5 research outputs found

    Author Correction: An analysis-ready and quality controlled resource for pediatric brain white-matter research

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    Probing associations between structural brain connectivity, childhood maltreatment, and later antisocial behavior

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    Childhood maltreatment, a form of early life stress, impacts an extraordinary number of children per year and has profound implications for mental health and other psychosocial outcomes. Abuse experienced as a child is well-linked to antisocial behavior such as aggression and misconduct and to alterations in neural structures and pathways. Many of the neural structures implicated in childhood maltreatment are crucial components of emotional regulatory brain networks, connected through pathways including the uncinate fasciculus, the cingulum bundle, and the fornix. Poorer emotion regulation has been pointed to as an underlying factor contributing to antisocial behavior; therefore, we seek to explore if alterations in neural emotion-regulatory pathways significantly account for a portion of the established link between childhood maltreatment and adult antisocial behavior. We explored these related questions in a subsample of the Pittsburgh Youth Study dataset – a unique, multi-decade longitudinal study of youth and family processes. Related to childhood maltreatment and violence in adulthood, we did not find significant associations between childhood maltreatment and violent adult criminal versatility within our sample. Connected to potential neural mediators, we also did not find any significant associations between childhood maltreatment and white matter integrity in the aforementioned tracts involved in emotion regulation. Further, we found no associations between white matter integrity in these tracts and violent criminal versatility. Potential explanations for this pattern of null findings, as well as implications for this field of research, are discussed. Further work is needed to continue to understand the associations between childhood abuse, the brain, and violent antisocial behavior in order to elucidate the downstream associations of early life stress on later behavior

    Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer

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    Abstract On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had “excellent” numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability. Graphical Abstrac

    Modeling emotion in complex stories: the Stanford Emotional Narratives Dataset

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    10.1109/taffc.2019.2955949IEEE Transactions on Affective Computing1-
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