Functional brain connectivity changes associated with day-to-day fluctuations in affective states

被引:0
|
作者
Racicot, Jeanne [1 ,2 ]
Smine, Salima [1 ]
Afzali, Kamran [3 ]
Orban, Pierre [1 ,2 ]
机构
[1] Ctr Rech Inst Univ Sante Mentale Montreal, Montreal, PQ, Canada
[2] Univ Montreal, Dept Psychiat & addictol, Montreal, PQ, Canada
[3] Univ Montreal, Consortium Sante Numer, Montreal, PQ, Canada
关键词
Amygdala; Emotion; Functional connectivity; Mood; Prefrontal cortex; INDIVIDUAL VARIABILITY; WORKING-MEMORY; RESTING-STATE; EMOTIONS; NETWORKS; FMRI; ORGANIZATION; PERFORMANCE; MODULATION; STRATEGIES;
D O I
10.3758/s13415-024-01216-6
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Affective neuroscience has traditionally relied on cross-sectional studies to uncover the brain correlates of affects, emotions, and moods. Such findings obfuscate intraindividual variability that may reveal meaningful changing affect states. The few functional magnetic resonance imaging longitudinal studies that have linked changes in brain function to the ebbs and flows of affective states over time have mostly investigated a single individual. In this study, we explored how the functional connectivity of brain areas associated with affective processes can explain within-person fluctuations in self-reported positive and negative affects across several subjects. To do so, we leveraged the Day2day dataset that includes 40 to 50 resting-state functional magnetic resonance imaging scans along self-reported positive and negative affectivity from a sample of six healthy participants. Sparse multivariate mixed-effect linear models could explain 15% and 11% of the within-person variation in positive and negative affective states, respectively. Evaluation of these models' generalizability to new data demonstrated the ability to predict approximately 5% and 2% of positive and negative affect variation. The functional connectivity of limbic areas, such as the amygdala, hippocampus, and insula, appeared most important to explain the temporal dynamics of affects over days, weeks, and months.
引用
收藏
页码:1141 / 1154
页数:14
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