Department of Mathematics, Faculty of Sciences, VU Amsterdam, the Netherlands; Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain; Institució Catalana de la Recerca i Estudis Avancats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain.
Research Center for Motor Control and Neuroplasticity, KU Leuven, Tervuursevest 101, 3001, Leuven, Belgium; Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy.
Neuroimage. 2019 Oct 15;200:259-274. doi: 10.1016/j.neuroimage.2019.06.007. Epub 2019 Jun 13.
Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.
由于 BOLD-fMRI 的时间分辨率较低，因此人类大脑功能的成像研究几乎完全集中在数据中的瞬时相关性上。然而，硬件和采集协议的发展提供了具有更高采样率的数据，从而可以研究 BOLD-fMRI 数据的潜伏期结构。在这项研究中，我们描述了一种分析 BOLD-fMRI 数据潜伏期结构的方法，并将其应用于来自人类连接组计划的 94 名参与者的静息状态数据。该方法表明，任务正性和任务负性网络通过早期视觉皮层内的 BOLD 波的传播而整合在一起。这些波从视野的外围开始，并向中央凹传播。这一观察结果为任务正性和任务负性网络的功能整合提供了一种机制，支持基于视场外围的视觉信息处理观点，并有助于新兴的观点，即静息状态 BOLD-fMRI 波动是固有时空模式的叠加。
