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BrainIAK: The Brain Imaging Analysis Kit
Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optimized solutions to key problems in advanced fMRI an...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351935/ https://www.ncbi.nlm.nih.gov/pubmed/35939268 http://dx.doi.org/10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da |
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author | Kumar, Manoj Anderson, Michael J. Antony, James W. Baldassano, Christopher Brooks, Paula P. Cai, Ming Bo Chen, Po-Hsuan Cameron Ellis, Cameron T. Henselman-Petrusek, Gregory Huberdeau, David Hutchinson, J. Benjamin Li, Y. Peeta Lu, Qihong Manning, Jeremy R. Mennen, Anne C. Nastase, Samuel A. Richard, Hugo Schapiro, Anna C. Schuck, Nicolas W. Shvartsman, Michael Sundaram, Narayanan Suo, Daniel Turek, Javier S. Turner, David Vo, Vy A. Wallace, Grant Wang, Yida Williams, Jamal A. Zhang, Hejia Zhu, Xia Capotă, Mihai Cohen, Jonathan D. Hasson, Uri Li, Kai Ramadge, Peter J. Turk-Browne, Nicholas B. Willke, Theodore L. Norman, Kenneth A. |
author_facet | Kumar, Manoj Anderson, Michael J. Antony, James W. Baldassano, Christopher Brooks, Paula P. Cai, Ming Bo Chen, Po-Hsuan Cameron Ellis, Cameron T. Henselman-Petrusek, Gregory Huberdeau, David Hutchinson, J. Benjamin Li, Y. Peeta Lu, Qihong Manning, Jeremy R. Mennen, Anne C. Nastase, Samuel A. Richard, Hugo Schapiro, Anna C. Schuck, Nicolas W. Shvartsman, Michael Sundaram, Narayanan Suo, Daniel Turek, Javier S. Turner, David Vo, Vy A. Wallace, Grant Wang, Yida Williams, Jamal A. Zhang, Hejia Zhu, Xia Capotă, Mihai Cohen, Jonathan D. Hasson, Uri Li, Kai Ramadge, Peter J. Turk-Browne, Nicholas B. Willke, Theodore L. Norman, Kenneth A. |
author_sort | Kumar, Manoj |
collection | PubMed |
description | Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optimized solutions to key problems in advanced fMRI analysis. A variety of techniques are presently included in BrainIAK: intersubject correlation (ISC) and intersubject functional connectivity (ISFC), functional alignment via the shared response model (SRM), full correlation matrix analysis (FCMA), a Bayesian version of representational similarity analysis (BRSA), event segmentation using hidden Markov models, topographic factor analysis (TFA), inverted encoding models (IEMs), an fMRI data simulator that uses noise characteristics from real data (fmrisim), and some emerging methods. These techniques have been optimized to leverage the efficiencies of high-performance compute (HPC) clusters, and the same code can be se amlessly transferred from a laptop to a cluster. For each of the aforementioned techniques, we describe the data analysis problem that the technique is meant to solve and how it solves that problem; we also include an example Jupyter notebook for each technique and an annotated bibliography of papers that have used and/or described that technique. In addition to the sections describing various analysis techniques in BrainIAK, we have included sections describing the future applications of BrainIAK to real-time fMRI, tutorials that we have developed and shared online to facilitate learning the techniques in BrainIAK, computational innovations in BrainIAK, and how to contribute to BrainIAK. We hope that this manuscript helps readers to understand how BrainIAK might be useful in their research. |
format | Online Article Text |
id | pubmed-9351935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-93519352022-08-04 BrainIAK: The Brain Imaging Analysis Kit Kumar, Manoj Anderson, Michael J. Antony, James W. Baldassano, Christopher Brooks, Paula P. Cai, Ming Bo Chen, Po-Hsuan Cameron Ellis, Cameron T. Henselman-Petrusek, Gregory Huberdeau, David Hutchinson, J. Benjamin Li, Y. Peeta Lu, Qihong Manning, Jeremy R. Mennen, Anne C. Nastase, Samuel A. Richard, Hugo Schapiro, Anna C. Schuck, Nicolas W. Shvartsman, Michael Sundaram, Narayanan Suo, Daniel Turek, Javier S. Turner, David Vo, Vy A. Wallace, Grant Wang, Yida Williams, Jamal A. Zhang, Hejia Zhu, Xia Capotă, Mihai Cohen, Jonathan D. Hasson, Uri Li, Kai Ramadge, Peter J. Turk-Browne, Nicholas B. Willke, Theodore L. Norman, Kenneth A. Apert Neuro Article Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optimized solutions to key problems in advanced fMRI analysis. A variety of techniques are presently included in BrainIAK: intersubject correlation (ISC) and intersubject functional connectivity (ISFC), functional alignment via the shared response model (SRM), full correlation matrix analysis (FCMA), a Bayesian version of representational similarity analysis (BRSA), event segmentation using hidden Markov models, topographic factor analysis (TFA), inverted encoding models (IEMs), an fMRI data simulator that uses noise characteristics from real data (fmrisim), and some emerging methods. These techniques have been optimized to leverage the efficiencies of high-performance compute (HPC) clusters, and the same code can be se amlessly transferred from a laptop to a cluster. For each of the aforementioned techniques, we describe the data analysis problem that the technique is meant to solve and how it solves that problem; we also include an example Jupyter notebook for each technique and an annotated bibliography of papers that have used and/or described that technique. In addition to the sections describing various analysis techniques in BrainIAK, we have included sections describing the future applications of BrainIAK to real-time fMRI, tutorials that we have developed and shared online to facilitate learning the techniques in BrainIAK, computational innovations in BrainIAK, and how to contribute to BrainIAK. We hope that this manuscript helps readers to understand how BrainIAK might be useful in their research. 2021 2022-02-16 /pmc/articles/PMC9351935/ /pubmed/35939268 http://dx.doi.org/10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da Text en https://creativecommons.org/licenses/by/4.0/Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 IGO License (https://creativecommons.org/licenses/by/4.0/) , which permits the copy and redistribution of the material in any medium or format provided the original work and author are properly credited. In any reproduction of this article there should not be any suggestion that APERTURE NEURO or this article endorse any specific organization or products. The use of the APERTURE NEURO logo is not permitted. This notice should be preserved along with the article’s original URL. Open access logo and text by PLoS, under the Creative Commons Attribution-Share Alike 4.0 Unported license. |
spellingShingle | Article Kumar, Manoj Anderson, Michael J. Antony, James W. Baldassano, Christopher Brooks, Paula P. Cai, Ming Bo Chen, Po-Hsuan Cameron Ellis, Cameron T. Henselman-Petrusek, Gregory Huberdeau, David Hutchinson, J. Benjamin Li, Y. Peeta Lu, Qihong Manning, Jeremy R. Mennen, Anne C. Nastase, Samuel A. Richard, Hugo Schapiro, Anna C. Schuck, Nicolas W. Shvartsman, Michael Sundaram, Narayanan Suo, Daniel Turek, Javier S. Turner, David Vo, Vy A. Wallace, Grant Wang, Yida Williams, Jamal A. Zhang, Hejia Zhu, Xia Capotă, Mihai Cohen, Jonathan D. Hasson, Uri Li, Kai Ramadge, Peter J. Turk-Browne, Nicholas B. Willke, Theodore L. Norman, Kenneth A. BrainIAK: The Brain Imaging Analysis Kit |
title | BrainIAK: The Brain Imaging Analysis Kit |
title_full | BrainIAK: The Brain Imaging Analysis Kit |
title_fullStr | BrainIAK: The Brain Imaging Analysis Kit |
title_full_unstemmed | BrainIAK: The Brain Imaging Analysis Kit |
title_short | BrainIAK: The Brain Imaging Analysis Kit |
title_sort | brainiak: the brain imaging analysis kit |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351935/ https://www.ncbi.nlm.nih.gov/pubmed/35939268 http://dx.doi.org/10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da |
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