Development of human emotion circuits investigated using a Big-Data analytic approach: Stability, reliability, and robustness.

JOURNAL OF NEUROSCIENCE(2019)

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摘要
Emotion perception is fundamental to affective and cognitive development and is thought to involve distributed brain circuits. Efforts to chart neurodevelopmental changes in emotion have been severely hampered by narrowly focused approaches centered on activation of individual brain regions and small sample sizes. Here we investigate the maturation of human functional brain circuits associated with identification of fearful, angry, sad, happy, and neutral faces using a large sample of 759 children, adolescents, and adults (ages 8-23; female/male = 419/340). Network analysis of emotion-related brain circuits revealed three functional modules, encompassing lateral frontoparietal, medial prefrontal-posterior cingulate, and subcortical-posterior insular cortices, with hubs in medial prefrontal, but not posterior cingulate, cortex. This overall network architecture was stable by age 8, and it anchored maturation of circuits important for salience detection and cognitive control, as well as dissociable circuit patterns across distinct emotion categories. Our findings point to similarities and differences in functional circuits associated with identification of fearful, angry, sad, happy, and neutral faces, and reveal aspects of brain circuit organization underlying emotion perception that are stable over development as well as features that change with age. Reliability analyses demonstrated the robustness of our findings and highlighted the importance of large samples for probing functional brain circuit development. Our study emphasizes a need to focus beyond amygdala circuits and provides a robust neurodevelopmental template for investigating emotion perception and identification in psychopathology.
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关键词
Big-Data,emotion perception and identification,functional networks,maturation,reliability,replicability
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