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Recent advances in functional neuroimaging analysis for cognitive neuroscience
Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7119434/ https://www.ncbi.nlm.nih.gov/pubmed/32285010 http://dx.doi.org/10.1177/2398212817752727 |
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author | Williams, Nitin Henson, Richard N. |
author_facet | Williams, Nitin Henson, Richard N. |
author_sort | Williams, Nitin |
collection | PubMed |
description | Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives. |
format | Online Article Text |
id | pubmed-7119434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-71194342020-04-13 Recent advances in functional neuroimaging analysis for cognitive neuroscience Williams, Nitin Henson, Richard N. Brain Neurosci Adv Editorial Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives. SAGE Publications 2018-01-19 /pmc/articles/PMC7119434/ /pubmed/32285010 http://dx.doi.org/10.1177/2398212817752727 Text en © The Author(s) 2018 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Editorial Williams, Nitin Henson, Richard N. Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title | Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title_full | Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title_fullStr | Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title_full_unstemmed | Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title_short | Recent advances in functional neuroimaging analysis for cognitive neuroscience |
title_sort | recent advances in functional neuroimaging analysis for cognitive neuroscience |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7119434/ https://www.ncbi.nlm.nih.gov/pubmed/32285010 http://dx.doi.org/10.1177/2398212817752727 |
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