Prefrontal Responses during Proactive and Reactive Inhibition Are Differentially Impacted by Stress in Anorexia and Bulimia Nervosa.

Binge eating is a distressing, transdiagnostic eating disorder symptom associated with impulsivity, particularly in negative mood states. Neuroimaging studies of bulimia nervosa (BN) report reduced activity in frontostriatal regions implicated in self-regulatory control, and an influential theory posits that binge eating results from self-regulation failures under stress. However, there is no direct evidence that psychological stress impairs self-regulation in binge-eating disorders, or that any such self-regulatory deficits generalize to binge eating in underweight individuals (i.e., anorexia nervosa bingeing/purging subtype; AN-BP). We therefore determined the effect of acute stress on inhibitory control in 85 women (BN, 33 women; AN-BP, 22 women; 30 control participants). Participants underwent repeated functional MRI scanning during performance of the Stop-signal anticipation task, a validated measure of proactive (i.e., anticipation of stopping) and reactive (outright stopping) inhibition. Neural and behavioral responses to induced stress and a control task were evaluated on 2 consecutive days. Women with BN had reduced proactive inhibition, while prefrontal responses were increased in both AN-BP and BN. Reactive inhibition was neurally and behaviorally intact in both diagnostic groups. Both AN-BP and BN groups showed distinct stress-induced changes in inferior and superior frontal activity during both proactive and reactive inhibition. However, task performance was unaffected by stress. These results offer novel evidence of reduced proactive inhibition in BN, yet inhibitory control deficits did not generalize to AN-BP. Our findings identify intriguing alterations of stress responses and inhibitory function associated with binge eating, but they counsel against stress-induced failures of inhibitory control as a comprehensive explanation for loss-of-control eating.SIGNIFICANCE STATEMENT Binge eating is a common psychiatric syndrome that feels uncontrollable to the sufferer. Theoretically, it has been related to reduced self-regulation under stress, but there remains no direct evidence for this link in binge-eating disorders. Here, we examined how experimentally induced stress affected response inhibition in control participants and women with anorexia nervosa and bulimia nervosa. Participants underwent repeated brain scanning under stressful and neutral conditions. Although patient groups had intact action cancellation, the slowing of motor responses was impaired in bulimia nervosa, even when the likelihood of having to stop increased. Stress altered brain responses for both forms of inhibition in both groups, yet performance remained unimpaired. These findings counsel against a simple model of stress-induced disinhibition as an adequate explanation for binge eating.

Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank.

BACKGROUND: Grip strength is a widely used and well-validated measure of overall health that is increasingly understood to index risk for psychiatric illness and neurodegeneration in older adults. However, existing work has not examined how grip strength relates to a comprehensive set of mental health outcomes, which can detect early signs of cognitive decline. Furthermore, whether brain structure mediates associations between grip strength and cognition remains unknown. METHODS: Based on cross-sectional and longitudinal data from over 40,000 participants in the UK Biobank, this study investigated the behavioral and neural correlates of handgrip strength using a linear mixed effect model and mediation analysis. RESULTS: In cross-sectional analysis, we found that greater grip strength was associated with better cognitive functioning, higher life satisfaction, greater subjective well-being, and reduced depression and anxiety symptoms while controlling for numerous demographic, anthropometric, and socioeconomic confounders. Further, grip strength of females showed stronger associations with most behavioral outcomes than males. In longitudinal analysis, baseline grip strength was related to cognitive performance at ~9 years follow-up, while the reverse effect was much weaker. Further, baseline neuroticism, health, and financial satisfaction were longitudinally associated with subsequent grip strength. The results revealed widespread associations between stronger grip strength and increased grey matter volume, especially in subcortical regions and temporal cortices. Moreover, grey matter volume of these regions also correlated with better mental health and considerably mediated their relationship with grip strength. CONCLUSIONS: Overall, using the largest population-scale neuroimaging dataset currently available, our findings provide the most well-powered characterization of interplay between grip strength, mental health, and brain structure, which may facilitate the discovery of possible interventions to mitigate cognitive decline during aging.

On what motivates us: a detailed review of intrinsic v. extrinsic motivation.

Motivational processes underlie behaviors that enrich the human experience, and impairments in motivation are commonly observed in psychiatric illness. While motivated behavior is often examined with respect to extrinsic reinforcers, not all actions are driven by reactions to external stimuli; some are driven by 'intrinsic' motivation. Intrinsically motivated behaviors are computationally similar to extrinsically motivated behaviors, in that they strive to maximize reward value and minimize punishment. However, our understanding of the neurocognitive mechanisms that underlie intrinsically motivated behavior remains limited. Dysfunction in intrinsic motivation represents an important trans-diagnostic facet of psychiatric symptomology, but due to a lack of clear consensus, the contribution of intrinsic motivation to psychopathology remains poorly understood. This review aims to provide an overview of the conceptualization, measurement, and neurobiology of intrinsic motivation, providing a framework for understanding its potential contributions to psychopathology and its treatment. Distinctions between intrinsic and extrinsic motivation are discussed, including divergence in the types of associated rewards or outcomes that drive behavioral action and choice. A useful framework for understanding intrinsic motivation, and thus separating it from extrinsic motivation, is developed and suggestions for optimization of paradigms to measure intrinsic motivation are proposed.

Dissociable hormonal profiles for psychopathology and stress in anorexia and bulimia nervosa.

BACKGROUND: Anorexia nervosa (AN) and bulimia nervosa (BN) are complex psychiatric conditions, in which both psychological and metabolic factors have been implicated. Critically, the experience of stress can precipitate loss-of-control eating in both conditions, suggesting an interplay between mental state and metabolic signaling. However, associations between psychological states, symptoms and metabolic processes in AN and BN have not been examined. METHODS: Eighty-five women (n = 22 AN binge/purge subtype, n = 33 BN, n = 30 controls) underwent remote salivary cortisol sampling and a 2-day, inpatient study session to examine the effect of stress on cortisol, gut hormones [acyl-ghrelin, peptide tyrosine tyrosine (PYY) and glucagon-like peptide-1] and food consumption. Participants were randomized to either an acute stress induction or control task on each day, and plasma hormones were serially measured before a naturalistic, ad libitum meal. RESULTS: Cortisol-awakening response was augmented in AN but not in BN relative to controls, with body mass index explaining the most variance in post-awakening cortisol (36%). Acute stress increased acyl-ghrelin and PYY in AN compared to controls; however, stress did not alter gut hormone profiles in BN. Instead, a group-by-stress interaction showed nominally reduced cortisol reactivity in BN, but not in AN, compared to controls. Ad libitum consumption was lower in both patient groups and unaffected by stress. CONCLUSIONS: Findings extend previous reports of metabolic dysfunction in binge-eating disorders, identifying unique associations across disorders and under stress. Moreover, we observed disrupted homeostatic signaling in AN following psychological stress, which may explain, in part, the maintenance of dysregulated eating in this serious illness.

Sugar addiction: the state of the science.

PURPOSE: As obesity rates continue to climb, the notion that overconsumption reflects an underlying 'food addiction' (FA) has become increasingly influential. An increasingly popular theory is that sugar acts as an addictive agent, eliciting neurobiological changes similar to those seen in drug addiction. In this paper, we review the evidence in support of sugar addiction. METHODS: We reviewed the literature on food and sugar addiction and considered the evidence suggesting the addictiveness of highly processed foods, particularly those with high sugar content. We then examined the addictive potential of sugar by contrasting evidence from the animal and human neuroscience literature on drug and sugar addiction. RESULTS: We find little evidence to support sugar addiction in humans, and findings from the animal literature suggest that addiction-like behaviours, such as bingeing, occur only in the context of intermittent access to sugar. These behaviours likely arise from intermittent access to sweet tasting or highly palatable foods, not the neurochemical effects of sugar. CONCLUSION: Given the lack of evidence supporting it, we argue against a premature incorporation of sugar addiction into the scientific literature and public policy recommendations.

Sociodemographic correlates of parent and youth-reported eating disorder symptoms in the Adolescent Brain Cognitive Development Study.

Purpose: Eating Disorders (EDs) often start in adolescence, though ED-related concerns in diverse youth samples remain understudied. We leveraged data from the Adolescent Brain Cognitive Development (ABCD) Study to identify the prevalence of parent- and youth-reported ED symptoms and their sociodemographic characteristics. Methods: Data were drawn from baseline (ages 9-11 years, n=11,868) and 2-year follow-up (ages 11-14 years; n=10,908) from the ABCD Study. A tetrachoric factor analysis summarized clusters of ED symptoms, which were compared between parent and youth reports and across sociodemographic variables. Results: Three factors emerged reflecting "weight distress", "weight control", and "binge eating" (prevalence range: 1.5-7.3%). Symptoms loaded onto similar factors between reporters. Rates of symptom endorsement were similar between sexes, with disproportionately higher endorsement rates for youth who self-identified as sexual minority, Hispanic, Black, or Mixed race participants, and those from a disadvantaged socioeconomic background, compared to the reference ABCD sample. Youth and parent reports at 2-year showed ~12% overlap. Conclusions: ED-related concerns among historically understudied racial and sexual minority groups call for greater attention to the detection and treatment of these symptoms in these groups. Applying a transdiagnostic approach to ED symptoms can inform effective detection and intervention efforts.

Power and reproducibility in the external validation of brain-phenotype predictions.

Brain-phenotype predictive models seek to identify reproducible and generalizable brain-phenotype associations. External validation, or the evaluation of a model in external datasets, is the gold standard in evaluating the generalizability of models in neuroimaging. Unlike typical studies, external validation involves two sample sizes: the training and the external sample sizes. Thus, traditional power calculations may not be appropriate. Here we ran over 900 million resampling-based simulations in functional and structural connectivity data to investigate the relationship between training sample size, external sample size, phenotype effect size, theoretical power and simulated power. Our analysis included a wide range of datasets: the Healthy Brain Network, the Adolescent Brain Cognitive Development Study, the Human Connectome Project (Development and Young Adult), the Philadelphia Neurodevelopmental Cohort, the Queensland Twin Adolescent Brain Project, and the Chinese Human Connectome Project; and phenotypes: age, body mass index, matrix reasoning, working memory, attention problems, anxiety/depression symptoms and relational processing. High effect size predictions achieved adequate power with training and external sample sizes of a few hundred individuals, whereas low and medium effect size predictions required hundreds to thousands of training and external samples. In addition, most previous external validation studies used sample sizes prone to low power, and theoretical power curves should be adjusted for the training sample size. Furthermore, model performance in internal validation often informed subsequent external validation performance (Pearson's r difference <0.2), particularly for well-harmonized datasets. These results could help decide how to power future external validation studies.

Power and reproducibility in the external validation of brain-phenotype predictions.

Identifying reproducible and generalizable brain-phenotype associations is a central goal of neuroimaging. Consistent with this goal, prediction frameworks evaluate brain-phenotype models in unseen data. Most prediction studies train and evaluate a model in the same dataset. However, external validation, or the evaluation of a model in an external dataset, provides a better assessment of robustness and generalizability. Despite the promise of external validation and calls for its usage, the statistical power of such studies has yet to be investigated. In this work, we ran over 60 million simulations across several datasets, phenotypes, and sample sizes to better understand how the sizes of the training and external datasets affect statistical power. We found that prior external validation studies used sample sizes prone to low power, which may lead to false negatives and effect size inflation. Furthermore, increases in the external sample size led to increased simulated power directly following theoretical power curves, whereas changes in the training dataset size offset the simulated power curves. Finally, we compared the performance of a model within a dataset to the external performance. The within-dataset performance was typically within r=0.2 of the cross-dataset performance, which could help decide how to power future external validation studies. Overall, our results illustrate the importance of considering the sample sizes of both the training and external datasets when performing external validation.

Hypothalamic volume is associated with body mass index.

The hypothalamus is an important neuroendocrine hub for the control of appetite and satiety. In animal studies it has been established that hypothalamic lesioning or stimulation causes alteration to feeding behaviour and consequently body mass, and exposure to high calorie diets induces hypothalamic inflammation. These findings suggest that alterations in hypothalamic structure and function are both a cause and a consequence of changes to food intake. However, there is limited in vivo human data relating the hypothalamus to obesity or eating disorders, in part due to technical problems relating to its small size. Here, we used a novel automated segmentation algorithm to exploratorily investigate the relationship between hypothalamic volume, normalised to intracranial volume, and body mass index (BMI). The analysis was applied across four independent datasets comprising of young adults (total n = 1,351 participants) spanning a range of BMIs (13.3 - 47.8 kg/m2). We compared underweight (including individuals with anorexia nervosa), healthy weight, overweight and obese individuals in a series of complementary analyses. We report that overall hypothalamic volume is significantly larger in overweight and obese groups of young adults. This was also observed for a number of hypothalamic sub-regions. In the largest dataset (the HCP-Young Adult dataset (n = 1111)) there was a significant relationship between hypothalamic volume and BMI. We suggest that our findings of a positive relationship between hypothalamic volume and BMI is potentially consistent with hypothalamic inflammation as seen in animal models in response to high fat diet, although more research is needed to establish a causal relationship. Overall, we present novel, in vivo findings that link elevated BMI to altered hypothalamic structure. This has important implications for study of the neural mechanisms of obesity in humans.

Altered Brain Dynamics Across Bipolar Disorder and Schizophrenia During Rest and Task Switching Revealed by Overlapping Brain States.

BACKGROUND: Individuals with bipolar disorder (BD) and schizophrenia (SCZ) show aberrant brain dynamics (i.e., altered recruitment or traversal through different brain states over time). Existing investigations of brain dynamics typically assume that one dominant brain state characterizes each time point. However, as multiple brain states likely are engaged at any given moment, this approach can obscure alterations in less prominent but critical brain states. Here, we examined brain dynamics in BD and SCZ by implementing a novel framework that simultaneously assessed the engagement of multiple brain states. METHODS: Four recurring brain states were identified by applying nonlinear manifold learning and k-means clustering to the Human Connectome Project task-based functional magnetic resonance imaging data. We then assessed moment-to-moment state engagement in 2 independent samples of healthy control participants and patients with BD or SCZ using resting-state (N = 336) or task-based (N = 217) functional magnetic resonance imaging data. Relative state engagement and state engagement variability were extracted and compared across groups using multivariate analysis of covariance, controlling for site, medication, age, and sex. RESULTS: Our framework identified dynamic alterations in BD and SCZ, while a state discretization approach revealed no significant group differences. Participants with BD or SCZ showed reduced state engagement variability, but not relative state engagement, across multiple brain states during resting-state and task-based functional magnetic resonance imaging. We found decreased state engagement variability in older participants and preliminary evidence suggesting an association with avolition. CONCLUSIONS: Assessing multiple brain states simultaneously can reflect the complexity of aberrant brain dynamics in BD and SCZ, providing a more comprehensive understanding of the neural mechanisms underpinning these conditions.

Connectome-based machine learning models are vulnerable to subtle data manipulations.

Neuroimaging-based predictive models continue to improve in performance, yet a widely overlooked aspect of these models is "trustworthiness," or robustness to data manipulations. High trustworthiness is imperative for researchers to have confidence in their findings and interpretations. In this work, we used functional connectomes to explore how minor data manipulations influence machine learning predictions. These manipulations included a method to falsely enhance prediction performance and adversarial noise attacks designed to degrade performance. Although these data manipulations drastically changed model performance, the original and manipulated data were extremely similar (r = 0.99) and did not affect other downstream analysis. Essentially, connectome data could be inconspicuously modified to achieve any desired prediction performance. Overall, our enhancement attacks and evaluation of existing adversarial noise attacks in connectome-based models highlight the need for counter-measures that improve the trustworthiness to preserve the integrity of academic research and any potential translational applications.

Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.

Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Nevertheless, despite growing evidence that altered brain maturation during the fetal, infant, and toddler (FIT) period modulates risk for poor mental health outcomes in childhood, these models are rarely implemented in FIT samples. Applications of predictive modeling in children of these ages provide an opportunity to develop powerful tools for improved characterization of the neural mechanisms underlying development. To facilitate the broader use of predictive models in FIT neuroimaging, we present a brief primer and systematic review on the methods used in current predictive modeling FIT studies. Reflecting on current practices in more than 100 studies conducted over the past decade, we provide an overview of topics, modalities, and methods commonly used in the field and under-researched areas. We then outline ethical and future considerations for neuroimaging researchers interested in predicting health outcomes in early life, including researchers who may be relatively new to either advanced machine learning methods or using FIT data. Altogether, the last decade of FIT research in machine learning has provided a foundation for accelerating the prediction of early-life trajectories across the full spectrum of illness and health.

A protocol for working with open-source neuroimaging datasets.

Large, publicly available neuroimaging datasets are becoming increasingly common, but their use presents challenges because of insufficient knowledge of the tool options for data processing and proper data organization. Here, we describe a protocol to lessen these barriers. We describe the steps for the search and download of the open-source dataset. We detail the steps for proper data management and practical guidelines for data analysis. Finally, we give instructions for data and result sharing on public repositories and preprint services. For complete details on the use and execution of this profile, please refer to Horien et al. (2021).

Characterizing cerebral metabolite profiles in anorexia and bulimia nervosa and their associations with habitual behavior.

Anorexia nervosa (AN) and bulimia nervosa (BN) are associated with altered brain structure and function, as well as increased habitual behavior. This neurobehavioral profile may implicate neurochemical changes in the pathogenesis of these illnesses. Altered glutamate, myo-inositol and N-acetyl aspartate (NAA) concentrations are reported in restrictive AN, yet whether these extend to binge-eating disorders, or relate to habitual traits in affected individuals, remains unknown. We therefore used single-voxel proton magnetic resonance spectroscopy to measure glutamate, myo-inositol, and NAA in the right inferior lateral prefrontal cortex and the right occipital cortex of 85 women [n = 22 AN (binge-eating/purging subtype; AN-BP), n = 33 BN, n = 30 controls]. To index habitual behavior, participants performed an instrumental learning task and completed the Creature of Habit Scale. Women with AN-BP, but not BN, had reduced myo-inositol and NAA concentrations relative to controls in both regions. Although patient groups had intact instrumental learning task performance, both groups reported increased routine behaviors compared to controls, and automaticity was related to reduced prefrontal glutamate and NAA participants with AN-BP. Our findings extend previous reports of reduced myo-inositol and NAA levels in restrictive AN to AN-BP, which may reflect disrupted axonal-glial signaling. Although we found inconsistent support for increased habitual behavior in AN-BP and BN, we identified preliminary associations between prefrontal metabolites and automaticity in AN-BP. These results provide further evidence of unique neurobiological profiles across binge-eating disorders.

Longitudinal Trajectory of the Link Between Ventral Striatum and Depression in Adolescence.

OBJECTIVE: Research in adolescent depression has found aberrant intrinsic functional connectivity (iFC) among the ventral striatum (VS) and several brain regions implicated in reward processing. The present study probes this question by taking advantage of the availability of data from a large youth cohort, the IMAGEN Consortium. METHODS: iFC data from 303 adolescents (48% of them female) were used to examine associations of VS connectivity at baseline (at age 14) with depressive disorders at baseline and at 2-year (N=250) and 4-year (N=219) follow-ups. Eleven regions of interest, key nodes of the reward system, were used to probe the reward network and calculate the connectivity strength of the VS within this network (VS connectivityrw). The main analyses assessed associations of VS connectivityrw with depressive disorders, anhedonia, and low mood using logistic regression. Autoregressive models accounting for carryover effects over time were conducted to further evaluate these brain-behavior associations. RESULTS: Higher right VS connectivityrw was associated with higher probability of depressive disorders at baseline (odds ratio=2.65, 95% CI=1.40, 5.05). This finding was confirmed in the autoregressive model, adjusting for carryover effects of the depressive disorders across the three time points. VS connectivityrw was not predictive of depressive disorders at follow-up assessments. Longitudinal associations between VS connectivityrw and anhedonia emerged in the structural equation model: left VS connectivityrw was associated with anhedonia at 2 years (odds ratio=2.20, 95% CI=1.54, 3.14), and right VS connectivityrw was linked to anhedonia at 4 years (odds ratio=1.87, 95% CI=1.09, 3.21). VS connectivityrw did not predict low mood at any time point in the structural equation model. CONCLUSIONS: The connectivity strength of the VS within the reward network showed distinct patterns of association with depressive disorders and anhedonia from mid to late adolescence, suggesting that the role of this circuitry in depression changes with age. This study replicates, in an independent sample, the association between the VS and depression previously reported in younger adolescents. The findings suggest a role of VS connectivityrw in anhedonia but not in low mood.

Combined effects of age and BMI are related to altered cortical thickness in adolescence and adulthood.

Overweight and obesity are associated with functional and structural alterations in the brain, but how these associations change across critical developmental periods remains unknown. Here, we examined the relationship between age, body mass index (BMI) and cortical thickness (CT) in healthy adolescents (n = 70; 14-19 y) and adults (n = 75; 25-45 y). We also examined the relationship between adiposity, impulsivity, measured by delay discounting (DD), and CT of the inferior frontal gyrus (IFG), a region key to impulse control. A significant age-by-BMI interaction was observed in both adolescents and adults; however, the direction of this relationship differed between age groups. In adolescents, increased age-adjusted BMI Z-score attenuated age-related CT reductions globally and in frontal, temporal and occipital regions. In adults, increased BMI augmented age-related CT reductions, both globally and in bilateral parietal cortex. Although DD was unrelated to adiposity in both groups, increased DD and adiposity were both associated with reduced IFG thickness in adolescents and adults. Our findings suggest that the known age effects on CT in adolescence and adulthood are moderated by adiposity. The association between weight, cortical development and its functional implications would suggest that future studies of adolescent and adult brain development take adiposity into account.

Associations between cortical thickness, structural connectivity and severity of dimensional bulimia nervosa symptomatology.

Bulimia nervosa (BN) is a psychiatric illness defined by preoccupation with body image (cognitive 'symptoms'), binge eating and compensatory behaviors. Although diagnosed BN has been related to grey matter alterations, characterization of brain structure in women with a range of BN symptoms has not been made. This study examined whether cortical thickness (CT) values scaled with severity of BN cognitions in 33 women with variable BN pathology. We then assessed global structural connectivity (SC) of CT to determine if individual differences in global SC relate to BN symptom severity. We used the Eating Disorder Examination Questionnaire (EDE-Q) as a continuous measure of BN symptom severity. EDE-Q score was negatively related to global CT and local CT in the left middle frontal gyrus, right superior frontal gyrus and bilateral orbitofrontal cortex (OFC) and temporoparietal regions. Moreover, cortical thinning was most pronounced in regions with high global connectivity. Finally, individual contributions to global SC at the group level related to EDE-Q score, where increased EDE-Q score correlated with reduced connectivity of the left OFC and middle temporal cortex and increased connectivity of the right superior parietal lobule. Findings represent the first evidence of cortical thinning that relates to cognitive BN symptoms.

Impact of the neural correlates of stress and cue reactivity on stress related binge eating in the natural environment.

Women with symptoms of bulimia nervosa (BN) exhibit decreased response to visual food cues in several limbic and frontal regions compared to controls. Stress causes decreased blood oxygenation level dependent (BOLD) response in these regions in non-clinical samples; there is a lack of data on this topic in BN. This study examined the impact of individual differences in neural reactivity to palatable food cues following acute stress on stress-binge trajectories in everyday life. 16 women with BN symptoms viewed palatable food cues prior to and immediately following an acute stress induction in the scanner. Participants then responded to a series of prompts assessing daily ratings of stress and binge episodes for a period of two weeks. Decreased BOLD signal was observed in response to food cues pre to post stress in the anterior cingulate cortex (ACC), amygdala, and ventromedial prefrontal cortex (vmPFC). Ecological momentary assessment data collection demonstrated that stress increased prior to binge episodes in the natural environment, and decreased following. Changes in activation in the ACC, precuneus, and dorsolateral prefrontal cortex (dlPFC) significantly moderated the relationship of stress to binge eating in daily life, such that women who exhibited decreased response reported significantly increasing stress prior to binges, while women who did not exhibit decreases reported no significant change in stress prior to binges. Individual differences in neural response to food cues under stress appear to underlie distinct antecedants to binge eating.