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
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.
Netw Neurosci. 2023 Oct 1;7(3):864-905. doi: 10.1162/netn_a_00323. eCollection 2023.
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.
科学学科的进步伴随着术语的标准化。在大脑宏观组织层面的网络神经科学,正开始面临与发展其基本解释结构的分类法相关的挑战。网络统一分类法工作组(WHATNET)于2020年成立,作为一个得到人类大脑图谱组织(OHBM)认可的最佳实践委员会,旨在就共识点提供建议、识别未解决的问题,并突出正在进行辩论的领域,以推动该领域朝着网络神经科学结果的标准化报告发展。该委员会进行了一项调查,以梳理大规模脑网络命名法的当前实践。一些知名的网络名称(如默认模式网络)在调查回复中占主导地位,同时也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思考和建议。这篇观点文章选择性地回顾了这项工作面临的挑战,包括:(1)网络规模、分辨率和层次结构;(2)网络的个体间变异性;(3)网络的动态性和非平稳性;(4)对皮层下结构网络归属的考量;以及(5)对多模态信息的考量。我们最后给出了认知和网络神经科学界可采用的最低报告指南。