Inferring the Genetic Influences on Psychological Traits Using MRI Connectivity Predictive Models: Demonstration with Cognition.

Introduction: Genetic correlations between brain and behavioral phenotypes in analyses from major genetic consortia have been weak and mostly nonsignificant. fMRI models of systems-level brain patterns may help improve our ability to link genes, brains, and behavior by identifying reliable and reproducible endophenotypes. Work using connectivity-based predictive modeling has generated brain-based proxies of behavioral and neuropsychological variables. If such models capture activity in inherited brain systems, they may offer a more powerful link between genes and behavior. Method: As a proof of concept, we develop models predicting intelligence (IQ) based on fMRI connectivity and test their effectiveness as endophenotypes. We link brain and IQ in a model development dataset of N = 3,000 individuals and test the genetic correlations between brain models and measured IQ in a genetic validation sample of N = 13,092 individuals from the UK Biobank. We compare an additive connectivity-based model to multivariate LASSO and ridge models phenotypically and genetically. We also compare these approaches to single "candidate" brain areas. Results: We found that predictive brain models were significantly phenotypically correlated with IQ and showed much stronger correlations than individual edges. Further, brain models were more heritable (h2 = 0.155-0.181) than single brain regions (h2 = 0.038-0.118) and captured about half of the genetic variance in IQ (rG = 0.422-0.576), while rGs with single brain measures were smaller and nonsignificant. For the different approaches, LASSO and ridge were similarly predictive, with slightly weaker performance of the additive model. LASSO model weights were highly theoretically interpretable and replicated known brain IQ associations. Finally, functional connectivity models trained in midlife showed genetic correlations with early life correlates of IQ, suggesting some stability in the prediction of fMRI models. Conclusion: Multisystem predictive models hold promise as imaging endophenotypes that offer complex and theoretically relevant conclusions for future imaging genetics research.

Genome-wide Association Study Shows That Executive Functioning Is Influenced by GABAergic Processes and Is a Neurocognitive Genetic Correlate of Psychiatric Disorders.

BACKGROUND: Deficits in executive functions (EFs), cognitive processes that control goal-directed behaviors, are associated with psychopathology and neurologic disorders. Little is known about the molecular bases of individual differences in EFs. Prior candidate gene studies have been underpowered in their search for dopaminergic processes involved in cognitive functioning, and existing genome-wide association studies of EFs used small sample sizes and/or focused on individual tasks that are imprecise measures of EFs. METHODS: We conducted a genome-wide association study of a common EF (cEF) factor score based on multiple tasks in the UK Biobank (n = 427,037 individuals of European descent). RESULTS: We found 129 independent genome-wide significant lead variants in 112 distinct loci. cEF was associated with fast synaptic transmission processes (synaptic, potassium channel, and GABA [gamma-aminobutyric acid] pathways) in gene-based analyses. cEF was genetically correlated with measures of intelligence (IQ) and cognitive processing speed, but cEF and IQ showed differential genetic associations with psychiatric disorders and educational attainment. CONCLUSIONS: Results suggest that cEF is a genetically distinct cognitive construct that is particularly relevant to understanding the genetic variance in psychiatric disorders.

The Angular Gyrus as a Hub for Modulation of Language-related Cortex by Distinct Prefrontal Executive Control Regions.

It has become clear in recent years that reading, while relying on domain-specific language processing regions, also involves regions that implement executive processes more broadly. Such executive control is generally considered to be implemented by prefrontal regions, which exert control via connectivity that allows them to modulate processing in target brain regions. The present study examined whether three previously identified and distinct executive control regions in the pFC [Wang, K., Banich, M. T., Reineberg, A. E., Leopold, D. R., Willcutt, E. G., Cutting, L. E., et al. Left posterior prefrontal regions support domain-general executive processes needed for both reading and math. Journal of Neuropsychology, 14, 467-495, 2020] show similar patterns of functional connectivity (FC) during a reading comprehension task as compared with a symbol identification condition. Our FC results in a sample of adolescents (n = 120) suggest all three regions commonly show associations with activity in "classic" left hemisphere reading areas, including the angular and supramarginal gyri, yet each exhibits differential connectivity as well. In particular, precentral regions show differential FC to parietal portions of the dorsal language stream, the inferior frontal junction shows differential FC to middle temporal regions of the right hemisphere and other regions involved in semantic processing, and portions of the inferior frontal gyrus show differential FC to an extensive set of right hemisphere prefrontal regions. These results suggest that prefrontal control over language-related regions occurs in a coordinated yet discrete manner.

Context-specific activations are a hallmark of the neural basis of individual differences in general executive function.

Common executive functioning (cEF) is a domain-general factor that captures shared variance in performance across diverse executive function tasks. To investigate the neural mechanisms of individual differences in cEF (e.g., goal maintenance, biasing), we conducted the largest fMRI study of multiple executive tasks to date (N = 546). Group average activation during response inhibition (antisaccade task), working memory updating (keep track task), and mental set shifting (number-letter switch task) overlapped in classic cognitive control regions. However, there were no areas across tasks that were consistently correlated with individual differences in cEF ability. Although similar brain areas are recruited when completing different executive function tasks, activation levels of those areas are not consistently associated with better performance. This pattern is inconsistent with a simple model in which higher cEF is associated with greater or less activation of a set of control regions across different task contexts; however, it is potentially consistent with a model in which individual differences in cEF primarily depend on activation of domain-specific targets of executive function. Brain features that explain commonalities in executive function performance across tasks remain to be discovered.

Topographical functional correlates of interindividual differences in executive functions in young healthy twins.

Executive functions (EF) are a set of higher-order cognitive abilities that enable goal-directed behavior by controlling lower-level operations. In the brain, those functions have been traditionally associated with activity in the Frontoparietal Network, but recent neuroimaging studies have challenged this view in favor of more widespread cortical involvement. In the present study, we aimed to explore whether the network that serves as critical hubs at rest, which we term network reliance, differentiate individuals as a function of their level of EF. Furthermore, we investigated whether such differences are driven by genetic as compared to environmental factors. For this purpose, resting-state functional magnetic resonance imaging data and the behavioral testing of 453 twins from the Colorado Longitudinal Twins Study were analyzed. Separate indices of EF performance were obtained according to a bifactor unity/diversity model, distinguishing between three independent components representing: Common EF, Shifting-specific and Updating-specific abilities. Through an approach of step-wise in silico network lesioning of the individual functional connectome, we show that interindividual differences in EF are associated with different dependencies on neural networks at rest. Furthermore, these patterns show evidence of mild heritability. Such findings add knowledge to the understanding of brain states at rest and their connection with human behavior, and how they might be shaped by genetic influences.

Heritability of brain resilience to perturbation in humans.

Resilience is the capacity of complex systems to persist in the face of external perturbations and retain their functional properties and performance. In the present study, we investigated how individual variations in brain resilience, which might influence response to stress, aging and disease, are influenced by genetics and/or the environment, with potential implications for the implementation of resilience-boosting interventions. Resilience estimates were derived from in silico lesioning of either brain regions or functional connections constituting the connectome of healthy individuals belonging to two different large and unique datasets of twins, specifically: 463 individual twins from the Human Connectome Project and 453 individual twins from the Colorado Longitudinal Twin Study. As has been reported previously, moderate heritability was found for several topological indexes of brain efficiency and modularity. Importantly, evidence of heritability was found for resilience measures based on removal of brain connections rather than specific single regions, suggesting that genetic influences on resilience are preferentially directed toward region-to-region communication rather than local brain activity. Specifically, the strongest genetic influence was observed for moderately weak, long-range connections between a specific subset of functional brain networks: the Default Mode, Visual and Sensorimotor networks. These findings may help identify a link between brain resilience and network-level alterations observed in neurological and psychiatric diseases, as well as inform future studies investigating brain shielding interventions against physiological and pathological perturbations.

Playing-Related Musculoskeletal Disorders, Risk Factors, and Treatment Efficacy in a Large Sample of Oboists.

OBJECTIVES: During their lifetimes, a majority of musicians experience playing-related musculoskeletal disorders (PRMD). PRMD prevalence is tied to instrument choice, yet most studies examine heterogeneous groups of musicians, leaving some high-risk groups such as oboists understudied. This paper aims to (1) ascertain the prevalence and nature of PRMDs in oboists, (2) determine relevant risk factors, and (3) evaluate the efficacy of treatment methods in preventing and remedying injuries in oboe players. METHODS: A 10-question online questionnaire on PRMDs and their treatments was completed by 223 oboists. PRMDs were compared across gender, weekly playing hours, career level, age, and years of playing experience. RESULTS: Of all respondents, 74.9% (167/223) reported having had at least one PRMD in their lifetime. A majority of these injuries (61.9% of all respondents) were of moderate to extreme severity (5 or higher on a scale of 1 to 10). Females (mean = 5.88) reported significantly more severe injuries than males. No significant effects of career level (i.e., professional vs. student vs. amateur), age, or years of playing experience were observed. We found significant non-linear relationships between weekly playing hours and PRMD prevalence and severity. Injuries were most commonly on the right side of the body, with the right thumb, wrist, hand, and forearm being most affected in frequency and severity. Of those injuries for which recovery information was provided, only 26.1% of injuries were "completely recovered." The perceived effectiveness of a few treatments (physical therapy, rest, stretching, occupational therapy, massage) tended to be ranked more highly than others. CONCLUSION: The oboists in this study experienced high rates of PRMD, particularly in the right upper extremities. Females and those playing 7-9 and 16-18 h per week reported a significantly higher severity of injuries than other groups.

Left posterior prefrontal regions support domain-general executive processes needed for both reading and math.

Substantial evidence has suggested that reading and math are supported by executive processes (EP). However, to date little is known about which portion of the neural system underpinning domain-general executive skills works to support reading and math. In this study, we aimed to answer this question using fMRI via two complementary approaches. First, imaging data were acquired whilst a sample of 231 adolescents performed each of three separate tasks designed to assess reading comprehension, numerical magnitude estimation, and EP in working memory (WM), respectively. With careful task designs and conjunction analyses, we were able to isolate cross-domain brain activity specifically related to EP, as opposed to lower-level domain-general processes (e.g., visual processing). Second, the meta-analytic tool Neurosynth was used to independently identify brain regions involved reading, math, and EP. Using a combination of forward and reverse statistical inference and conjunction analyses, we again isolated brain regions specifically supporting domain-general EP. Results from both approaches yielded overlapping activation for reading, math, and EP in the left ventrolateral prefrontal cortex, left inferior frontal junction, and left precentral gyrus. This pattern suggests that posterior regions of the prefrontal cortex, rather than more central regions such as mid-DLPFC, play a leading role in supporting domain-general EP utilized by both reading and math.

Genetic and Environmental Influence on the Human Functional Connectome.

Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. We analyzed resting-state functional magnetic resonance imaging data from two adult twin samples (Nos = 446 and 371) to quantify genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35 000 functional connections). Nonshared environmental influence was high across the whole connectome. Approximately 14-22% of connections had nominally significant genetic influence in each sample, 4.6% were significant in both samples, and 1-2% had heritability estimates greater than 30%. Evidence of shared environmental influence was weak. Genetic influences on connections were distinct from genetic influences on a global summary measure of the connectome, network-based estimates of connectivity, and movement during the resting-state scan, as revealed by a novel connectome-wide bivariate genetic modeling procedure. The brain's genetic organization is diverse and not as one would expect based solely on structure evident in nongenetically informative data or lower resolution data. As follow-up, we make novel classifications of functional connections and examine highly localized connections with particularly strong genetic influence. This high-resolution genetic taxonomy of brain connectivity will be useful in understanding genetic influences on brain disorders.

Whole-cortex mapping of common genetic influences on depression and a social deficits dimension.

Social processes are associated with depression, particularly understanding and responding to others, deficits in which can manifest as callousness/unemotionality (CU). Thus, CU may reflect some of the genetic risk to depression. Further, this vulnerability likely reflects the neurological substrates of depression, presenting biomarkers to capture genetic vulnerability of depression severity. However, heritability varies within brain regions, so a high-resolution genetic perspective is needed. We developed a toolbox that maps genetic and environmental associations between brain and behavior at high resolution. We used this toolbox to estimate brain areas that are genetically associated with both depressive symptoms and CU in a sample of 258 same-sex twin pairs from the Colorado Longitudinal Twin Study (LTS). We then overlapped the two maps to generate coordinates that allow for tests of downstream effects of genes influencing our clusters. Genetic variance influencing cortical thickness in the right dorsal lateral prefrontal cortex (DLFPC) sulci and gyri, ventral posterior cingulate cortex (PCC), pre-somatic motor cortex (PreSMA), medial precuneus, left occipital-temporal junction (OTJ), parietal-temporal junction (PTJ), ventral somatosensory cortex (vSMA), and medial and lateral precuneus were genetically associated with both depression and CU. Split-half replication found support for both DLPFC clusters. Meta-analytic term search identified "theory of mind", "inhibit", and "pain" as likely functions. Gene and transcript mapping/enrichment analyses implicated calcium channels. CU reflects genetic vulnerability to depression that likely involves executive and social functioning in a distributed process across the cortex. This approach works to unify neuroimaging, neuroinformatics, and genetics to discover pathways to psychiatric vulnerability.

Characterizing and decomposing the neural correlates of individual differences in reading ability among adolescents with task-based fMRI.

To better characterize the neural correlates of the full spectrum of reading ability, this fMRI study examined how variations in reading ability correlate with task-based brain activity during reading among a large community sample of adolescents (N = 234). In addition, complimentary approaches taking advantage of empirical as well as independent meta-analytic information were employed to isolate neural substrates of domain-general executive processes that are predictive of reading ability. Age-related differences in brain activity were also examined. Better reading was associated with increased activation in left anterior and inferior temporal regions and parts of orbitofrontal cortex, along with reduced activation in the thalamus and left frontal eye field (FEF). Converging evidence suggests that FEF activity corresponds to executive processes during reading. In contrast, activity in temporal regions is likely to reflect cognitive processes specific to reading. Older adolescents also demonstrated increased activation in an orbitofrontal region that overlaps with the aforementioned age-independent, reading-related regions, along with reduced activity in parietal and occipital regions. These results suggest that comparedto poor readers, proficient readers benefit from efficient reading-specific processes and require less executive effort, implemented via the FEF, during a reading comprehension task.

Adjustments in Torque Steadiness During Fatiguing Contractions Are Inversely Correlated With IQ in Persons With Multiple Sclerosis.

Fatigue is one of the most debilitating symptoms of multiple sclerosis (MS), and the underlying mechanisms are poorly understood. When exposed to a physical or cognitive challenge, individuals with MS tend to exhibit greater declines in task performance (performance fatigability) and increased levels of self-reported fatigue (perceived fatigability), but these effects may be attenuated by greater intellectual capacity. The purpose of our study was to examine the influence of intelligence on fatigability in persons with MS. We hypothesized that greater intellectual capacity confers some protection against heightened levels of fatigue and fatigability associated with MS. Twelve adults with relapsing-remitting MS were compared with 12 control (CO) subjects who were matched for age, sex, and premorbid intellectual capacity. Performance fatigability was measured as the decline in maximal voluntary contraction (MVC) torque after 60 isometric contractions (10 s contraction at 25% MVC, 5 s rest) performed with the knee extensor muscles. Perceived fatigability was assessed with the modified fatigue impact scale (MFIS) questionnaire (trait fatigability) and the Borg rating of perceived exertion (RPE, state fatigability). Persons with MS reported greater MFIS scores (MS: 43 ± 14; CO: 11 ± 8, P ≤ 0.001). Initial MVC torque for the knee extensors did not differ between the groups (MS: 112 ± 38 N⋅m; CO: 107 ± 44 N⋅m) and the decline (performance fatigability) was similar for both groups (MS: -16 ± 19 N⋅m; CO: -13 ± 16 N⋅m). RPE increased during the fatiguing contraction for both groups (P < 0.001) but was significantly greater in magnitude (main effect for group, P = 0.03) and increased more for the MS group (group × time interaction, P = 0.05). Torque steadiness declined during the fatiguing contractions (main effect for time, P = 0.05) and was less steady for the MS group (main effect for group, P = 0.02). Performance and full-4 IQ was correlated with the decline in torque steadiness for the MS group (r = -0.63, P < 0.05; r = -0.64, P < 0.05). Intellectual capacity was not associated with fatigability in persons with MS but was associated with adjustments in muscle activation during the fatiguing contractions.

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.

Functional connectivity at rest is sensitive to individual differences in executive function: A network analysis.

Graph theory provides a means to understand the nature of network characteristics and connectivity between specific brain regions. Here it was used to investigate whether the network characteristics of the brain at rest are associated with three dimensions thought to underlie individual differences in executive function (EF)-common EF, shifting-specific EF, and updating-specific EF (Miyake and Friedman [2012]). To do so, both an a priori analysis focused mainly on select frontoparietal regions previously linked to individual differences in EF as well as a whole-brain analysis were performed. The findings indicated that individual differences in each of the three dimensions of EF were associated with specific patterns of resting-state connectivity both in a priori and other brain regions. More specifically, higher common EF was associated with greater integrative (i.e., more hublike) connectivity of cuneus and supplementary motor area but less integrative function of lateral frontal nodes and left temporal lobe nodes. Higher shifting-specific EF was associated with more hublike motor-related nodes and cingulo-opercular nodes. Higher updating-specific EF was associated with less hublike lateral and medial frontoparietal nodes. In general, these results suggested that higher ability in each of these three dimensions of EF was not solely characterized by the connectivity characteristics of frontoparietal regions. The pattern was complicated in that higher EF was associated with the connectivity profile of nodes outside of the traditional frontoparietal network, as well as with less hublike or centrality characteristics of some nodes within the frontoparietal network. Hum Brain Mapp 37:2959-2975, 2016. © 2016 Wiley Periodicals, Inc.

Resting-state networks predict individual differences in common and specific aspects of executive function.

The goal of the present study was to examine relationships between individual differences in resting state functional connectivity as ascertained by fMRI (rs-fcMRI) and performance on tasks of executive function (EF), broadly defined as the ability to regulate thoughts and actions. Unlike most previous research that focused on the relationship between rs-fcMRI and a single behavioral measure of EF, in the current study we examined the relationship of rs-fcMRI with individual differences in subcomponents of EF. Ninety-one adults completed a resting state fMRI scan and three separate EF tasks outside the magnet: inhibition of prepotent responses, task set shifting, and working memory updating. From these three measures, we derived estimates of common aspects of EF, as well as abilities specific to working memory updating and task shifting. Using Independent Components Analysis (ICA), we identified across the group of participants several networks of regions (Resting State Networks, RSNs) with temporally correlated time courses. We then used dual regression to explore how these RSNs covaried with individual differences in EF. Dual regression revealed that increased higher common EF was associated with connectivity of a) frontal pole with an attentional RSN, and b) Crus I and II of the cerebellum with the right frontoparietal RSN. Moreover, higher shifting-specific abilities were associated with increased connectivity of angular gyrus with a ventral attention RSN. The results of the current study suggest that the organization of the brain at rest may have important implications for individual differences in EF, and that individuals higher in EF may have expanded resting state networks as compared to individuals with lower EF.

A penny for your thoughts: dimensions of self-generated thought content and relationships with individual differences in emotional wellbeing.

A core aspect of human cognition involves overcoming the constraints of the present environment by mentally simulating another time, place, or perspective. Although these self-generated processes confer many benefits, they can come at an important cost, and this cost is greater for some individuals than for others. Here we explore the possibility that the costs and benefits of self-generated thought depend, in part, upon its phenomenological content. To test these hypotheses, we first developed a novel thought sampling paradigm in which a large sample of young adults recalled several recurring thoughts and rated each thought on multiple content variables (i.e., valence, specificity, self-relevance, etc.). Next, we examined multi-level relationships among these content variables and used a hierarchical clustering approach to partition self-generated thought into distinct dimensions. Finally, we investigated whether these content dimensions predicted individual differences in the costs and benefits of the experience, assessed with questionnaires measuring emotional health and wellbeing. Individuals who characterized their thoughts as more negative and more personally significant scored higher on constructs associated with Depression and Trait Negative Affect, whereas those who characterized their thoughts as less specific scored higher on constructs linked to Rumination. In contrast, individuals who characterized their thoughts as more positive, less personally significant, and more specific scored higher on constructs linked to improved wellbeing (Mindfulness). Collectively, these findings suggest that the content of people's inner thoughts can (1) be productively examined, (2) be distilled into several major dimensions, and (3) account for a large portion of variability in their functional outcomes.

Eye movements during mindless reading.

Mindless reading occurs when the eyes continue moving across the page even though the mind is thinking about something unrelated to the text. Despite how commonly it occurs, very little is known about mindless reading. The present experiment examined eye movements during mindless reading. Comparisons of fixation-duration measures collected during intervals of normal reading and intervals of mindless reading indicate that fixations during the latter were longer and less affected by lexical and linguistic variables than fixations during the former. Also, eye movements immediately preceding self-caught mind wandering were especially erratic. These results suggest that the cognitive processes that guide eye movements during normal reading are not engaged during mindless reading. We discuss the implications of these findings for theories of eye movement control in reading, for the distinction between experiential awareness and meta-awareness, and for reading comprehension.