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Controversies and progress on standardization of large-scale brain network nomenclature.

作者信息

Uddin Lucina Q, Betzel Richard F, Cohen Jessica R, Damoiseaux Jessica S, De Brigard Felipe, Eickhoff Simon B, Fornito Alex, Gratton Caterina, Gordon Evan M, Laird Angela R, Larson-Prior Linda, McIntosh A Randal, Nickerson Lisa D, Pessoa Luiz, Pinho Ana Luísa, Poldrack Russell A, Razi Adeel, Sadaghiani Sepideh, Shine James M, Yendiki Anastasia, Yeo B T Thomas, Spreng R Nathan

机构信息

Department of Psychiatry and Biobehavioral Sciences and Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.

Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.

出版信息

Netw Neurosci. 2023 Oct 1;7(3):864-905. doi: 10.1162/netn_a_00323. eCollection 2023.


DOI:10.1162/netn_a_00323
PMID:37781138
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10473266/
Abstract

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/e7282fb42e59/netn-7-3-864-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/9825c6a36e48/netn-7-3-864-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/b703b73e56aa/netn-7-3-864-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/230a8632dc55/netn-7-3-864-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/5e5ae3b5183c/netn-7-3-864-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/102e972782a5/netn-7-3-864-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/67db84d46b2e/netn-7-3-864-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/e7282fb42e59/netn-7-3-864-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/9825c6a36e48/netn-7-3-864-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/b703b73e56aa/netn-7-3-864-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/230a8632dc55/netn-7-3-864-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/5e5ae3b5183c/netn-7-3-864-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/102e972782a5/netn-7-3-864-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/67db84d46b2e/netn-7-3-864-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/546f/10473266/e7282fb42e59/netn-7-3-864-g007.jpg

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[2]
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[3]
BOLD cofluctuation 'events' are predicted from static functional connectivity.

Neuroimage. 2022-10-15

[4]
Time-resolved structure-function coupling in brain networks.

Commun Biol. 2022-6-2

[5]
Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI.

Neuroimage. 2022-8-15

[6]
Post mortem mapping of connectional anatomy for the validation of diffusion MRI.

Neuroimage. 2022-8-1

[7]
Age differences in the functional architecture of the human brain.

Cereb Cortex. 2022-12-15

[8]
White matter lesion load is associated with lower within- and greater between- network connectivity across older age.

Neurobiol Aging. 2022-4

[9]
Individualized event structure drives individual differences in whole-brain functional connectivity.

Neuroimage. 2022-5-15

[10]
Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.

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