在停止-信号范式下,皮质下BOLD反应的多研究fMRI前景。

IF 6.4 1区 生物学 Q1 BIOLOGY
eLife Pub Date : 2025-01-22 DOI:10.7554/eLife.88652
Scott Isherwood, Sarah A Kemp, Steven Miletić, Niek Stevenson, Pierre-Louis Bazin, Birte Forstmann
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引用次数: 0

摘要

本研究探讨了人脑反应抑制的功能网络,特别是基底神经节在成功的动作取消中的作用。功能性磁共振成像(fMRI)方法经常使用停止信号任务来检查该网络。我们合并了五个这样的数据集,使用一种新的聚合方法,允许跨站点统一原始fMRI数据。这项荟萃分析,连同其他最近的聚合功能磁共振成像研究,并没有发现成功抑制反应的超直接或间接皮质-基底神经节通路的神经支配的证据。我们确实发现,在失败的停止试验中,皮层下的活动分布很大。我们讨论了fMRI结果与其他研究模式的结果不匹配的可能解释,这些研究模式涉及基底神经节节点的成功抑制。我们还强调了平滑对从特定任务的一般线性模型中得出的结论的实质性影响。首先,本研究提出了元分析方法的概念证明,该方法可以合并广泛的、未处理的或未简化的数据集。它展示了开放获取数据共享可以为研究界提供的巨大潜力。随着越来越多的数据集被公开共享,研究人员将有能力对不仅仅是摘要数据进行元分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm.

This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites. This meta-analysis, along with other recent aggregatory fMRI studies, does not find evidence for the innervation of the hyperdirect or indirect cortico-basal-ganglia pathways in successful response inhibition. What we do find, is large subcortical activity profiles for failed stop trials. We discuss possible explanations for the mismatch of findings between the fMRI results presented here and results from other research modalities that have implicated nodes of the basal ganglia in successful inhibition. We also highlight the substantial effect smoothing can have on the conclusions drawn from task-specific general linear models. First and foremost, this study presents a proof of concept for meta-analytical methods that enable the merging of extensive, unprocessed, or unreduced datasets. It demonstrates the significant potential that open-access data sharing can offer to the research community. With an increasing number of datasets being shared publicly, researchers will have the ability to conduct meta-analyses on more than just summary data.

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来源期刊
eLife
eLife BIOLOGY-
CiteScore
12.90
自引率
3.90%
发文量
3122
审稿时长
17 weeks
期刊介绍: eLife is a distinguished, not-for-profit, peer-reviewed open access scientific journal that specializes in the fields of biomedical and life sciences. eLife is known for its selective publication process, which includes a variety of article types such as: Research Articles: Detailed reports of original research findings. Short Reports: Concise presentations of significant findings that do not warrant a full-length research article. Tools and Resources: Descriptions of new tools, technologies, or resources that facilitate scientific research. Research Advances: Brief reports on significant scientific advancements that have immediate implications for the field. Scientific Correspondence: Short communications that comment on or provide additional information related to published articles. Review Articles: Comprehensive overviews of a specific topic or field within the life sciences.
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