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

IF 3.6 3区 医学 Q2 NEUROSCIENCES Network Neuroscience Pub Date : 2023-10-01 eCollection Date: 2023-01-01 DOI:10.1162/netn_a_00323
Lucina Q Uddin, Richard F Betzel, Jessica R Cohen, Jessica S Damoiseaux, Felipe De Brigard, Simon B Eickhoff, Alex Fornito, Caterina Gratton, Evan M Gordon, Angela R Laird, Linda Larson-Prior, A Randal McIntosh, Lisa D Nickerson, Luiz Pessoa, Ana Luísa Pinho, Russell A Poldrack, Adeel Razi, Sepideh Sadaghiani, James M Shine, Anastasia Yendiki, B T Thomas Yeo, R Nathan Spreng
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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.

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大规模脑网络命名标准化的争议和进展。
科学学科的进步伴随着术语的标准化。网络神经科学,在大脑的宏观组织层面,开始面临与开发其基本解释结构的分类学相关的挑战。网络统一分类工作组(WHATNET)成立于2020年,是人脑映射组织(OHBM)认可的最佳实践委员会,旨在就共识点提供建议,确定悬而未决的问题,并强调正在进行的辩论领域,为推动该领域向网络神经科学结果的标准化报告服务。该委员会进行了一项调查,对大规模脑网络命名法的当前实践进行了编目。一些知名的网络名称(例如,默认模式网络)主导了对调查的回应,出现了一些有启发性的分歧点。我们总结了调查结果,并提供了工作组的初步考虑和建议。这篇观点文章包括对这家企业面临的挑战的选择性回顾,包括(1)网络规模、解决方案和层次结构;(2) 网络的个体间变异性;(3) 网络的动态性和非平稳性;(4) 考虑皮层下结构的网络从属关系;以及(5)对多模式信息的考虑。我们以最低限度的报告指南结束,供认知和网络神经科学社区采用。
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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
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