Resting-state fMRI dynamic functional network connectivity and associations with psychopathy traits

被引:30
|
作者
Espinoza, Flor A. [1 ,9 ,10 ]
Anderson, Nathaniel E. [1 ]
Vergara, Victor M. [1 ,9 ,10 ]
Harenski, Carla L. [1 ]
Decety, Jean [2 ,7 ,8 ]
Rachakonda, Srinivas [1 ,9 ,10 ]
Damaraju, Eswar [1 ,9 ,10 ]
Koenigs, Michael [3 ]
Kosson, David S. [4 ]
Harenski, Keith [1 ,6 ]
Calhoun, Vince D. [1 ,5 ,9 ,10 ]
Kiehl, Kent A. [1 ]
机构
[1] Mind Res Network, Albuquerque, NM 87106 USA
[2] Univ Chicago, Dept Psychol, 5848 S Univ Ave, Chicago, IL 60637 USA
[3] Univ Wisconsin, Dept Psychiat, Madison, WI 53706 USA
[4] Rosalind Franklin Univ Med & Sci, Dept Psychol, Chicago, IL USA
[5] Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA
[6] Univ New Mexico, Dept Psychol, Albuquerque, NM 87131 USA
[7] Univ Chicago, Dept Psychiat, Chicago, IL 60637 USA
[8] Univ Chicago, Dept Behav Neurosci, Chicago, IL 60637 USA
[9] Georgia State Univ, Georgia Inst Technol, Tri Inst, Ctr Translat Res Neuroimaging & Data Sci TReNDS, Atlanta, GA 30303 USA
[10] Emory Univ, Atlanta, GA 30322 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Psychopathy; Resting-state fMRI; Dynamic functional network connectivity; Group independent component analysis; K-means clustering; VENTROMEDIAL PREFRONTAL CORTEX; GRAY-MATTER; AMYGDALA; MRI; ATTENTION;
D O I
10.1016/j.nicl.2019.101970
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Studies have used resting-state functional magnetic resonance imaging (rs-fMRI) to examine associations between psychopathy and brain connectivity in selected regions of interest as well as networks covering the whole-brain. One of the limitations of these approaches is that brain connectivity is modeled as a constant state through the scan duration. To address this limitation, we apply group independent component analysis (GICA) and dynamic functional network connectivity (dFNC) analysis to uncover whole-brain, time-varying functional network connectivity (FNC) states in a large forensic sample. We then examined relationships between psychopathic traits (PCL-R total scores, Factor 1 and Factor 2 scores) and FNC states obtained from dFNC analysis. FNC over the scan duration was better represented by five states rather than one state previously shown in static FNC analysis. Consistent with prior findings, psychopathy was associated with networks from paralimbic regions (amygdala and insula). In addition, whole-brain FNC identified 15 networks from nine functional domains (subcortical, auditory, sensorimotor, cerebellar, visual, salience, default mode network, executive control and attentional) related to psychopathy traits (Factor 1 and PCL-R scores). Results also showed that individuals with higher Factor 1 scores (affective and interpersonal traits) spend more time in a state with weaker connectivity overall, and changed states less frequently compared to those with lower Factor 1 scores. On the other hand, individuals with higher Factor 2 scores (impulsive and antisocial behaviors) showed more dynamism (changes to and from different states) than those with lower scores.
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页数:9
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