Browsing by Subject "individual differences"

Now showing 1 - 5 of 5
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    Individual differences in regulatory focus predict neural response to reward.
    (Soc Neurosci, 2016-04-30) Scult, Matthew A; Knodt, Annchen R; Hanson, Jamie L; Ryoo, Minyoung; Adcock, R Alison; Hariri, Ahmad R; Strauman, Timothy J
    Although goal pursuit is related to both functioning of the brain's reward circuits and psychological factors, the literatures surrounding these concepts have often been separate. Here, we use the psychological construct of regulatory focus to investigate individual differences in neural response to reward. Regulatory focus theory proposes two motivational orientations for personal goal pursuit: (1) promotion, associated with sensitivity to potential gain, and (2) prevention, associated with sensitivity to potential loss. The monetary incentive delay task was used to manipulate reward circuit function, along with instructional framing corresponding to promotion and prevention in a within-subject design. We observed that the more promotion oriented an individual was, the lower their ventral striatum response to gain cues. Follow-up analyses revealed that greater promotion orientation was associated with decreased ventral striatum response even to no-value cues, suggesting that promotion orientation may be associated with relatively hypoactive reward system function. The findings are also likely to represent an interaction between the cognitive and motivational characteristics of the promotion system with the task demands. Prevention orientation did not correlate with ventral striatum response to gain cues, supporting the discriminant validity of regulatory focus theory. The results highlight a dynamic association between individual differences in self-regulation and reward system function.
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    Individual differences in toddlers' social understanding and prosocial behavior: disposition or socialization?
    (Front Psychol, 2015) Gross, Rebekkah L; Drummond, Jesse; Satlof-Bedrick, Emma; Waugh, Whitney E; Svetlova, Margarita; Brownell, Celia A
    We examined how individual differences in social understanding contribute to variability in early-appearing prosocial behavior. Moreover, potential sources of variability in social understanding were explored and examined as additional possible predictors of prosocial behavior. Using a multi-method approach with both observed and parent-report measures, 325 children aged 18-30 months were administered measures of social understanding (e.g., use of emotion words; self-understanding), prosocial behavior (in separate tasks measuring instrumental helping, empathic helping, and sharing, as well as parent-reported prosociality at home), temperament (fearfulness, shyness, and social fear), and parental socialization of prosocial behavior in the family. Individual differences in social understanding predicted variability in empathic helping and parent-reported prosociality, but not instrumental helping or sharing. Parental socialization of prosocial behavior was positively associated with toddlers' social understanding, prosocial behavior at home, and instrumental helping in the lab, and negatively associated with sharing (possibly reflecting parents' increased efforts to encourage children who were less likely to share). Further, socialization moderated the association between social understanding and prosocial behavior, such that social understanding was less predictive of prosocial behavior among children whose parents took a more active role in socializing their prosociality. None of the dimensions of temperament was associated with either social understanding or prosocial behavior. Parental socialization of prosocial behavior is thus an important source of variability in children's early prosociality, acting in concert with early differences in social understanding, with different patterns of influence for different subtypes of prosocial behavior.
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    Neurobehavioral Mechanisms of Resilience Against Emotional Distress: An Integrative Brain-Personality-Symptom Approach Using Structural Equation Modeling.
    (Personality neuroscience, 2018-01) Moore, Matthew; Culpepper, Steven; Phan, K Luan; Strauman, Timothy J; Dolcos, Florin; Dolcos, Sanda
    Clarifying individual differences that predict resilience or vulnerability to emotional distress is crucial for identifying etiological factors contributing to affective disturbances, and to promoting emotional well-being. Despite recent progress identifying specific brain regions and personality traits, it remains unclear whether there are common factors underlying the structural aspects of the brain and the personality traits that, in turn, protect against symptoms of emotional distress. In the present study, an integrative structural equation model was developed to examine the associations among (1) a latent construct of Control, representing the volumes of a system of prefrontal cortical (PFC) regions including middle, inferior, and orbital frontal cortices; (2) a latent construct of Resilience personality traits including cognitive reappraisal, positive affectivity, and optimism; and (3) Anxiety and Depression symptoms, in a sample of 85 healthy young adults. Results showed that the latent construct of PFC volumes positively predicted the latent construct of Resilience, which in turn negatively predicted Anxiety. Mediation analysis confirmed that greater latent PFC volume is indirectly associated with lower Anxiety symptoms through greater latent trait Resilience. The model did not show a significant mediation for Depression. These results support the idea that there are common volumetric and personality factors that help protect against symptoms of emotional distress. These findings provide strong evidence that such brain-personality-symptom approaches can provide novel insights with valuable implications for understanding the interaction of these factors in healthy and clinically diagnosed individuals.
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    Revising a Self-Regulation Phenotype for Depression Through Individual Differences in Macroscale Brain Organization.
    (Current directions in psychological science, 2023-08) Strauman, Timothy J; Hariri, Ahmad R
    Self-regulation denotes the processes by which people initiate, maintain, and control their own thoughts, behaviors, or emotions to produce a desired outcome or avoid an undesired outcome. Self-regulation brings the influence of distal factors such as biology, temperament, and socialization history onto cognition, motivation, and behavior. Dysfunction in self-regulation represents a contributory causal factor for psychopathology. Accordingly, we previously proposed a risk phenotype model for depression drawing from regulatory focus theory and traditional task-based fMRI studies. In this article, we revise and expand our risk phenotype model using insights from new methodologies allowing quantification of individual differences in task-free macroscale brain organization. We offer a set of hypotheses as examples of how examination of intrinsic macroscale brain organization can extend and enrich investigations of self-regulation and depression. In doing so, we hope to promote a useful heuristic for model development and for identifying transdiagnostic risk phenotypes in psychopathology.
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    What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis.
    (Psychological science, 2020-07) Elliott, Maxwell L; Knodt, Annchen R; Ireland, David; Morris, Meriwether L; Poulton, Richie; Ramrakha, Sandhya; Sison, Maria L; Moffitt, Terrie E; Caspi, Avshalom; Hariri, Ahmad R
    Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.