The Relationship Between Resting State Network Connectivity and Individual Differences in Executive Functions.

The brain is organized into a number of large networks based on shared function, for example, high-level cognitive functions (frontoparietal network), attentional capabilities (dorsal and ventral attention networks), and internal mentation (default network). The correlations of these networks during resting-state fMRI scans varies across individuals and is an indicator of individual differences in ability. Prior work shows higher cognitive functioning (as measured by working memory and attention tasks) is associated with stronger negative correlations between frontoparietal/attention and default networks, suggesting that increased ability may depend upon the diverging activation of networks with contrasting function. However, these prior studies lack specificity with regard to the higher-level cognitive functions involved, particularly with regards to separable components of executive function (EF). Here we decompose EF into three factors from the unity/diversity model of EFs: Common EF, Shifting-specific EF, and Updating-specific EF, measuring each via factor scores derived from a battery of behavioral tasks completed by 250 adult participants (age 28) at the time of a resting-state scan. We found the hypothesized segregated pattern only for Shifting-specific EF. Specifically, after accounting for one's general EF ability (Common EF), individuals better able to fluidly switch between task sets have a stronger negative correlation between the ventral attention network and the default network. We also report non-predicted novel findings in that individuals with higher Shifting-specific abilities exhibited more positive connectivity between frontoparietal and visual networks, while those individuals with higher Common EF exhibited increased connectivity between sensory and default networks. Overall, these results reveal a new degree of specificity with regard to connectivity/EF relationships.

Communicating with Sensation Seekers: An fMRI Study of Neural Responses to Antidrug Public Service Announcements.

This study examined the neural basis of processing high- and low-message sensation value (MSV) antidrug public service announcements (PSAs) in high (HSS) and low sensation seekers (LSS) using fMRI. HSS more strongly engaged the salience network when processing PSAs (versus LSS), suggesting that high-MSV PSAs attracted their attention. HSS and LSS participants who engaged higher level cognitive processing regions reported that the PSAs were more convincing and believable and recalled the PSAs better immediately after testing. In contrast, HSS and LSS participants who strongly engaged visual attention regions for viewing PSAs reported lower personal relevance. These findings provide neurobiological evidence that high-MSV content is salient to HSS, a primary target group for antidrug messages, and additional cognitive processing is associated with higher perceived message effectiveness.

Predicting Cognitive Executive Functioning with Polygenic Risk Scores for Psychiatric Disorders.

Executive functions (EFs) have been proposed as an endophenotype for psychopathology because EF deficits are associated with most psychiatric disorders. To examine this hypothesis, we derived polygenic risk scores for autism, attention-deficit/hyperactive disorder (ADHD), bipolar disorder, major depression (MDD), and schizophrenia, using genome-wide data from the Psychiatric Genomics Consortium as discovery samples. We then examined the relationships between these polygenic risk scores and three separable EF components measured with a latent variable model. We also examined the relationship between genetic risk for ADHD and MDD and their respective symptom counts and lifetime diagnoses. We found no evidence for larger effect sizes for EFs as endophenotypes for psychiatric disorders. However, larger sample sizes will be important in examining this relationship further.

The changing landscape of functional brain networks for face processing in typical development.

Greater expertise for faces in adults than in children may be achieved by a dynamic interplay of functional segregation and integration of brain regions throughout development. The present study examined developmental changes in face network functional connectivity in children (5-12 years) and adults (18-43 years) during face-viewing using a graph-theory approach. A face-specific developmental change involved connectivity of the right occipital face area. During childhood, this node increased in strength and within-module clustering based on positive connectivity. These changes reflect an important role of the ROFA in segregation of function during childhood. In addition, strength and diversity of connections within a module that included primary visual areas (left and right calcarine) and limbic regions (left hippocampus and right inferior orbitofrontal cortex) increased from childhood to adulthood, reflecting increased visuo-limbic integration. This integration was pronounced for faces but also emerged for natural objects. Taken together, the primary face-specific developmental changes involved segregation of a posterior visual module during childhood, possibly implicated in early stage perceptual face processing, and greater integration of visuo-limbic connections from childhood to adulthood, which may reflect processing related to development of perceptual expertise for individuation of faces and other visually homogenous categories.