Goal-Directed Processing of Naturalistic Stimuli Modulates Large-Scale Functional Connectivity

被引:6
|
作者
Wen, Zhenfu [1 ,2 ]
Yu, Tianyou [1 ,2 ]
Yang, Xinbin [3 ]
Li, Yuanqing [1 ,2 ]
机构
[1] South China Univ Technol, Ctr Brain Comp Interfaces & Brain Informat Proc, Guangzhou, Guangdong, Peoples R China
[2] Guangzhou Key Lab Brain Comp Interact & Applicat, Guangzhou, Guangdong, Peoples R China
[3] Guangzhou Med Univ, Affiliated Canc Hosp & Inst, Dept Surg Thorac Oncol, Guangzhou, Guangdong, Peoples R China
来源
FRONTIERS IN NEUROSCIENCE | 2019年 / 12卷
基金
国家重点研发计划;
关键词
top-down goals; naturalistic condition; inter-subject functional correlation; multivariate pattern analysis; large-scale brain networks; HUMAN BRAIN; ATTENTION; NETWORK; REPRESENTATIONS; DYNAMICS; PATTERNS; FEATURES; DORSAL; CORTEX; AREAS;
D O I
10.3389/fnins.2018.01003
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Humans selectively process external information according to their internal goals. Previous studies have found that cortical activity and interactions between specific cortical areas such as frontal-parietal regions are modulated by behavioral goals. However, these results are largely based on simple stimuli and task rules in laboratory settings. Here, we investigated how top-down goals modulate whole-brain functional connectivity (FC) under naturalistic conditions. Analyses were conducted on a publicly available functional magnetic resonance imaging (fMRl) dataset (OpenfMRl database, accession number: ds000233) collected on twelve participants who made either behavioral or taxonomic judgments of behaving animals containing in naturalistic video clips. The task-evoked FC patterns of the participants were extracted using a novel inter-subject functional correlation (ISFC) method that increases the signal-to-noise ratio for detecting task-induced inter-regional correlation compared with standard FC analysis. Using multivariate pattern analysis (MVPA) methods, we successfully predicted the task goals of the participants with ISFC patterns but not with standard FC patterns, suggests that the ISFC method may be an efficient tool for exploring subtle network differences between brain states. We further examined the predictive power of several canonical brain networks and found that many within-network and across-network ISFC measures supported task goals classification. Our findings suggest that goal-directed processing of naturalistic stimuli systematically modulates large-scale brain networks but is not limited to the local neural activity or connectivity of specific regions.
引用
收藏
页数:12
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