Predicting Task and Subject Differences with Functional Connectivity and Blood-Oxygen-Level-Dependent Variability

被引:14
作者
Gaut, Garren [1 ]
Turner, Brandon [2 ]
Lu, Zhong-Lin [2 ,3 ]
Li, Xiangrui [2 ,3 ]
Cunningham, William A. [4 ]
Steyvers, Mark [1 ]
机构
[1] Univ Calif Irvine, Dept Cognit Sci, 2316 Social & Behav Sci Gateway Bldg, Irvine, CA 92697 USA
[2] Ohio State Univ, Dept Psychol, Columbus, OH USA
[3] Ohio State Univ, Ctr Cognit & Behav Brain Imaging, Columbus, OH 43210 USA
[4] Univ Toronto, Dept Psychol, Toronto, ON, Canada
关键词
BOLD variability; fMRI; functional connectivity; machine learning; subject identity classification; task classification; INDIVIDUAL-DIFFERENCES; SIGNAL VARIABILITY; BOLD VARIABILITY; COGNITIVE STATES; BRAIN; RELIABILITY; REGRESSION; SELECTION; MEMORY; MRI;
D O I
10.1089/brain.2018.0632
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Previous research has found that functional connectivity (FC) can accurately predict the identity of a subject performing a task and the type of task being performed. These results are replicated using a large data set collected at the Ohio State University Center for Cognitive and Behavioral Brain Imaging. This work introduces a novel perspective on task and subject identity prediction: blood-oxygen-level-dependent variability (BV). Conceptually, BV is a region-specific measure based on the variance within each brain region. BV is simple to compute, interpret, and visualize. This work shows that both FC and BV are predictive of task and subject, even across scanning sessions separated by multiple years. Subject differences rather than task differences account for the majority of changes in BV and FC. Similar to results in FC, BV is reduced during cognitive tasks relative to rest.
引用
收藏
页码:451 / 463
页数:13
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