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Intrinsic non-hub connectivity predicts human inter-temporal decision-making
Authors:Wang  Qiang  Zhu  Yuxuan  Wang  Yajie  Chen  Chuansheng  He  Qinghua  Xue  Gui
Institution:1.Key Research Base of Humanities and Social Sciences of the Ministry of Education, Academy of Psychology and Behavior, Tianjin Normal University, Tianjin, 300387, China
;2.Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China
;3.Tianjin Social Science Laboratory of Students’ Mental Development and Learning, Tianjin, 300387, China
;4.Department of Psychological Science, University of California, Irvine, CA, 92697-7085, USA
;5.Faculty of Psychology, Southwest University, Chongqing, 400715, China
;6.CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, China
;7.National Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
;
Abstract:

Inter-temporal decision-making is ubiquitous in daily life and has been considered as a critical characteristic associated with an individual’s success. Such decisions require us to tradeoff between short-term and long-term benefits. Prior studies have indicated that inter-temporal decision involves various brain regions that tend to occupy the central hubs. However, it is unclear whether the functional connectivities among hub as well as non-hub regions can predict discounting behaviors. Here, we combined with graph-theoretical algorithm and multivariate pattern analysis to explore whether voxel-wise functional connectivity strength in the whole brain could predict discounting rates (indexed as logk, based on the adaptive delay-discounting task) in a relatively large sample (n = 429) of young adults. Results revealed that short- and long-distance as well as all-range non-hub functional connectivity strength in the limbic system (i.e., medial orbitofrontal cortex and parahippocampus) were inversely associated with discounting rates. Furthermore, these results were robust and did not appear to be due to potential confounding factors. Above weight-based degree metric is commonly indicative of the communication pattern of local and global parallel information processing, and it therefore provides novel insights into the neural mechanisms underlying inter-temporal decision-making from the perspective of human brain topological organizations.

Keywords:
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