Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing

Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region dec...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Trung Quang Pham, Shota Nishiyama, Norihiro Sadato, Junichi Chikazoe
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	MVPA decoding machine learning fMRI visions Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/fa04078a989746ad982d8fe62482170e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:fa04078a989746ad982d8fe62482170e
record_format	dspace
spelling	oai:doaj.org-article:fa04078a989746ad982d8fe62482170e2021-12-01T09:06:46ZDistillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing1662-516110.3389/fnhum.2021.777464https://doaj.org/article/fa04078a989746ad982d8fe62482170e2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fnhum.2021.777464/fullhttps://doaj.org/toc/1662-5161Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region decoding technique, we examined whether the information represented in the visual areas can be explained by those represented in the other visual areas. We first predicted the brain activity patterns of an area on the visual pathway from the others, then subtracted the predicted patterns from their originals. Subsequently, the visual features were derived from these residuals. During the visual perception task, the elimination of the top-down signals enhanced the simple visual features represented in the early visual cortices. By contrast, the elimination of the bottom-up signals enhanced the complex visual features represented in the higher visual cortices. The directions of such modulation effects varied across visual perception/imagery tasks, indicating that the information flow across the visual cortices is dynamically altered, reflecting the contents of visual processing. These results demonstrated that the distillation approach is a useful tool to estimate the hidden content of information conveyed across brain regions.Trung Quang PhamShota NishiyamaShota NishiyamaShota NishiyamaNorihiro SadatoNorihiro SadatoJunichi ChikazoeJunichi ChikazoeFrontiers Media S.A.articleMVPAdecodingmachine learningfMRIvisionsNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Human Neuroscience, Vol 15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	MVPA decoding machine learning fMRI visions Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	MVPA decoding machine learning fMRI visions Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Trung Quang Pham Shota Nishiyama Shota Nishiyama Shota Nishiyama Norihiro Sadato Norihiro Sadato Junichi Chikazoe Junichi Chikazoe Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
description	Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region decoding technique, we examined whether the information represented in the visual areas can be explained by those represented in the other visual areas. We first predicted the brain activity patterns of an area on the visual pathway from the others, then subtracted the predicted patterns from their originals. Subsequently, the visual features were derived from these residuals. During the visual perception task, the elimination of the top-down signals enhanced the simple visual features represented in the early visual cortices. By contrast, the elimination of the bottom-up signals enhanced the complex visual features represented in the higher visual cortices. The directions of such modulation effects varied across visual perception/imagery tasks, indicating that the information flow across the visual cortices is dynamically altered, reflecting the contents of visual processing. These results demonstrated that the distillation approach is a useful tool to estimate the hidden content of information conveyed across brain regions.
format	article
author	Trung Quang Pham Shota Nishiyama Shota Nishiyama Shota Nishiyama Norihiro Sadato Norihiro Sadato Junichi Chikazoe Junichi Chikazoe
author_facet	Trung Quang Pham Shota Nishiyama Shota Nishiyama Shota Nishiyama Norihiro Sadato Norihiro Sadato Junichi Chikazoe Junichi Chikazoe
author_sort	Trung Quang Pham
title	Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
title_short	Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
title_full	Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
title_fullStr	Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
title_full_unstemmed	Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing
title_sort	distillation of regional activity reveals hidden content of neural information in visual processing
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/fa04078a989746ad982d8fe62482170e
work_keys_str_mv	AT trungquangpham distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT shotanishiyama distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT shotanishiyama distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT shotanishiyama distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT norihirosadato distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT norihirosadato distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT junichichikazoe distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing AT junichichikazoe distillationofregionalactivityrevealshiddencontentofneuralinformationinvisualprocessing
_version_	1718405392846815232

Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing

Ejemplares similares