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Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision
The human language system interacts with cognitive and sensorimotor regions during natural language processing. However, where, when, and how these processes occur remain unclear. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal re...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312422/ https://www.ncbi.nlm.nih.gov/pubmed/37398177 http://dx.doi.org/10.1101/2023.05.29.542546 |
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author | Lei, Victoria Lai Cheng Leong, Teng Ieng Leong, Cheok Teng Liu, Lili Choi, Chi Un Sereno, Martin I. Li, Defeng Huang, Ruey-Song |
author_facet | Lei, Victoria Lai Cheng Leong, Teng Ieng Leong, Cheok Teng Liu, Lili Choi, Chi Un Sereno, Martin I. Li, Defeng Huang, Ruey-Song |
author_sort | Lei, Victoria Lai Cheng |
collection | PubMed |
description | The human language system interacts with cognitive and sensorimotor regions during natural language processing. However, where, when, and how these processes occur remain unclear. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging (fMRI) data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured neural information flows as coherent waves traveling over the cortical surface during listening, reciting, and oral cross-language interpreting. The timing, location, direction, and surge of traveling waves, visualized as ‘brainstorms’ on brain ‘weather’ maps, reveal the functional and effective connectivity of the brain in action. These maps uncover the functional neuroanatomy of language perception and production and motivate the construction of finer-grained models of human information processing. |
format | Online Article Text |
id | pubmed-10312422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103124222023-07-01 Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision Lei, Victoria Lai Cheng Leong, Teng Ieng Leong, Cheok Teng Liu, Lili Choi, Chi Un Sereno, Martin I. Li, Defeng Huang, Ruey-Song bioRxiv Article The human language system interacts with cognitive and sensorimotor regions during natural language processing. However, where, when, and how these processes occur remain unclear. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging (fMRI) data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured neural information flows as coherent waves traveling over the cortical surface during listening, reciting, and oral cross-language interpreting. The timing, location, direction, and surge of traveling waves, visualized as ‘brainstorms’ on brain ‘weather’ maps, reveal the functional and effective connectivity of the brain in action. These maps uncover the functional neuroanatomy of language perception and production and motivate the construction of finer-grained models of human information processing. Cold Spring Harbor Laboratory 2023-05-29 /pmc/articles/PMC10312422/ /pubmed/37398177 http://dx.doi.org/10.1101/2023.05.29.542546 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Lei, Victoria Lai Cheng Leong, Teng Ieng Leong, Cheok Teng Liu, Lili Choi, Chi Un Sereno, Martin I. Li, Defeng Huang, Ruey-Song Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title | Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title_full | Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title_fullStr | Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title_full_unstemmed | Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title_short | Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision |
title_sort | phase-encoded fmri tracks down brainstorms of natural language processing with sub-second precision |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312422/ https://www.ncbi.nlm.nih.gov/pubmed/37398177 http://dx.doi.org/10.1101/2023.05.29.542546 |
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