We all experience a host of common life stressors such as the death of a family member, medical illness, and financial uncertainty. While most of us are resilient to such stressors, continuing to ...function normally, for a subset of individuals, experiencing these stressors increases the likelihood of developing treatment-resistant, chronic psychological problems, including depression and anxiety. It is thus paramount to identify predictive markers of risk, particularly those reflecting fundamental biological processes that can be targets for intervention and prevention. Using data from a longitudinal study of 340 healthy young adults, we demonstrate that individual differences in threat-related amygdala reactivity predict psychological vulnerability to life stress occurring as much as 1 to 4 years later. These results highlight a readily assayed biomarker, threat-related amygdala reactivity, which predicts psychological vulnerability to commonly experienced stressors and represents a discrete target for intervention and prevention.
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•Amygdala reactivity interacts with stress to predict internalizing symptoms•Amygdala reactivity predicted symptoms as much as 1 to 4 years after scanning
Swartz et al. find that individual differences in a readily assayed neural biomarker, threat-related amygdala reactivity, predict psychological vulnerability to common life stressors as much as 1 to 4 years later.
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.
Recent research has identified a single factor accounting for broad risk to experience common forms of psychopathology. Structural alterations of cerebellar circuitry have emerged as a neural nexus ...of this broad risk, highlighting the cerebellum’s importance for executive control.
Recent research has identified a single factor accounting for broad risk to experience common forms of psychopathology. Structural alterations of cerebellar circuitry have emerged as a neural nexus of this broad risk, highlighting the cerebellum’s importance for executive control.
High rates of comorbidity, shared risk, and overlapping therapeutic mechanisms have led psychopathology research toward transdiagnostic dimensional investigations of clustered symptoms. One ...influential framework accounts for these transdiagnostic phenomena through a single general factor, sometimes referred to as the p factor, associated with risk for all common forms of mental illness.
We build on previous research identifying unique structural neural correlates of the p factor by conducting a data-driven analysis of connectome-wide intrinsic functional connectivity (n = 605).
We demonstrate that higher p factor scores and associated risk for common mental illness maps onto hyperconnectivity between visual association cortex and both frontoparietal and default mode networks.
These results provide initial evidence that the transdiagnostic risk for common forms of mental illness is associated with patterns of inefficient connectome-wide intrinsic connectivity between visual association cortex and networks supporting executive control and self-referential processes, networks that are often impaired across categorical disorders.
Neurobiological factors contributing to violence in humans remain poorly understood. One approach to this question is examining allelic variation in the X-linked monoamine oxidase A (MAOA) gene, ...previously associated with impulsive aggression in animals and humans. Here, we have studied the impact of a common functional polymorphism in MAOA on brain structure and function assessed with MRI in a large sample of healthy human volunteers. We show that the low expression variant, associated with increased risk of violent behavior, predicted pronounced limbic volume reductions and hyperresponsive amygdala during emotional arousal, with diminished reactivity of regulatory prefrontal regions, compared with the high expression allele. In men, the low expression allele is also associated with changes in orbitofrontal volume, amygdala and hippocampus hyperreactivity during aversive recall, and impaired cingulate activation during cognitive inhibition. Our data identify differences in limbic circuitry for emotion regulation and cognitive control that may be involved in the association of MAOA with impulsive aggression, suggest neural systems-level effects of X-inactivation in human brain, and point toward potential targets for a biological approach toward violence.
Neuroimaging, especially BOLD fMRI, has begun to identify how variability in brain function contributes to individual differences in complex behavioral traits. In parallel, pharmacological fMRI and ...multimodal PET/fMRI are identifying how variability in molecular signaling pathways influences individual differences in brain function. Against this background, functional genetic polymorphisms are being utilized to understand the origins of variability in signaling pathways as well as to model efficiently how such emergent variability impacts behaviorally relevant brain function. This article provides an overview of a research strategy seeking to integrate these complementary technologies and utilizes existing empirical data to illustrate its effectiveness in illuminating the neurobiology of individual differences in complex behavioral traits. The article also discusses how such efforts can contribute to the identification of predictive markers that interact with environmental factors to precipitate disease and to develop more effective and individually tailored treatment regimes.
Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough ...resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.
Identifying biological mechanisms through which genes lead to individual differences in emotional behavior is paramount to our understanding of how such differences confer risk for neuropsychiatric ...illness. The emergence of techniques such as
in vivo imaging of brain function in humans and genetic engineering in rodents has provided important new insights into the impact of serotonin (5-HT), a key modulator of emotional behavior, on neural systems subserving anxiety and depression. A major finding has been the discovery of genetic variation in a crucial regulatory molecule within the 5-HT system, the 5HT transporter (5-HTT), and its influence on emotional traits. The study of the 5-HTT provides a new foundation for understanding the neurobiological and genetic basis of emotional regulation and affective illness.
Evidence of marked variability in response among people exposed to the same environmental risk implies that individual differences in genetic susceptibility might be at work. The study of such ...Gene-by-Environment (GxE) interactions has gained momentum. In this article, the authors review research about one of the most extensive areas of inquiry: variation in the promoter region of the serotonin transporter gene (SLC6A4; also known as 5-HTT) and its contribution to stress sensitivity. Research in this area has both advanced basic science and generated broader lessons for studying complex diseases and traits. The authors evaluate four lines of evidence about the 5-HTT stress-sensitivity hypothesis: 1) observational studies about the serotonin transporter linked polymorphic region (5-HTTLPR), stress sensitivity, and depression in humans; 2) experimental neuroscience studies about the 5-HTTLPR and biological phenotypes relevant to the human stress response; 3) studies of 5-HTT variation and stress sensitivity in nonhuman primates; and 4) studies of stress sensitivity and genetically engineered 5-HTT mutations in rodents. The authors then dispel some misconceptions and offer recommendations for GxE research. The authors discuss how GxE interaction hypotheses can be tested with large and small samples, how GxE research can be carried out before as well as after replicated gene discovery, the uses of GxE research as a tool for gene discovery, the importance of construct validation in evaluating GxE research, and the contribution of GxE research to the public understanding of genetic science.
Attempts to link the Big Five personality traits of Openness-to-Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism with variability in trait-like features of brain structure ...have produced inconsistent results. Small sample sizes and heterogeneous methodology have been suspected in driving these inconsistencies. Here, using data collected from 1,107 university students (636 women, mean age 19.69 ± 1.24 years), representing the largest sample to date of unrelated individuals, we tested for associations between the Big Five personality traits and measures of cortical thickness and surface area, subcortical volume, and white matter microstructural integrity. In addition to replication analyses based on a prior study, we conducted exploratory whole-brain analyses. Four supplementary analyses were also conducted to examine 1) possible associations with lower-order facets of personality; 2) modulatory effects of sex; 3) effect of controlling for non-target personality traits; and 4) parcellation scheme effects. Our analyses failed to identify significant associations between the Big Five personality traits and brain morphometry, except for a weak association between greater surface area of the superior temporal gyrus and lower conscientiousness scores. As the latter association is not supported by previous studies, it should be treated with caution. Our supplementary analyses mirrored these predominantly null findings, suggesting they were not substantively biased by our analytic choices. Collectively, these results indicate that if there are associations between the Big Five personality traits and brain structure, they are likely of very small effect size and will require very large samples for reliable detection.
•We conducted replication and exploratory analyses of personality-brain morphometry associations.•Analyses failed to replicate previously found associations.•Exploratory analyses primarily did not yield significant associations.•Personality-brain morphometry associations are weak and require large sample sizes for detection.
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