Pre-pandemic Executive Function Protects Against Pandemic Anxiety in Children with and Without Autism Spectrum Disorder.

The COVID-19 pandemic may have exacerbated depression, anxiety, and executive function (EF) difficulties in children with autism spectrum disorder (ASD). EF skills have been positively associated with mental health outcomes. Here, we probed the psychosocial impacts of pandemic responses in children with and without ASD by relating pre-pandemic EF assessments with anxiety and depression symptoms several months into the pandemic. We found that pre-pandemic inhibition and shifting difficulties, measured by the Behavior Rating Inventory of Executive Function, predicted higher risk of anxiety symptoms. These findings are critical for promoting community recovery and maximizing clinical preparedness to support children at increased risk for adverse psychosocial outcomes.

Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan.

The neural mechanisms contributing to flexible cognition and behavior and how they change with development and aging are incompletely understood. The current study explored intrinsic brain dynamics across the lifespan using resting-state fMRI data (n = 601, 6-85 years) and examined the interactions between age and brain dynamics among three neurocognitive networks (midcingulo-insular network, M-CIN; medial frontoparietal network, M-FPN; and lateral frontoparietal network, L-FPN) in relation to behavioral measures of cognitive flexibility. Hierarchical multiple regression analysis revealed brain dynamics among a brain state characterized by co-activation of the L-FPN and M-FPN, and brain state transitions, moderated the relationship between quadratic effects of age and cognitive flexibility as measured by scores on the Delis-Kaplan Executive Function System (D-KEFS) test. Furthermore, simple slope analyses of significant interactions revealed children and older adults were more likely to exhibit brain dynamic patterns associated with poorer cognitive flexibility compared with younger adults. Our findings link changes in cognitive flexibility observed with age with the underlying brain dynamics supporting these changes. Preventative and intervention measures should prioritize targeting these networks with cognitive flexibility training to promote optimal outcomes across the lifespan.

Altered patterns of brain dynamics linked with body mass index in youth with autism.

Children with autism spectrum disorder (ASD) have higher rates of overweight and obesity (OWOB) compared with typically developing (TD) children. Brain functional connectivity differences have been shown in both ASD and OWOB. However, only one study to date has examined ASD and OWOB concurrently, so little is known regarding the neural mechanisms associated with the higher prevalence of OWOB and its behavioral impacts in ASD. We investigated co-activation patterns (CAPs) of brain regions identified by independent component analysis in 129 children and adolescents between 6 and 18 years of age (n = 68 ASD). We examined the interaction between body mass index (BMI) and diagnosis in predicting dynamic brain metrics (dwell time, DT; frequency of occurrence, and transitions between states) as well as dimensional brain-behavior relationships. The relationship between BMI and brain dynamics was moderated by diagnosis (ASD, TD), particularly among the frequency of CAP 4, characterized by co-activation of lateral frontoparietal, temporal, and frontal networks. This pattern was negatively associated with parent-reported inhibition skills. Children with ASD had shorter CAP 1, characterized by co-activation of the subcortical, temporal, sensorimotor, and frontal networks, and CAP 4 DTs compared with TD children. CAP 1 DT was negatively associated with cognitive flexibility, inhibition, social functioning, and BMI. Cognitive flexibility moderated the relationship between BMI and brain dynamics in the visual network. Our findings provide novel evidence of neural mechanisms associated with OWOB in children with ASD. Further, poorer cognitive flexibility may result in increased vulnerability for children with ASD and co-occurring OWOB. LAY SUMMARY: Obesity is a societal epidemic and is common in autism, however, little is known about the neural mechanisms associated with the higher rates of obesity in autism. Here, we find unique patterns of brain dynamics associated with obesity in autism that were not observed in typically developing children. Further, the relationship between body mass index and brain dynamics depended on cognitive flexibility. These findings suggest that individuals with autism may be more vulnerable to the effects of obesity on brain function. Autism Res 2021, 14: 873-886. © 2021 International Society for Autism Research, Wiley Periodicals LLC.

Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals.

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

Brain Activity Associated With Regulating Food Cravings Predicts Changes in Self-Reported Food Craving and Consumption Over Time.

Neural patterns associated with viewing energy-dense foods can predict changes in eating-related outcomes. However, most research on this topic is limited to one follow-up time point, and single outcome measures. The present study seeks to add to that literature by employing a more refined assessment of food craving and consumption outcomes along with a more detailed neurobiological model of behavior change over several time points. Here, a community sample of 88 individuals (age: M = 39.17, SD = 3.47; baseline BMI: M = 31.5, SD = 3.9, range 24-42) with higher body mass index (BMI) performed a food craving reactivity and regulation task while undergoing functional magnetic resonance imaging. At that time-and 1, 3, and 6 months later-participants reported craving for and consumption of healthy and unhealthy foods via the Food Craving Inventory (FCI) and ASA24 (N at 6 months = 52-55 depending on the measure). A priori hypotheses that brain activity associated with both viewing and regulating personally desired unhealthy, energy-dense foods would be associated with self-reported craving for and consumption of unhealthy foods at baseline were not supported by the data. Instead, regression models controlling for age, sex, and BMI demonstrated that brain activity across several regions measured while individuals were regulating their desires for unhealthy food was associated with the self-reported craving for and consumption of healthy food. The hypothesis that vmPFC activity would predict patterns of healthier eating was also not supported. Instead, linear mixed models controlling for baseline age and sex, as well as changes in BMI, revealed that more regulation-related activity in the dlPFC, dACC, IFG, and vmPFC at baseline predicted decreases in the craving for and consumption of healthy foods over the course of 6 months.

Evoked and intrinsic brain network dynamics in children with autism spectrum disorder.

OBJECTIVE: Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors. METHOD: 17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task. Metrics indexing brain dynamics were generated from dynamic CAPs computed across three major large-scale brain networks: midcingulo-insular (M-CIN), medial frontoparietal (M-FPN), and lateral frontoparietal (L-FPN). RESULTS: Five time-varying CAPs representing dynamic co-activations among network nodes were identified across rest and task fMRI datasets. Significant Diagnosis × Condition interactions were observed for the dwell time of CAP 3, representing co-activation between nodes of the M-CIN and L-FPN, and the frequency of CAP 1, representing co-activation between nodes of the L-FPN. A significant brain-behavior association between dwell time of CAP 5, representing co-activation between nodes of the M-FPN, and social abilities was also observed across both groups of children. CONCLUSION: Analysis of brain co-activation patterns reveals altered dynamics among three core networks in children with ASD, particularly evident during later stages of an attention task. Dimensional analyses demonstrating relationships between M-FPN dwell time and social abilities suggest that metrics of brain dynamics may index individual differences in social cognition and behavior.

Neural Responses to a Putative Set-shifting Task in Children with Autism Spectrum Disorder.

While much progress has been made toward understanding the neurobiology of social and communication deficits associated with autism spectrum disorder (ASD), less is known regarding the neurobiological basis of restricted and repetitive behaviors (RRBs) central to the ASD diagnosis. Symptom severity for RRBs in ASD is associated with cognitive inflexibility. Thus, understanding the neural mechanisms underlying cognitive inflexibility in ASD is critical for tailoring therapies to treat this understudied yet pervasive symptom. Here we used a set-shifting paradigm adopted from the developmental cognitive neuroscience literature involving flexible switching between stimulus categories to examine task performance and neural responses in children with ASD. Behaviorally, we found little evidence for group differences in performance on the set-shifting task. Compared with typically developing children, children with ASD exhibited greater activation of the parahippocampal gyrus during performance on trials requiring switching. These findings suggest that children with ASD may need to recruit memory-based neural systems to a greater degree when learning to flexibly associate stimuli with responses. LAY SUMMARY: Children with autism often struggle to behave in a flexible way when faced with unexpected challenges. We examined brain responses during a task thought to involve flexible thinking and found that compared with typically developing children, those with autism relied more on brain areas involved in learning and memory to complete the task. This study helps us to understand what types of cognitive tasks are best suited for exploring the neural basis of cognitive flexibility in children with autism. Autism Res 2020, 13: 1501-1515. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Coactivation pattern analysis reveals altered salience network dynamics in children with autism spectrum disorder.

Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6-13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder.