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时间的映像:体素水平的荟萃分析。

The image of time: a voxel-wise meta-analysis.

机构信息

Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Neuroimage. 2010 Jan 15;49(2):1728-40. doi: 10.1016/j.neuroimage.2009.09.064. Epub 2009 Oct 2.

Abstract

Although there has been an explosion of interest in the neural correlates of time perception during the past decade, substantial disagreement persists regarding the structures that are relevant to interval timing. We addressed this important issue by conducting a comprehensive, voxel-wise meta-analysis using the activation likelihood estimation algorithm; this procedure models each stereotactic coordinate as a 3D Gaussian distribution, then tests the likelihood of activation across all voxels in the brain (Turkeltaub et al., 2002). We included 446 sets of activation foci across 41 studies of timing that report whole-brain analyses. We divided the data set along two dimensions: stimulus duration (sub- vs. supra-second) and nature of response (motor vs. perceptual). Our meta-analyses revealed dissociable neural networks for the processing of duration with motor or perceptual components. Sub-second timing tasks showed a higher propensity to recruit sub-cortical networks, such as the basal ganglia and cerebellum, whereas supra-second timing tasks were more likely to activate cortical structures, such as the SMA and prefrontal cortex. We also detected a differential pattern of activation likelihood in basal ganglia structures, depending on the interval and task design. Finally, a conjunction analysis revealed the SMA and right inferior frontal gyrus as the only structures with significant voxels across all timing conditions. These results suggest that the processing of temporal information is mediated by a distributed network that can be differentially engaged depending on the task requirements.

摘要

尽管在过去的十年中,人们对时间感知的神经相关性产生了浓厚的兴趣,但对于与时间间隔相关的结构仍然存在很大的分歧。我们通过使用激活似然估计算法进行全面的体素级元分析来解决这个重要问题;该程序将每个立体坐标建模为 3D 高斯分布,然后测试大脑中所有体素的激活可能性(Turkeltaub 等人,2002 年)。我们包括了 41 项关于时间的研究中的 446 个激活焦点集,这些研究报告了全脑分析。我们沿着两个维度划分数据集:刺激持续时间(亚秒与超秒)和反应性质(运动与知觉)。我们的元分析揭示了具有运动或知觉成分的处理持续时间的可分离神经网络。亚秒时间任务更倾向于招募皮质下网络,如基底神经节和小脑,而超秒时间任务更可能激活皮质结构,如 SMA 和前额叶皮层。我们还检测到基底神经节结构中激活可能性的差异模式,这取决于间隔和任务设计。最后,联合分析显示 SMA 和右侧额下回是所有时间条件下具有显著体素的唯一结构。这些结果表明,时间信息的处理是由一个分布式网络介导的,这个网络可以根据任务要求进行不同的参与。

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