Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan.
Neuroimage. 2019 Nov 15;202:116042. doi: 10.1016/j.neuroimage.2019.116042. Epub 2019 Jul 22.
The analysis of functional magnetic resonance imaging (fMRI) data is challenging when subjects are under exposure to natural sensory stimulation. In this study, a two-stage approach was developed to enable the identification of connectivity networks involved in the processing of information in the brain under natural sensory stimulation. In the first stage, the degree of concordance between the results of inter-subject and intra-subject correlation analyses is assessed statistically. The microstructurally (i.e., cytoarchitectonically) defined brain areas are designated either as concordant in which the results of both correlation analyses are in agreement, or as discordant in which one analysis method shows a higher proportion of supra-threshold voxels than does the other. In the second stage, connectivity networks are identified using the time courses of supra-threshold voxels in brain areas contingent upon the classifications derived in the first stage. In an empirical study, fMRI data were collected from 40 young adults (19 males, average age 22.76 ± 3.25), who underwent auditory stimulation involving sound clips of human voices and animal vocalizations under two operational conditions (i.e., eyes-closed and eyes-open). The operational conditions were designed to assess confounding effects due to auditory instructions or visual perception. The proposed two-stage analysis demonstrated that stress modulation (affective) and language networks in the limbic and cortical structures were respectively engaged during sound stimulation, and presented considerable variability among subjects. The network involved in regulating visuomotor control was sensitive to the eyes-open instruction, and presented only small variations among subjects. A high degree of concordance was observed between the two analyses in the primary auditory cortex which was highly sensitive to the pitch of sound clips. Our results have indicated that brain areas can be identified as concordant or discordant based on the two correlation analyses. This may further facilitate the search for connectivity networks involved in the processing of information under natural sensory stimulation.
当研究对象处于自然感官刺激下时，对功能磁共振成像（fMRI）数据的分析具有挑战性。在这项研究中，开发了一种两阶段方法，以识别在自然感官刺激下大脑中信息处理所涉及的连接网络。在第一阶段，统计评估组内和组间相关分析结果的一致性程度。根据两种相关分析结果的一致性，将微观结构（即细胞构筑学）定义的大脑区域指定为一致区域，或者将其中一种分析方法显示出比另一种分析方法更高比例的超阈值体素的区域指定为不一致区域。在第二阶段，使用大脑区域中超阈值体素的时间历程来识别连接网络，这些时间历程取决于第一阶段得出的分类。在一项实证研究中，从 40 名年轻成年人（19 名男性，平均年龄 22.76±3.25 岁）中收集了 fMRI 数据，他们在两种操作条件（即闭眼和睁眼）下接受了涉及人类声音和动物叫声的声音片段的听觉刺激。操作条件旨在评估听觉指令或视觉感知引起的混杂效应。所提出的两阶段分析表明，在声音刺激期间，边缘和皮质结构中的应激调节（情感）和语言网络分别被激活，并且在个体之间存在相当大的变异性。调节视动控制的网络对睁眼指令敏感，并且在个体之间仅呈现较小的变化。在对声音片段的音高高度敏感的初级听觉皮层中，两种分析之间观察到高度一致性。我们的结果表明，可以根据两种相关分析将大脑区域识别为一致或不一致。这可能进一步促进对自然感官刺激下信息处理所涉及的连接网络的搜索。
