Individual differences in common factors of emotional traits and executive functions predict functional connectivity of the amygdala.

Evidence suggests that individual differences in emotion control are associated with frontoparietal-limbic networks and linked to emotional traits and executive functions. In a first attempt to directly target the link between emotional traits and executive functions using resting-state fMRI analysis, 43 healthy adults completed a test battery including executive tasks and emotional trait self-assessments that were subjected to a principal component analysis. Of the three factors detected, two explained 40.4% of the variance and were further investigated. Both factors suggest a relation between emotional traits and executive functions. Specifically, the first factor consisted of measures related to inhibitory control and negative affect, and the second factor was related to reward and positive affect. To investigate whether this interplay between emotional traits and executive functions is reflected in neural connectivity, we used resting-state fMRI to explore the functional connectivity of the amygdala as a starting point, and progressed to other seed-based analyses based on the initial findings. We found that the first factor predicted the strength of connectivity between brain regions known to be involved in the cognitive control of emotion, including the amygdala and the dorsolateral prefrontal cortex, whereas the second factor predicted the strength of connectivity between brain regions known to be involved in reward and attention, including the amygdala, the caudate and the thalamus. These findings suggest that individual differences in the ability to inhibit negative affect are mediated by prefrontal-limbic pathways, while the ability to be positive and use rewarding information is mediated by a network that includes the amygdala and thalamostriatal regions.

Age of onset in obsessive-compulsive disorder: admixture analysis with a large sample.

BACKGROUND: Research into age of onset in obsessive-compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early- and late-onset OCD, rendering inconsistent results that are difficult to interpret. METHOD: In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered. RESULTS: A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset ≤19 years). Patients with early age of onset were more likely to be single. Early age of onset patients demonstrated higher levels of OCD severity and increased symptoms on all OCD dimensions along with increased ADHD symptoms and higher rates of bipolar disorder. CONCLUSIONS: It is suggested that 20 years is the recommended cut-off age for the determination of early versus late age of onset in OCD. Early age of onset is associated with a generally graver OCD clinical picture and increased ADHD symptoms and bipolar disorder rates, which may be related to greater functional implications of the disorder. We propose that age of onset could be an important marker for the subtyping of OCD.

Longitudinal associations between post-traumatic distress and depressive symptoms following a traumatic event: a test of three models.

BACKGROUND: Symptoms of post-traumatic stress disorder (PTSD) and depression are highly co-morbid following a traumatic event. Nevertheless, decisive evidence regarding the direction of the relationship between these clinical entities is missing. METHOD: The aim of the present study was to examine the nature of this relationship by comparing a synchronous change model (PTSD and depression are time synchronous, possibly stemming from a third common factor) with a demoralization model (i.e. PTSD symptoms causing depression) and a depressogenic model (i.e. depressive symptoms causing PTSD symptoms). Israeli adult victims of single-event traumas (n=156) were assessed on measures of PTSD and depression at 2, 4 and 12 weeks post-event. RESULTS: A cross-lagged structural equation modeling (SEM) analysis provided results consistent with the synchronous change model and the depressogenic model. CONCLUSIONS: Depressive symptoms may play an important role in the development of post-traumatic symptoms.