Elevated Body Mass Index is Associated with Increased Integration and Reduced Cohesion of Sensory-Driven and Internally Guided Resting-State Functional Brain Networks

Functional alterations in overweight/obesity: focusing on the reward and executive control network

Overweight (OW) and obesity (OB) have become prevalent issues in the global public health arena. Serving as a prominent risk factor for various chronic diseases, overweight/obesity not only poses serious threats to people's physical and mental health but also imposes significant medical and economic burdens on society as a whole. In recent years, there has been a growing focus on basic scientific research dedicated to seeking the neural evidence underlying overweight/obesity, aiming to elucidate its causes and effects by revealing functional alterations in brain networks. Among them, dysfunction in the reward network (RN) and executive control network (ECN) during both resting state and task conditions is considered pivotal in neuroscience research on overweight/obesity. Their aberrations contribute to explaining why persons with overweight/obesity exhibit heightened sensitivity to food rewards and eating disinhibition. This review centers on the reward and executive control network by analyzing and organizing the resting-state and task-based fMRI studies of functional brain network alterations in overweight/obesity. Building upon this foundation, the authors further summarize a reward-inhibition dual-system model, with a view to establishing a theoretical framework for future exploration in this field.

Relationship between functional connectivity and weight-gain risk of antipsychotics in schizophrenia

BACKGROUND

The mechanisms by which antipsychotic medications (APs) contribute to obesity in schizophrenia are not well understood. Because AP effects on functional brain connectivity may contribute to weight effects, the current study investigated how AP-associated weight-gain risk relates to functional connectivity in schizophrenia.

METHODS

Fifty-five individuals with schizophrenia (final N = 54) were divided into groups based on previously reported AP weight-gain risk (no APs/low risk [N = 19]; moderate risk [N = 17]; high risk [N = 18]). Resting-state functional magnetic resonance imaging (fMRI) was completed after an overnight fast ("fasted") and post-meal ("fed"). Correlations between AP weight-gain risk and functional connectivity were assessed at the whole-brain level and in reward- and eating-related brain regions (anterior insula, caudate, nucleus accumbens).

RESULTS

When fasted, greater AP weight-gain risk was associated with increased connectivity between thalamus and sensorimotor cortex (pFDR = 0.021). When fed, greater AP weight-gain risk was associated with increased connectivity between left caudate and left precentral/postcentral gyri (pFDR = 0.048) and between right caudate and multiple regions, including the left precentral/postcentral gyri (pFDR = 0.001), intracalcarine/precuneal/cuneal cortices (pFDR < 0.001), and fusiform gyrus (pFDR = 0.008). When fed, greater AP weight-gain risk was also associated with decreased connectivity between right anterior insula and ventromedial prefrontal cortex (pFDR = 0.002).

CONCLUSIONS

APs with higher weight-gain risk were associated with greater connectivity between reward-related regions and sensorimotor regions when fasted, perhaps relating to motor anticipation for consumption. Higher weight-gain risk APs were also associated with increased connectivity between reward, salience, and visual regions when fed, potentially reflecting greater desire for consumption following satiety.

Associations of Brain Entropy Estimated by Resting State fMRI With Physiological Indices, Body Mass Index, and Cognition

BACKGROUND

In recent years, resting-state fMRI (rsfMRI)-based brain entropy (BEN) has gained increasing interest as a tool to characterize brain activity. While previous studies indicate that BEN is correlated with cognition, it remains unclear whether BEN is influenced by other factors that typically affect brain activity measured by fMRI.

PURPOSE

To investigate the relationship between BEN and physiological indices, including respiratory rate (RR), heart rate (HR), systolic blood pressure (s-BP), and body mass index (BMI), and to investigate whether and to what extent the relationship between BEN and cognition is influenced by physiological variables.

STUDY TYPE

Retrospective.

SUBJECTS

One thousand two hundred six healthy subjects (mean age: 28.83 ± 3.69 years; 550 male) with rsfMRI datasets selected from the Human Connectome Project (HCP).

FIELD STRENGTH/SEQUENCE

Multiband echo planar imaging (EPI) sequence at 3.0 Tesla.

ASSESSMENT

Neurocognitive, physical health (RR, HR, s-BP, BMI), and rsfMRI data were retrieved from the HCP datasets. Neurocognition was measured through the total cognition composite (TCC) score provided by HCP. BEN maps were calculated from rsfMRI data.

STATISTICAL TESTS

Multiple regression models, pheight-family wise error (FWE) < 0.05 and pcluster-FWE < 0.05 were considered statistically significant.

RESULTS

BEN was negatively associated with RR (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) and positively associated with s-BP and BMI (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) in areas overlapping with the default mode network. After controlling the physiological effects, BEN still showed regional associations with TCC, including negative associations (T-thresholds = 3.09; r-threshold = |0.1|) in the fronto-parietal cortex and positive associations (T-thresholds = 3.09; r-threshold = |0.1|) in the sensorimotor system (motor network and the limbic system).

DATA CONCLUSIONS

RR negatively affects rsfMRI-derived BEN, while s-BP and BMI positively affect BEN. The positive associations between BEN and cognition in the motor network and the limbic system might indicate a facilitation of information processing in the sensorimotor system.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity

Background

Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention.

Methods

In a sub-study of 102 participants of the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on magnetic resonance imaging (MRI)-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age.

Results

To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months' attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18 months of intervention. Finally, we showed that lower consumption of processed food, sweets and beverages were associated with attenuated brain age.

Conclusions

Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging.

Funding

The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11, Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission 09933838 SFB 105 (to I Shai).

Altered functional connectivity of the right caudate nucleus in chronic migraine: a resting-state fMRI study

BACKGROUND

The definitive pathogenic mechanisms underlying chronic migraine (CM) remain unclear. Mounting evidence from functional and structural magnetic resonance imaging (MRI) studies suggests that the caudate nucleus (CN) plays a role in the cognitive, sensory, and emotional integration of pain information in patients with migraine. However, evidence concerning the role played by CN in CM patients is limited. Here, we used the CN as the seed to explore patterns of functional connectivity (FC) among healthy controls (HCs), patients with episodic migraine (EM), and patients with CM.

METHODS

We included 25 HCs, 23 EM patients, and 46 CM patients in this study. All participants underwent resting-state functional MRI scans on a GE 3.0T MRI system. We performed seed-based FC analyses among the three groups using the bilateral CNs as seeds. We also compared the subgroups of CM (with and without medication overuse headache, males and females) and performed Pearson's correlation analyses between FC values and the clinical features of CM patients.

RESULTS

FC values between the right CN and five clusters (mainly involved in emotion, cognition, and sensory-related brain regions) were higher in CM patients than in HCs. Compared to EM patients, enhanced FC values between the bilateral precuneus, left anterior cingulate gyrus, right middle cingulate cortex, right lingual gyrus, and right CN were shown in the CM patients. There were no significant differences between CM patients with and without MOH, males and females. FC values between the bilateral calcarine cortex, lingual gyrus, and right CN were positively correlated with body mass index. Moreover, right CN-related FC values in the left calcarine cortex and right lingual gyrus were inversely correlated with visual analogue scale scores for headaches.

CONCLUSION

Our results revealed abnormal right CN-based FC values in CM patients, suggesting dysfunction of brain networks associated with pain perception and multi-regulation (emotion, cognition, and sensory). Aberrant FC of the CN can provide potential neuroimaging markers for the diagnosis and treatment of CM.

Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters

Introduction: Replicability has become an increasing focus within the scientific communities with the ongoing "replication crisis." One area that appears to struggle with unreliable results is resting-state functional magnetic resonance imaging (rs-fMRI). Therefore, the current study aimed at improving the knowledge of endogenous factors that contribute to inter-individual variability. Methods: Arterial blood pressure (BP), body mass, hematocrit, and glycated hemoglobin were investigated as potential sources of between-subject variability in rs-fMRI, in healthy individuals. Whether changes in resting-state networks (rs-networks) could be attributed to variability in the blood-oxygen-level-dependent (BOLD)-signal, changes in neuronal activity, or both was of special interest. Within-subject parameters were estimated by utilizing dynamic-causal modeling, as it allows to make inferences on the estimated hemodynamic (BOLD-signal dynamics) and neuronal parameters (effective connectivity) separately. Results: The results of the analyses imply that BP and body mass can cause between-subject and between-group variability in the BOLD-signal and that all the included factors can affect the underlying connectivity. Discussion: Given the results of the current and previous studies, rs-fMRI results appear to be susceptible to a range of factors, which is likely to contribute to the low degree of replicability of these studies. Interestingly, the highest degree of variability seems to appear within the much-studied default mode network and its connections to other networks. Impact statement We believe that thanks to the evidence that we have collected by analyzing the well-controlled data of the Human Connectome Project with dynamic-causal modeling (DCM) and by focusing not only on the effective connectivity, which is the typical way of using DCM, but also by analyzing the underlying hemodynamic parameters, we were able to explore the underlying vascular dependencies in a much broader perspective. Our results challenge the premise for studying changes in the default mode network as a clinical marker of disease, and we add to the growing list of factors that contribute to resting-state network variability.

The reduction of vitamin D in females with major depressive disorder is associated with worse cognition mediated by abnormal brain functional connectivity

Low vitamin D is linked to major depressive disorder (MDD) through affecting the brain. Gender difference is apparent in MDD and vitamin D level. We aimed to examine the association between gender, vitamin D, clinical presentations, and brain functional connectivity in a large cohort of MDD patients and comparison subjects. Resting-state functional MRI data from 122 patients and 119 controls were collected to perform a combined analysis of functional connectivity density (FCD) and seed-based functional connectivity (FC). Peripheral venous blood samples were obtained to measure serum concentration of vitamin D (SCVD). Clinical presentations (symptoms profiles and cognition) were also assessed. We found an interaction of group and gender on SCVD in which MDD patients demonstrated lower SCVD than controls in females rather than males. Concurrently, lower SCVD was associated with worse cognitive performance (prospective memory and sustained attention). Compared with controls, female MDD patients showed reduced FCD and FC of the left middle frontal gyrus, which were related to lower SCVD. Importantly, these FCD and FC changes mediated the relationship between lower SCVD and cognitive dysfunction. Our findings suggest that functional connectivity abnormalities may serve as neural substrates underlying the associations between low vitamin D and cognitive impairments in female MDD patients, providing unique insight into treatment and prevention of MDD and its related cognitive dysfunction from the perspective of regulating circulating vitamin D.

A systematic review of resting-state functional connectivity in obesity: Refining current neurobiological frameworks and methodological considerations moving forward

Obesity is the second most common cause of preventable morbidity worldwide. Resting-state functional magnetic resonance imaging (fMRI) has been used extensively to characterise altered communication between brain regions in individuals with obesity, though findings from this research have not yet been systematically evaluated within the context of prominent neurobiological frameworks. This systematic review aggregated resting-state fMRI findings in individuals with obesity and evaluated the contribution of these findings to current neurobiological models. Findings were considered in relation to a triadic model of problematic eating, outlining disrupted communication between reward, inhibitory, and homeostatic systems. We identified a pattern of consistently increased orbitofrontal and decreased insula cortex resting-state functional connectivity in individuals with obesity in comparison to healthy weight controls. BOLD signal amplitude was also increased in people with obesity across studies, predominantly confined to subcortical regions, including the hippocampus, amygdala, and putamen. We posit that altered orbitofrontal cortex connectivity may be indicative of a shift in the valuation of food-based rewards and that dysfunctional insula connectivity likely contributes to altered homeostatic signal processing. Homeostatic violation signals in obesity may be maintained despite satiety, thereby 'hijacking' the executive system and promoting further food intake. Moving forward, we provide a roadmap for more reliable resting-state and task-based functional connectivity experiments, which must be reconciled within a common framework if we are to uncover the interplay between psychological and biological factors within current theoretical frameworks.

Obesity, Psychological Distress, and Resting State Connectivity of the Hippocampus and Amygdala Among Women With Early-Stage Breast Cancer

Objective

Overweight and obesity [body mass index (BMI) ≥ 25 kg/m2] are associated with poorer prognosis among women with breast cancer, and weight gain is common during treatment. Symptoms of depression and anxiety are also highly prevalent in women with breast cancer and may be exacerbated by post-diagnosis weight gain. Altered brain function may underlie psychological distress. Thus, this secondary analysis examined the relationship between BMI, psychological health, and resting state functional connectivity (rsFC) among women with breast cancer.

Methods

The sample included 34 post-menopausal women newly diagnosed with Stage 0-IIa breast cancer (Mage = 63.59 ± 5.73) who were enrolled in a 6-month randomized controlled trial of aerobic exercise vs. usual care. At baseline prior to randomization, whole-brain analyses were conducted to evaluate the relationship between BMI and seed-to-voxel rsFC of the hippocampus and amygdala. Connectivity values from significant clusters were then extracted and examined as predictors of self-reported depression and anxiety.

Results

Mean BMI was in the obese range (M = 31.83 ± 6.62). For both seeds examined, higher BMI was associated with lower rsFC with regions of prefrontal cortex (PFC), including ventrolateral PFC (vlPFC), dorsolateral PFC, and superior frontal gyrus (z range = 2.85-4.26). Hippocampal connectivity with the vlPFC was negatively correlated with self-reported anxiety (β = 0.47, p < 0.01).

Conclusion

Higher BMI was associated with lower hippocampal and amygdala connectivity to regions of PFC implicated in cognitive control and emotion regulation. BMI-related differences in hippocampal and amygdala connectivity following a recent breast cancer diagnosis may relate to future worsening of psychological functioning during treatment and remission. Additional longitudinal research exploring this hypothesis is warranted.

Altered Brain Structural Reorganization and Hierarchical Integrated Processing in Obesity

The brain receives sensory information about food, evaluates its desirability and value, and responds with approach or withdrawal. The evaluation process of food in the brain with obesity may involve a variety of neurocircuit abnormalities in the integration of internal and external information processing. There is a lack of consistency of the results extant reported for aberrant changes in the brain with obesity that prohibits key brain alterations to be identified. Moreover, most studies focus on the observation of neural plasticity of function or structure, and the evidence for functional and structural correlations in the neuronal plasticity process of obesity is still insufficient. The aims of this article are to explore the key neural structural regions and the hierarchical activity pattern of key structural nodes and evaluate the correlation between changes in functional modulation and eating behavior. Forty-two participants with obesity and 33 normal-weight volunteers were recruited. Gray matter volume (GMV) and Granger causality analysis (GCA) were performed using the DPARSF, CAT12, and DynamicBC toolbox. Compared with the normal weight group, the obesity group exhibited significantly increased GMV in the left parahippocampal gyrus (PG). The obesity group showed decreased causal inflow to the left PG from the left orbitofrontal cortex (OFC), right calcarine, and bilateral supplementary motor area (SMA). Decreased causal outflow to the left OFC, right precuneus, and right SMA from the left PG, as well as increased causal outflow to the left middle occipital gyrus (MOG) were observed in the obesity group. Negative correlations were found between DEBQ-External scores and causal outflow from the left PG to the left OFC, and DEBQ-Restraint scores and causal inflow from the left OFC to the left PG in the obesity group. Positive correlation was found between DEBQ-External scores and causal outflow from the left PG to the left MOG. These results show that the increased GMV in the PG may play an important role in obesity, which may be related to devalued reward system, altered behavioral inhibition, and the disengagement of attentional and visual function for external signals. These findings have important implications for understanding neural mechanisms in obesity and developing individual-tailored strategies for obesity prevention.

Multivariate patterns of brain-behavior associations across the adult lifespan

The nature of brain-behavior covariations with increasing age is poorly understood. In the current study, we used a multivariate approach to investigate the covariation between behavioral-health variables and brain features across adulthood. We recruited healthy adults aged 20–73 years-old (29 younger, mean age = 25.6 years; 30 older, mean age = 62.5 years), and collected structural and functional MRI (s/fMRI) during a resting-state and three tasks. From the sMRI, we extracted cortical thickness and subcortical volumes; from the fMRI, we extracted activation peaks and functional network connectivity (FNC) for each task. We conducted canonical correlation analyses between behavioral-health variables and the sMRI, or the fMRI variables, across all participants. We found significant covariations for both types of neuroimaging phenotypes (ps = 0.0004) across all individuals, with cognitive capacity and age being the largest opposite contributors. We further identified different variables contributing to the models across phenotypes and age groups. Particularly, we found behavior was associated with different neuroimaging patterns between the younger and older groups. Higher cognitive capacity was supported by activation and FNC within the executive networks in the younger adults, while it was supported by the visual networks’ FNC in the older adults. This study highlights how the brain-behavior covariations vary across adulthood and provides further support that cognitive performance relies on regional recruitment that differs between older and younger individuals.

Disrupted stepwise functional brain organization in overweight individuals

Functional hierarchy establishes core axes of the brain, and overweight individuals show alterations in the networks anchored on these axes, particularly in those involved in sensory and cognitive control systems. However, quantitative assessments of hierarchical brain organization in overweight individuals are lacking. Capitalizing stepwise functional connectivity analysis, we assess altered functional connectivity in overweight individuals relative to healthy weight controls along the brain hierarchy. Seeding from the brain regions associated with obesity phenotypes, we conduct stepwise connectivity analysis at different step distances and compare functional degrees between the groups. We find strong functional connectivity in the somatomotor and prefrontal cortices in both groups, and both converge to transmodal systems, including frontoparietal and default-mode networks, as the number of steps increased. Conversely, compared with the healthy weight group, overweight individuals show a marked decrease in functional degree in somatosensory and attention networks across the steps, whereas visual and limbic networks show an increasing trend. Associating functional degree with eating behaviors, we observe negative associations between functional degrees in sensory networks and hunger and disinhibition-related behaviors. Our findings suggest that overweight individuals show disrupted functional network organization along the hierarchical axis of the brain and these results provide insights for behavioral associations.

Weight Status Modulated Brain Regional Homogeneity in Long-Term Male Smokers

BACKGROUND

Tobacco smoking and being overweight could lead to adverse health effects, which remain an important public health problem worldwide. Research indicates that overlapping pathophysiology may contribute to tobacco addiction and being overweight, but the neurobiological interaction mechanism between the two factors is still unclear.

METHODS

The current study used a mixed sample design, including the following four groups: (i) overweight long-term smokers (n = 24); (ii) normal-weight smokers (n = 28); (iii) overweight non-smokers (n = 19), and (iv) normal-weight non-smokers (n = 28), for a total of 89 male subjects. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) was used to compare internal cerebral activity among the four groups. Interaction effects between tobacco addiction and weight status on ReHo were detected using a two-way analysis of variance, correcting for age, years of education, and head motion.

RESULTS

A significant interaction effect between tobacco addiction and weight status is shown in right superior frontal gyrus. Correlation analyses show that the strengthened ReHo value in the right superior frontal gyrus is positively associated with pack-year. Besides, the main effect of tobacco addiction is specially observed in the occipital lobe and cerebellum posterior lobe. As for the main effect of weight status, the right lentiform nucleus, left postcentral gyrus, and brain regions involved in default mode network (DMN) survived.

CONCLUSIONS

These results shed light on an antagonistic interaction on brain ReHo between tobacco addiction and weight status in the right superior frontal gyrus, which may be a clinical neuro-marker of comorbid tobacco addiction and overweight. Our findings may provide a potential target to develop effective treatments for the unique population of comorbid tobacco addiction and overweight people.

Exploration of the influence of body mass index on intra-network resting-state connectivity in chronic cigarette smokers

BACKGROUND

Obesity and cigarette smoking are two leading preventable causes of death. Previous research suggests that comorbid smoking and obesity likely share neurobehavioral underpinnings; however, the influence of body mass index (BMI) on resting-state functional connectivity (rsFC) in smokers remains unknown. In this study, we explore how BMI affects rsFC and associations between rsFC and smoking-related behavior.

METHODS

Treatment-seeking cigarette smokers (N = 87; 54 % men) completed a BOLD resting-state fMRI scan session. We grouped smokers into BMI groups (N = 23 with obesity, N = 33 with overweight, N = 31 lean) and used independent components analysis (ICA) to identify the resting state networks commonly associated with cigarette smoking: salience network (SN), right and left executive control networks (ECN) and default mode network (DMN). Average rsFC values were extracted (p < 0.001, k = 100) to determine group differences in rsFC and relationship to self-reported smoking and dependence.

RESULTS

Analyses revealed a significant relationship between BMI and connectivity in the SN and a significant quadratic effect of BMI on DMN connectivity. Heavier smoking was related to greater rsFC in the SN among lean and obese groups but reduced rsFC in the overweight group.

CONCLUSIONS

Findings build on research suggesting an influence of BMI on the neurobiology of smokers. In particular, dysfunction of SN-DMN-ECN circuitry in smokers with overweight may lead to a failure to modulate attention and behavior and subsequent difficulty quitting smoking. Future research is needed to elucidate the mechanism underlying the interaction of BMI and smoking and its impact on treatment.

The Association between Body Mass Index and Intra-Cortical Myelin: Findings from the Human Connectome Project

Intra-cortical myelin is a myelinated part of the cerebral cortex that is responsible for the spread and synchronization of neuronal activity in the cortex. Recent animal studies have established a link between obesity and impaired oligodendrocyte maturation vis-à-vis cells that produce and maintain myelin; however, the association between obesity and intra-cortical myelination remains to be established. To investigate the effects of obesity on intra-cortical myelin in living humans, we employed a large, demographically well-characterized sample of healthy young adults drawn from the Human Connectome Project (n = 1066). Intra-cortical myelin was assessed using a novel T1-w/T2-w ratio method. Linear regression analysis was used to investigate the association between body mass index (BMI), an indicator of obesity, and intra-cortical myelination, adjusting for covariates of no interest. We observed BMI was related to lower intra-cortical myelination in regions previously identified to be involved in reward processing (i.e., medial orbitofrontal cortex, rostral anterior cingulate cortex), attention (i.e., visual cortex, inferior/middle temporal gyrus), and salience detection (i.e., insula, supramarginal gyrus) in response to viewing food cues (corrected p < 0.05). In addition, higher BMIs were associated with more intra-cortical myelination in regions associated with somatosensory processing (i.e., the somatosensory network) and inhibitory control (i.e., lateral inferior frontal gyrus, frontal pole). These findings were also replicated after controlling for key potential confounding factors including total intracranial volume, substance use, and fluid intelligence. Findings suggested that altered intra-cortical myelination may represent a novel microstructure-level substrate underlying prior abnormal obesity-related brain neural activity, and lays a foundation for future investigations designed to evaluate how living habits, such as dietary habit and physical activity, affect intra-cortical myelination.

Contrasting dorsal caudate functional connectivity patterns between frontal and temporal cortex with BMI increase: link to cognitive flexibility

BACKGROUND

Obesity is associated with brain intrinsic functional reorganization. However, little is known about the BMI-related interhemispheric functional connectivity (IHFC) alterations, and their link with executive function in young healthy adults.

METHODS

We examined voxel-mirrored homotopic connectivity (VMHC) patterns in 417 young adults from the Human Connectome Project. Brain regions with significant association between BMI and VMHC were identified using multiple linear regression. Results from these analyses were then used to determine regions for seed-voxel FC analysis, and multiple linear regression was used to explore the brain regions showing significant association between BMI and FC. The correlations between BMI-related executive function measurements and VMHC, as well as seed-voxel FC, were further examined.

RESULTS

BMI was negatively associated with scores of Dimensional Change Card Sort Test (DCST) assessing cognitive flexibility (r = -0.14, p = 0.006) and with VMHC of bilateral inferior parietal lobule, insula and dorsal caudate. The dorsal caudate emerged as a nexus for BMI-related findings: greater BMI was associated with greater FC between caudate and hippocampus and lower FC between caudate and several prefrontal nodes (right inferior frontal gyrus, anterior cingulate cortex, and middle frontal gyrus). The FC between right caudate and left hippocampus was negatively associated with scores of DCST (r = -0.15, p = 0.0018).

CONCLUSIONS

Higher BMI is associated with poorer cognitive flexibility performance and IHFC in an extensive set of brain regions implicated in cognitive control. Larger BMI was associated with higher caudate-medial temporal lobe FC and lower caudate-dorsolateral prefrontal cortex FC. These findings may have relevance for executive function associated with weight gain among otherwise healthy young adults.

Effects of bariatric surgery on functional connectivity of the reward and default mode network: A pre-registered analysis

Obesity imposes serious health risks and involves alterations in resting‐state functional connectivity of brain networks involved in eating behavior. Bariatric surgery is an effective treatment, but its effects on functional connectivity are still under debate. In this pre‐registered study, we aimed to determine the effects of bariatric surgery on major resting‐state brain networks (reward and default mode network) in a longitudinal controlled design. Thirty‐three bariatric surgery patients and 15 obese waiting‐list control patients underwent magnetic resonance imaging at baseline, after 6 and 12 months. We conducted a pre‐registered whole‐brain time‐by‐group interaction analysis, and a time‐by‐group interaction analysis on within‐network connectivity. In exploratory analyses, we investigated the effects of weight loss and head motion. Bariatric surgery compared to waiting did not significantly affect functional connectivity of the reward network and the default mode network (FWE‐corrected p > .05), neither whole‐brain nor within‐network. In exploratory analyses, surgery‐related BMI decrease (FWE‐corrected p = .041) and higher average head motion (FWE‐corrected p = .021) resulted in significantly stronger connectivity of the reward network with medial posterior frontal regions. This pre‐registered well‐controlled study did not support a strong effect of bariatric surgery, compared to waiting, on major resting‐state brain networks after 6 months. Exploratory analyses indicated that head motion might have confounded the effects. Data pooling and more rigorous control of within‐scanner head motion during data acquisition are needed to substantiate effects of bariatric surgery on brain organization.

Dysregulated resting state functional connectivity and obesity: A systematic review

Obesity has been variously linked to differences in brain functional connectivity in regions associated with reward, emotional regulation and cognition, potentially revealing neural mechanisms contributing to its development and maintenance. This systematic review summarizes and critically appraises the existing literature on differences in resting state functional connectivity (Rs-FC) between overweight and individuals with obesity in relation healthy-BMI controls. Twenty-nine studies were identified and the results consistently support the hypothesis that obesity is associated with differences in Rs-FC. Specifically, obesity/overweight was consistently associated with (i) DMN hypoconnectivity and salience network hyperconnectivity; (ii) increased Rs-FC between the hypothalamus and reward, limbic and salience networks, and decreased Rs-FC between the hypothalamus and cognitive regions; (iii) increased power within regions associated with inhibition/emotional reasoning; (iv) decreased nodal efficiency, degree centrality, and global efficiency. Collectively, the results suggest obesity is associated with disrupted connectivity of brain networks responsible for cognition, reward, self-referential processing and emotional regulation.

Inter-individual body mass variations relate to fractionated functional brain hierarchies

Variations in body mass index (BMI) have been suggested to relate to atypical brain organization, yet connectome-level substrates of BMI and their neurobiological underpinnings remain unclear. Studying 325 healthy young adults, we examined associations between functional connectivity and inter-individual BMI variations. We utilized non-linear connectome manifold learning techniques to represent macroscale functional organization along continuous hierarchical axes that dissociate low level and higher order brain systems. We observed an increased differentiation between unimodal and heteromodal association networks in individuals with higher BMI, indicative of a disrupted modular architecture and hierarchy of the brain. Transcriptomic decoding and gene enrichment analyses identified genes previously implicated in genome-wide associations to BMI and specific cortical, striatal, and cerebellar cell types. These findings illustrate functional connectome substrates of BMI variations in healthy young adults and point to potential molecular associations.

Reduced network integration in default mode and executive networks is associated with social and personal optimism biases

An optimism bias refers to the belief in good things happening to oneself in the future with a higher likelihood than is justified. Social optimism biases extend this concept to groups that one identifies with. Previous literature has found that both personal and social optimism biases are linked to brain structure and task-related brain function. Less is known about whether optimism biases are also expressed in resting-state functional connectivity (RSFC). Forty-two participants completed questionnaires on dispositional personal optimism (which is not necessarily unjustified) and comparative optimism (i.e., whether we see our own future as being rosier than a comparison person's future) and underwent a resting-state functional magnetic resonance imaging scan. They further undertook an imaginative soccer task in order to assess both their personal and social optimism bias. We tested associations of these data with RSFC within and between 13 networks, using sparse canonical correlation analyses (sCCAs). We found that the primary sCCA component was positively connected to personal and social optimism bias and negatively connected to dispositional personal pessimism. This component was associated with (a) reduced integration of the default mode network, (b) reduced integration of the central executive and salience networks, and (c) reduced segregation between the default mode network and the central executive network. Our finding that optimism biases are linked to RSFC indicates that they may be rooted in neurobiology that exists outside of concurrent tasks. This poses questions as to what the limits of the malleability of such biases may be.

Altered between-network connectivity in individuals prone to obesity

OBJECTIVE

Investigating intrinsic brain functional connectivity may help identify the neurobiology underlying cognitive patterns and biases contributing to obesity propensity. To address this, the current study used a novel whole-brain, data-driven approach to examine functional connectivity differences in large-scale network interactions between obesity-prone (OP) and obesity-resistant (OR) individuals.

METHODS

OR (N = 24) and OP (N = 25) adults completed functional magnetic resonance imaging (fMRI) during rest. Large-scale brain networks were identified using independent component analysis (ICA). Voxel-specific between-network connectivity analysis assessed correlations between ICA component time series' and individual voxel time series, identifying regions strongly connected to many networks, i.e., "hubs".

RESULTS

Significant group differences in between-network connectivity (OP vs. OR; FDR-corrected) were observed in bilateral basal ganglia (left: q = 0.009; right: q = 0.010) and right dorsolateral prefrontal cortex (dlPFC; q = 0.026), with OP>OR. Basal ganglia differences were largely driven by a more strongly negative correlation with a lateral sensorimotor network in OP, with dlPFC differences driven by a more strongly negative correlation with an inferior visual network in OP.

CONCLUSIONS

Greater between-network connectivity was observed in the basal ganglia and dlPFC in OP, driven by stronger associations with lateral sensorimotor and inferior visual networks, respectively. This may reflect a disrupted balance between goal-directed and habitual control systems and between internal/external monitoring processes.

Earlier onset of menstruation is related to increased body mass index in adulthood and altered functional correlations between visual, task control and somatosensory brain networks

Later onset of puberty has been associated with lower body mass index (BMI) in adulthood independent of childhood BMI. However, how the relationship between time of onset of puberty and BMI in adulthood is associated with neurocognitive outcomes is largely unstudied. In the present study, women were sampled from the Human Connectome Project 1200 parcellation, timeseries and netmats1 release (PTN) release. Inclusion criteria were: four (15 minutes) resting state fMRI scans, current measured BMI, self-reported age at onset of menstruation (a proxy of age at onset of puberty) and no endocrine complications (eg, polycystic ovarian syndrome). The effect of age at onset of menstruation, measured BMI at scan date and the interaction of age at onset of menstruation by BMI on brain functional correlation was modelled using fslnets (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets) controlling for race and age at scan. Corrected significance was set at a family-wise error probability (pFWE) < 0.05. A final sample of n = 510 (age 29.5 years ± 3.6, BMI at scan 25.9 ± 5.6 and age at onset of menstruation 12.7 ± 1.6 were included. Age at onset of menstruation was negatively associated with BMI at scan (r = - 0.19, P < 0.001). The interaction between age at onset of menstruation and BMI at scan was associated with stronger correlation between a somatosensory and visual network (t = 3.45, pFWE = 0.026) and a visual network and cingulo-opercular task control network (t = 4.74, pFWE = 0.0002). Post-hoc analyses of behavioural/cognitive measures showed no effect of the interaction between BMI and age at onset of menstruation on behavioural/cognitive measures. However, post-hoc analyses of heritability showed adult BMI and the correlation between the visual and somatosensory networks have high heritability. In sum, we report increased correlation between visual, taste-associated and self-control brain regions in women at high BMI with later age at onset of menstruation.

A review of the relationship between eating behavior, obesity and functional brain network organization

Obesity is a major public health issue affecting nearly 40% of American adults and is associated with increased mortality and elevated risk for a number of physical and psychological illnesses. Obesity is associated with impairments in executive functions such as decision making and inhibitory control, as well as in reward valuation, which is thought to contribute to difficulty sustaining healthy lifestyle behaviors, including adhering to a healthy diet. Growing evidence indicates that these impairments are accompanied by disruptions in functional brain networks, particularly those that support self-regulation, reward valuation, self-directed thinking and homeostatic control. Weight-related differences in task-evoked and resting-state connectivity have most frequently been noted in the executive control network (ECN), salience network (SN) and default mode network (DMN), with obesity generally being associated with weakened connectivity in the ECN and enhanced connectivity in the SN and DMN. Similar disruptions have been observed in the much smaller literature examining the relationship between diet and disordered eating behaviors on functional network organization. The purpose of this narrative review was to summarize what is currently known about how obesity and eating behavior relate to functional brain networks, describe common patterns and provide recommendations for future research based on the identified gaps in knowledge.

Person-based similarity in brain structure and functional connectivity in bipolar disorder

BACKGROUND

Bipolar disorder shows significant variability in clinical presentation. Here we adopt a personalized approach to quantify the brain structural and functional similarity of each individual patient to other patients and to healthy individuals.

METHODS

Brain morphometric and resting-state functional connectivity measures from two independent samples of patients with bipolar disorder and healthy individuals (total number of participants=215) were modeled as single vectors to generated individualized morphometric and connectivity profiles. These profiles were then used to compute a person-based similarity indices which quantified the similarity in neuroimaging profiles amongst patients and between patients and health individuals.

RESULTS

The morphometric and connectivity profiles of patients showed within-diagnosis similarity which was comparable to that observed in healthy individuals. They also showed minimal deviance from those of healthy individuals; the correlation between the profiles of patients and healthy individuals was high (range: 0.71-0.94, p<10^-5). The degree of similarity between imaging profiles was associated with IQ (for cortical thickness) and age (functional integration) rather than clinical variables. Patients who were prescribed lithium, compared to those who were not, showed greater similarity to healthy individuals in terms of network integration (t = 2.2, p = 0.03).

LIMITATIONS

We focused on patients with Bipolar disorder, type I only.

CONCLUSIONS

High inter-individual similarity in neuroimaging profiles was observed amongst patients with bipolar disorder and between patients and healthy individuals. We infer that brain alterations associated with bipolar disorder may be nested within the normal biological diversity consistent with the high prevalence of mood symptoms in the general population.

In Utero Exposure to Maternal Overweight or Obesity is Associated with Altered Offspring Brain Function in Middle Childhood

OBJECTIVE

The impact of in utero exposure to maternal overweight and obesity on offspring metabolic health is well documented. Neurodevelopmental outcomes among these children are, however, less well studied. To address this gap, the current study investigated brain function among 4- to 6-year-old children exposed to maternal overweight or obesity during gestation compared with that of children born to mothers with healthy BMI in pregnancy.

METHODS

Resting-state functional magnetic resonance imaging was used to study neuronal activity and connectivity during a passive viewing task (movie) among 101 typically developing children enrolled in the Healthy Start study, a longitudinal prebirth cohort in Colorado.

RESULTS

Forty-nine children (48%) were exposed to maternal overweight or obesity in utero (mean age = 5 years, SD = 0.9). Children born to mothers with overweight or obesity demonstrated hyperactivity in the left posterior cingulate cortex and hypoactivity in the dorsal anterior cingulate and the supplementary motor area (P < 0.05 for all). Children born to mothers with overweight or obesity also showed ubiquitously weaker brain connectivity (P < 0.05 for all).

CONCLUSIONS

These novel results suggest altered brain function among children exposed to maternal overweight and obesity in utero.

Neuroimaging of Sex/Gender Differences in Obesity: A Review of Structure, Function, and Neurotransmission

While the global prevalence of obesity has risen among both men and women over the past 40 years, obesity has consistently been more prevalent among women relative to men. Neuroimaging studies have highlighted several potential mechanisms underlying an individual’s propensity to become obese, including sex/gender differences. Obesity has been associated with structural, functional, and chemical alterations throughout the brain. Whereas changes in somatosensory regions appear to be associated with obesity in men, reward regions appear to have greater involvement in obesity among women than men. Sex/gender differences have also been observed in the neural response to taste among people with obesity. A more thorough understanding of these neural and behavioral differences will allow for more tailored interventions, including diet suggestions, for the prevention and treatment of obesity.

Stressing diets? Amygdala networks, cumulative cortisol, and weight loss in adolescents with excess weight

OBJECTIVE

The amygdala is importantly involved in stress and obesity, but its role on weight change and diet-related stress remains unexplored among adolescents with excess weight. We aimed to examine the functional connectivity of the Central and Basolateral amygdala nuclei (CeA and BLA) among adolescents, and to explore the longitudinal association between brain connectivity measures and diet-related cortisol and weight loss in adolescents with excess weight.

METHODS

We compared resting-state functional connectivity between adolescents with excess (EW, N = 34; Age = 16.44 ± 1.66) and normal weight (NW, N = 36; Age = 16.50 ± 1.40) using a seed-based (CeA and BLA) whole-brain approach. Then, in a subset of 30 adolescents with EW, followed-up after 3-months of dietary/lifestyle intervention, we explored for interactions between connectivity in the CeA/BLA networks and weight loss. Regression analyses were performed to explore the relationship between accumulated cortisol and weight loss, and to test the potential effect of the amygdala networks on such association.

RESULTS

In EW compared with NW, the CeA regions showed higher functional connectivity with anterior portions, and lower connectivity with posterior portions of the cingulate cortex, while the left BLA regions showed lower connectivity with the dorsal caudate and angular gyrus. In addition, higher connectivity between the left CeA-midbrain network was negatively associated with weight loss. Hair cortisol significantly predicted weight change (p = 0.012). However, this association was no longer significant (p = 0.164) when considering the CeA-midbrain network in the model as an additional predictor.

CONCLUSIONS

Adolescents with EW showed functional connectivity alterations within the BLA/CeA networks. The CeA-midbrain network might constitute an important brain pathway regulating weight change.

Individual intelligence and brain neural correlates associated with outcome expectancies for risk behaviors in adults

Although adults have matured developments of general intelligence, brain structure and brain function, many people continue to be risk takers, despite the harm that can result. The neural basis underlying risk-taking behaviors has been studied extensively in adolescents, but less so in adults. Outcome expectancies are important factors influencing individuals' risk behaviors, which comprise the expected risks (ER) and expected benefits (EB) associated with risk behaviors. In the current study, we systematically investigated inter-individual differences in adults' outcome expectancies for risk behaviors, considering the general intelligence, brain function, and brain structure. At the intelligence level, individuals with higher intelligence scores showed lower ER but higher EB associated with risk behaviors. At the brain function level, resting-state functional connectivity (FC) between regions within the default mode network is negatively correlated with ER but positively correlated with EB associated with risk behaviors, while FC between the insula and motor cortex is negatively correlated with EB associated with the risk behaviors. At the brain structure level, gray matter volume in posterior cingulate cortex (PCC) and bilateral parahippocampus were negatively correlated with the ER associated with risk behaviors. Furthermore, the relationship between the outcome expectancy associated with risk behaviors and the FC between anterior cingulate cortex and PCC is partially mediated by the general intelligence. The current study provides new insight that furthers our understanding of how individual differences in adults' risk attitudes and behaviors are modulated by general intelligence and reflected in resting-state FC and brain structures related to self-reference and inhibitory control processing.

Comparison of Food Cue-Evoked and Resting-State Functional Connectivity in Obesity

OBJECTIVE

Obesity is associated with differences in task-evoked and resting-state functional brain connectivity (FC). However, no studies have compared obesity-related differences in FC evoked by high-calorie food cues from that observed at rest. Such a comparison could improve our understanding of the neural mechanisms of reward valuation and decision making in the context of obesity.

METHODS

The sample included 122 adults (78% female; mean age = 44.43 [8.67] years) with body mass index (BMI) in the overweight or obese range (mean = 31.28 [3.92] kg/m). Participants completed a functional magnetic resonance imaging scan that included a resting period followed by a visual food cue task. Whole-brain FC analyses examined seed-to-voxel signal covariation during the presentation of high-calorie food and at rest using seeds located in the left and right orbitofrontal cortex, left hippocampus, and left dorsomedial prefrontal cortex.

RESULTS

For all seeds examined, BMI was associated with stronger FC during the presentation of high-calorie food, but weaker FC at rest. Regions exhibiting BMI-related modulation of signal coherence in the presence of palatable food cues were largely located within the default mode network (z range = 2.34-4.91), whereas regions exhibiting BMI-related modulation of signal coherence at rest were located within the frontostriatal and default mode networks (z range = 3.05-4.11). All FC results exceeded a voxelwise threshold of p < .01 and cluster-defining familywise error threshold of p < .05.

CONCLUSIONS

These dissociable patterns of FC may suggest separate neural mechanisms contributing to variation in distinct cognitive, psychological, or behavioral domains that may be related to individual differences in risk for obesity.

Neuroendocrinological mechanisms underlying impulsive and compulsive behaviors in obesity: a narrative review of fMRI studies

Impulsivity and compulsivity are multidimensional constructs that are increasingly considered determinants of obesity. Studies using functional magnetic resonance imaging (fMRI) have provided insight on how differences in brain response during tasks exploring facets of impulsivity and compulsivity relate to the ingestive behaviors that support the etiology and maintenance of obesity. In this narrative review, we provide an overview of neuroimaging studies exploring impulsivity and compulsivity factors as they relate to weight status. Special focus will be placed on studies examining the impulsivity-related dimensions of attentional bias, delayed gratification and emotion regulation. Discussions of compulsivity within the context of obesity will be restricted to fMRI studies investigating habit formation and response flexibility under shifting contingencies. Further, we will highlight neuroimaging research demonstrating how alterations in neuroendocrine functioning are linked to excessive food intake and may serve as a driver of the impulsive and compulsive behaviors observed in obesity. Research on the associations between brain response with neuroendocrine factors, such as insulin, peptide YY (PYY), leptin, ghrelin and glucagon-like peptide 1 (GLP-1), will be reviewed.

Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases

The human brain is intrinsically organized into resting‐state networks (RSNs). Currently, several human brain functional atlases are used to define the spatial constituents of these RSNs. However, there are significant concerns about interatlas variability. In response, we undertook a quantitative comparison of the five major RSNs (default mode [DMN], salience, central executive, sensorimotor, and visual networks) across currently available brain functional atlases (n = 6) in which we demonstrated that (a) similarity between atlases was modest and positively linked to the size of the sample used to construct them; (b) across atlases, spatial overlap among major RSNs ranged between 17 and 76% (mean = 39%), which resulted in variability in their functional connectivity; (c) lower order RSNs were generally spatially conserved across atlases; (d) among higher order RSNs, the DMN was the most conserved across atlases; and (e) voxel‐wise flexibility (i.e., the likelihood of a voxel to change network assignment across atlases) was high for subcortical regions and low for the sensory, motor and medial prefrontal cortices, and the precuneus. In order to facilitate RSN reproducibility in future studies, we provide a new freely available Consensual Atlas of REsting‐state Networks, based on the most reliable atlases.

Salience network connectivity is reduced by a meal and influenced by genetic background and hypothalamic gliosis

Background/Objectives:

The salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function.

Subjects/Methods:

Monozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders.

Results:

SN connectivity was reduced by meal ingestion (β=−0.20; P<0.001). Inherited influences on both pre- and post-meal connectivity were present (ICC MZ twins 26%, P<0.05 and 47%, P<0.001, respectively), but not percentage change in response to the meal. SN connectivity in response to a meal did not differ between participants with obesity and of normal weight (χ2(1)=0.93; P=0.33). However, when participants were classified as having high or low signs of MBH gliosis, the high MBH gliosis group failed to reduce the connectivity in response to a meal (z=−1.32; P=0.19). Excluding genetic confounders, the percentage change in SN connectivity by a meal correlated to body fat percentage (r=0.24; P<0.01).

Conclusions:

SN connectivity was reduced by a meal, indicating potential participation of the SN in control of feeding. The strength of SN connectivity is inherited, but the degree to which SN connectivity is reduced by eating appears to be influenced by adiposity and the presence of hypothalamic gliosis.

Inhibitory control mediates a negative relationship between body mass index and intelligence: A neurocognitive investigation

The structure and function of the human brain is closely related to cognitive processes of the mind and physiological processes of the body, suggesting that an intricate relationship exists between cognitive health, body health, and underlying neural architecture. In the current study, morphometric differences in cortical and subcortical gray matter regions, white matter integrity, and resting-state functional connectivity was assessed to determine what combinations of neural variables best explain an interconnected behavioral relationship between body mass index (BMI), general intelligence, and specific measures of executive function. Data for 82 subjects were obtained from the Nathan Kline Institute Rockland Sample. Behavioral results indicated a negative relationship between BMI and intelligence, which exhibited mediation by an inhibitory measure of executive function. Neural analyses further revealed generally contrasting associations of BMI, intelligence, and executive function with cortical morphometric regions important for inhibitory control and directed attention. Moreover, BMI related to morphometric alterations in components of a frontolimbic network, namely reduced thickness in the anterior cingulate cortex and ventromedial prefrontal cortex, whereas intelligence and inhibitory control primarily related to increased thickness and volume in parietal regions, as well as significantly increased across-network connectivity of visual and default mode resting-state networks. These results propose that medial prefrontal structure and interconnected frontolimbic and frontoparietal networks are important to consider in the relationship between BMI, intelligence, and executive function.

Metabolic-inflammatory status as predictor of clinical outcome at 1-year follow-up in patients with first episode psychosis

BACKGROUND

Metabolic abnormalities and peripheral inflammation have been increasingly reported in patients at the onset of psychosis and associated with important physical health disorders and increased mortality. However, the impact of an abnormal metabolic-inflammatory status on the psychiatric outcome of these patients has not yet been investigated.

OBJECTIVES

The aims of this study were 1) to explore whether, in a sample of patients at their first episode of psychosis (FEP), an overall metabolic-inflammatory status may be measured, by combining metabolic and inflammatory variables in metabolic-inflammatory factors; 2) to explore the association between these factors and clinical outcome at 1-year follow-up (FU), in terms of symptoms severity and treatment response.

METHODS

In this longitudinal study we recruited 42 FEP patients and 46 healthy controls (HC) matched with patients for age, gender and ethnicity. At baseline (T1) we measured high sensitivity C-reactive protein (hsCRP) as biomarker of inflammation, and body mass index (BMI), lipid profile and gluco-metabolic parameters (glycated hemoglobin (HbA1c) and fasting glucose) as metabolic variables. A principal component analysis (PCA) was then used to reduce the dimensionality of the dataset accounting for both inflammation and metabolic status. In FEP patients, we assessed symptoms severity at T1 and at 1-year FU (T2) as well as treatment response to antipsychotics at T2.

RESULTS

at T1, FEP showed higher HbA1c (p = 0.034), triglycerides (TG) (p = 0.045) and BMI (p = 0.026) than HC. PCA identified 3 factors: factor 1 accounting for hsCRP, TG and BMI, factor 2 accounting for LDL and cholesterol, and factor 3 accounting for fasting glucose and HbA1c. Factor 1 was associated with T1 negative symptoms severity (p = 0.021) and predicted T2 positive (p = 0.004) and overall symptoms severity (0.001), as well as general psychopathology (p < 0.001) and T2 treatment response (p = 0.007).

CONCLUSION

In this sample of FEP patients, inflammation and metabolism, closely correlated at the onset of psychosis, proved to play a key role as predictors of the clinical course of psychosis when combined in a single factor. These findings offer an important potential target for early screening and interventions.

Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia

BACKGROUND

The functional architecture of resting-state networks (RSNs) is defined by their connectivity and metastability. Disrupted RSN connectivity has been amply demonstrated in schizophrenia while the role of metastability remains poorly defined. Here, we undertake a comprehensive characterisation of RSN organization in schizophrenia and test its contribution to the clinical profile of this disorder.

METHODS

We extracted RSNs representing the default mode (DMN), central executive (CEN), salience (SAL), language (LAN), sensorimotor (SMN), auditory (AN) and visual (VN) networks from resting-state functional magnetic resonance imaging data obtained from patients with schizophrenia (n = 85) and healthy individuals (n = 48). For each network, we computed its functional cohesiveness and integration and used the Kuramoto order parameter to compute metastability. We used stepwise multiple regression analyses to test these RSN features as predictors of symptom severity in patients.

RESULTS

RSN features respectively explained 14%, 17%, 12% and 5% of the variance in positive, negative, anxious/depressive and agitation/disorganization symptoms. Lower functional integration between the DMN, CEN and SMN primarily contributed to positive symptoms. The functional properties of the SAL network were key predictors of all other symptom dimensions; specifically, lower cohesiveness of the SAL, lower integration of this network with the LAN and higher integration with the CEN respectively contributed to negative, anxious/depressive and disorganization symptoms. Increased SAL metastability was associated with negative symptoms.

CONCLUSIONS

These results confirm the primacy of the SAL network for schizophrenia and demonstrate that abnormalities in RSN connectivity and metastability are significant predictors of schizophrenia-related psychopathology.

Baseline brain structural and functional predictors of clinical outcome in the early course of schizophrenia

Although schizophrenia is considered a brain disorder, the role of brain organization for symptomatic improvement remains inadequately defined. We investigated the relationship between baseline brain morphology, resting-state network connectivity and clinical response after 24-weeks of antipsychotic treatment in patients with schizophrenia (n = 95) using integrated multivariate analyses. There was no significant association between clinical response and measures of cortical thickness (r = 0.37, p = 0.98) and subcortical volume (r = 0.56, p = 0.15). By contrast, we identified a strong mode of covariation linking functional network connectivity to clinical response (r = 0.70; p = 0.04), and particularly to improvement in positive (weight = 0.62) and anxious/depressive symptoms (weight = 0.49). Higher internal cohesiveness of the default mode network was the single most important positive predictor. Key negative predictors involved the functional cohesiveness of central executive subnetworks anchored in the frontoparietal cortices and subcortical regions (including the thalamus and striatum) and the inter-network integration between the default mode and sensorimotor networks. The present findings establish links between clinical response and the functional organization of brain networks involved both in perception and in spontaneous and goal-directed cognition, thereby advancing our understanding of the pathophysiology of schizophrenia.

Neurobehavioral correlates of obesity are largely heritable

Obesity is a widespread heritable health condition. Evidence from psychology, cognitive neuroscience, and genetics has proposed links between obesity and the brain. The current study tested whether the heritable variance in body mass index (BMI) is explained by brain and behavioral factors in a large brain imaging cohort that included multiple related individuals. We found that the heritable variance in BMI had genetic correlations 0.25–0.45 with cognitive tests, cortical thickness, and regional brain volume. In particular, BMI was associated with frontal lobe asymmetry and differences in temporal-parietal perceptual systems. Further, we found genetic overlap between certain brain and behavioral factors. In summary, the genetic vulnerability to BMI is expressed in the brain. This may inform intervention strategies.

Recent molecular genetic studies have shown that the majority of genes associated with obesity are expressed in the central nervous system. Obesity has also been associated with neurobehavioral factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioral factors were associated with the heritable variance in obesity measured by body mass index (BMI) in the Human Connectome Project (n = 895 siblings). Phenotypically, cortical thickness findings supported the “right brain hypothesis” for obesity. Namely, increased BMI is associated with decreased cortical thickness in right frontal lobe and increased thickness in the left frontal lobe, notably in lateral prefrontal cortex. In addition, lower thickness and volume in entorhinal-parahippocampal structures and increased thickness in parietal-occipital structures in participants with higher BMI supported the role of visuospatial function in obesity. Brain morphometry results were supported by cognitive tests, which outlined a negative association between BMI and visuospatial function, verbal episodic memory, impulsivity, and cognitive flexibility. Personality–BMI correlations were inconsistent. We then aggregated the effects for each neurobehavioral factor for a behavioral genetics analysis and estimated each factor’s genetic overlap with BMI. Cognitive test scores and brain morphometry had 0.25–0.45 genetic correlations with BMI, and the phenotypic correlations with BMI were 77–89% explained by genetic factors. Neurobehavioral factors also had some genetic overlap with each other. In summary, obesity as measured by BMI has considerable genetic overlap with brain and cognitive measures. This supports the theory that obesity is inherited via brain function and may inform intervention strategies.

Hallmarks of Brain Aging: Adaptive and Pathological Modification by Metabolic States

During aging, the cellular milieu of the brain exhibits tell-tale signs of compromised bioenergetics, impaired adaptive neuroplasticity and resilience, aberrant neuronal network activity, dysregulation of neuronal Ca2+ homeostasis, the accrual of oxidatively modified molecules and organelles, and inflammation. These alterations render the aging brain vulnerable to Alzheimer's and Parkinson's diseases and stroke. Emerging findings are revealing mechanisms by which sedentary overindulgent lifestyles accelerate brain aging, whereas lifestyles that include intermittent bioenergetic challenges (exercise, fasting, and intellectual challenges) foster healthy brain aging. Here we provide an overview of the cellular and molecular biology of brain aging, how those processes interface with disease-specific neurodegenerative pathways, and how metabolic states influence brain health.

Multivariate Associations Among Behavioral, Clinical, and Multimodal Imaging Phenotypes in Patients With Psychosis

IMPORTANCE

Alterations in multiple neuroimaging phenotypes have been reported in psychotic disorders. However, neuroimaging measures can be influenced by factors that are not directly related to psychosis and may confound the interpretation of case-control differences. Therefore, a detailed characterization of the contribution of these factors to neuroimaging phenotypes in psychosis is warranted.

OBJECTIVE

To quantify the association between neuroimaging measures and behavioral, health, and demographic variables in psychosis using an integrated multivariate approach.

DESIGN, SETTING, AND PARTICIPANTS

This imaging study was conducted at a university research hospital from June 26, 2014, to March 9, 2017. High-resolution multimodal magnetic resonance imaging data were obtained from 100 patients with schizophrenia, 40 patients with bipolar disorder, and 50 healthy volunteers; computed were cortical thickness, subcortical volumes, white matter fractional anisotropy, task-related brain activation (during working memory and emotional recognition), and resting-state functional connectivity. Ascertained in all participants were nonimaging measures pertaining to clinical features, cognition, substance use, psychological trauma, physical activity, and body mass index. The association between imaging and nonimaging measures was modeled using sparse canonical correlation analysis with robust reliability testing.

MAIN OUTCOMES AND MEASURES

Multivariate patterns of the association between nonimaging and neuroimaging measures in patients with psychosis and healthy volunteers.

RESULTS

The analyses were performed in 92 patients with schizophrenia (23 female [25.0%]; mean [SD] age, 27.0 [7.6] years), 37 patients with bipolar disorder (12 female [32.4%]; mean [SD] age, 27.5 [8.1] years), and 48 healthy volunteers (20 female [41.7%]; mean [SD] age, 29.8 [8.5] years). The imaging and nonimaging data sets showed significant covariation (r = 0.63, P < .001), which was independent of diagnosis. Among the nonimaging variables examined, age (r = -0.53), IQ (r = 0.36), and body mass index (r = -0.25) were associated with multiple imaging phenotypes; cannabis use (r = 0.23) and other substance use (r = 0.33) were associated with subcortical volumes, and alcohol use was associated with white matter integrity (r = -0.15). Within the multivariate models, positive symptoms retained associations with the global neuroimaging (r = -0.13), the cortical thickness (r = -0.22), and the task-related activation variates (r = -0.18); negative symptoms were mostly associated with measures of subcortical volume (r = 0.23), and depression/anxiety was associated with measures of white matter integrity (r = 0.12).

CONCLUSIONS AND RELEVANCE

Multivariate analyses provide a more accurate characterization of the association between brain alterations and psychosis because they enable the modeling of other key factors that influence neuroimaging phenotypes.

Cognitive Control of Eating: the Role of Memory in Appetite and Weight Gain

PURPOSE OF REVIEW

The present review organises the recent literature on the role of memory in eating behaviours and provides an overview of the current evidence relating to the associations between memory and weight gain.

RECENT FINDINGS

Research over the last few years has highlighted working memory as an important cognitive process that underpins many aspects of appetite control. Recent work on episodic memory and appetite has replicated work showing that manipulating memory for recent eating affects later consumption and extended this work to examine associations between individual differences in memory and eating behaviours. Poorer episodic memory ability is related to a reduced sensitivity to internal states of hunger and satiety and a tendency towards uncontrolled eating. There is also recent evidence to suggest that working memory and episodic memory impairments are related to weight gain and high BMI. Working memory and episodic memory are core cognitive processes that are critical for food-related decision-making, and disruption to these processes contributes to problems with appetite control and weight gain, which suggests that weight loss programmes might be improved by the addition of cognitive training.

Higher body mass index is associated with reduced posterior default mode connectivity in older adults

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m²  ± 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp 38:3502-3515, 2017. © 2017 Wiley Periodicals, Inc.