joseph Rideaux, Reuben Goebel, Rainer Kourtzi, Zoe eLife Neuroscience Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing. eLife Sciences Publications, Ltd 2020-11-10 /pmc/articles/PMC7688307/ /pubmed/33170124 http://dx.doi.org/10.7554/eLife.57637 Text en © 2020, Zamboni et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Zamboni, Elisa Kemper, Valentin G Goncalves, Nuno Reis Jia, Ke Karlaftis, Vasilis M Bell, Samuel J Giorgio, Joseph Rideaux, Reuben Goebel, Rainer Kourtzi, Zoe Fine-scale computations for adaptive processing in the human brain |
title | Fine-scale computations for adaptive processing in the human brain |
title_full | Fine-scale computations for adaptive processing in the human brain |
title_fullStr | Fine-scale computations for adaptive processing in the human brain |
title_full_unstemmed | Fine-scale computations for adaptive processing in the human brain |
title_short | Fine-scale computations for adaptive processing in the human brain |
title_sort | fine-scale computations for adaptive processing in the human brain |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688307/ https://www.ncbi.nlm.nih.gov/pubmed/33170124 http://dx.doi.org/10.7554/eLife.57637 |
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