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Introduction: Evidence suggests an inverse correlation between smoking and Parkinson's disease (PD), yet the mechanisms remain unclear. This study examines the changing risk relationship between smoking and PD diagnosis using alcohol consumption, another reward-driven behavior, as a comparative measure., Methods: A nested case-control study was conducted using the UK Biobank (UKBB) database. Participants in the prediagnostic phase of PD were identified, and self-reported data on tobacco and alcohol use were analyzed employing conditional binary logistic regression. Polynomial and piece-wise regression models were employed to discern shifting associations with PD over time., Results: Of 502,304 participants (63 ± 5.3 years, 63 % male), 3049 prediagnostic PD cases were identified. Non-smokers had a heightened PD risk, and this association strengthened closer to diagnosis. The odds ratio (OR [95 % CI]) associated with PD in non-smokers was 2.02 [1.07-3.81] 1-4 years before diagnosis, compared to 1.36 [1.02-1.83] at >10-year intervals (linear trend, p = 0.012). The time trajectory of ORs was best depicted by a quadratic function, identifying a shift in risk 7.5 years before diagnosis documentation. Similar patterns emerged among alcohol non-consumers, with an 8.5-year interval inflection point., Conclusion: This study identified two disparate risk trajectories among non-smokers: an initial low-amplitude increased risk at prolonged prediagnostic intervals possibly related to genetic/personality factors, followed by a sharp escalation in risk association commencing 7-8 years before diagnosis, possibly propelled by reverse causality. Similar trends in alcohol consumption reinforce these conclusions. These findings could suggest that smoking cessation may serve as an early indicator of PD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Obesity and hypothalamic inflammation are causally related. It is unclear whether this neuroinflammation precedes or results from obesity. Animal studies show that an increase in food intake can lead to hypothalamic inflammation, but hypothalamic inflammation can create a feedback loop that further increases food intake. Internal and external factors mediate patterns of food intake and how it can affect the hypothalamus. Measures of water diffusivity in magnetic resonance imaging of the brain such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) are associated with grey matter inflammation. Here, we investigated how those measures are associated with obesity-related variables in groups of young and older adults. We found relationships between decreased diffusivity and obesity markers in young adults. In older adults, obesity and comorbidities were also related to significant changes in diffusivity. Here, diffusivity was strongly associated with body mass index (BMI) and blood levels of C-reactive protein (CRP) in multiple subcortical regions, rather than only the hypothalamus. Our results suggest that diffusivity measures can be used to investigate obesity-associated changes in the brain that can potentially reflect neuroinflammation. The connection seen between subcortical inflammation and obesity opens the conversation on preventative interventions needed to reduce the effects of obesity at all stages in life., Competing Interests: Declaration of competing Interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms., (© 2024. The Author(s).)

Animal studies indicate that a high-fat/high-sugar diet (HFS) can change dopamine signal transmission in the brain, which could promote maladaptive behavior and decision-making. Such diet-induced changes may also explain observed alterations in the dopamine system in human obesity. Genetic variants that modulate dopamine transmission have been proposed to render some individuals more prone to potential effects of HFS. The objective of this study was to investigate the association of HFS with dopamine-dependent cognition in humans and how genetic variations might modulate this potential association. Using a questionnaire assessing the self-reported consumption of high-fat/high-sugar foods, we investigated the association with diet by recruiting healthy young men that fall into the lower or upper end of that questionnaire (low fat/sugar group: LFS, n = 45; high fat/sugar group: HFS, n = 41) and explored the interaction of fat and sugar consumption with COMT Val 158 Met and Taq1A genotype. During functional magnetic resonance imaging (fMRI) scanning, male participants performed a working memory (WM) task that probes distractor-resistance and updating of WM representations. Logistic and linear regression models revealed no significant difference in WM performance between the two diet groups, nor an interaction with COMT Val 158 Met or Taq1A genotype. Neural activation in task-related brain areas also did not differ between diet groups. Independent of diet group, higher BMI was associated with lower overall accuracy on the WM task. This cross-sectional study does not provide evidence for diet-related differences in WM stability and flexibility in men, nor for a predisposition of COMT Val 158 Met or Taq1A genotype to the hypothesized detrimental effects of an HFS diet. Previously reported associations of BMI with WM seem to be independent of HFS intake in our male study sample., Competing Interests: Declaration of competing interest No potential conflicts of interest relevant to this article were reported., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Sleep disturbances are increasingly recognized as adversely affecting brain health in aging. Our aim was to investigate interrelations between subjective sleep-related symptoms, obesity, cardiometabolic disorders, brain structure and cognitive decline in a population-based aging sample., Methods: Data were extracted from the UK Biobank for anthropometric and demographic information, self-reported sleep behaviours, cardiometabolic measures, structural brain magnetic resonance imaging and cognitive test scores. "Sleep-related symptoms" (SRS) were measured using four questionnaire items: loud snoring, daytime sleepiness, likelihood to nap and difficulty getting up in the morning. Associations were tested using a structural equation model (SEM), adjusted for confounders. Further, multiple regression analysis was used to test for direct relationships between SRS and specific cognitive domains., Results: Among 36,468 participants with an average age of 63.6 (SD 7.5) years and 46.7% male, we found that SRS were associated with obesity and several pre-existing cardiometabolic disturbances. In turn, cardiometabolic disorders were associated with increased white matter hyperintensities and cortical thinning, which were related to cognitive dysfunction. SRS were also directly related to several structural brain changes and to cognitive dysfunction. Regression analyses showed that SRS were directly associated with slower reaction times, and lower scores in fluid intelligence, working memory and executive function., Conclusions: Self-reported sleep-related symptoms were associated with cognitive dysfunction directly and through pre-existing cardiometabolic disorders and brain structural alterations. These findings provide evidence that symptoms of sleep disturbances, here defined primarily by hypersomnolence and snoring, are important risk factors or markers for cognitive dysfunction in an aging population., Competing Interests: Declaration of competing interest JY: Student Award from the Faculty of Medicine, McGill University; FM: Postdoctoral Fellowship from the Fonds de recherche du Quebec – Santé; AD: Unrestricted research grant from the Canadian Institutes for Health Research; EO: none; AL: research support Fondation de l’IUCPQ, Fonds de recherche en apnée du sommeil (Alphonse l’Espérance), Reseau de recherche en santé respiratoire du Quebec, consulting fee from Institut national de l'excellence en santé et en services sociaux du Québec and Jazz Pharmaceuticals; TG: none; JK: research support from CIHR, Fonds de recherche du Quebec – Santé, Multiple Sclerosis Society of Canada, Signifier Medical, consulting fees from Powell-Mansfield Inc and Esai Inc, DSMB for Bresotec Inc; MK: Research support including equipment from CIHR, Weston Brain Foundation, Fisher Paykel, Philips, Vitalaire, The Chest Foundation, Adviory Board for Biron Soins du sommeil; Honorarium for a lecture for eMedEvents; Advisory Pannel for Jazz Pharmaceuticals., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Food-specific go/no-go training might reduce overeating and facilitate weight loss. In this pilot study, we examined whether a food-specific go/no-go training over five weeks, as compared to a non-food-specific training, could produce changes in behavioral and neural responses to food images and body weight. Here, we used a sample of 51 overweight participants divided into training and control groups whose brain activity and food evaluation were measured before and after the training. Compared with the control group, in the training group we found significant reductions in high-calorie food evaluation. We also found lower activations in inhibitory control- and reward-related brain regions in response to high-calorie food images. Further, activation change of the mid-insula in response to the high-calorie food images was positively associated with change in the evaluation of those images. However, we found no evidence for a significant effect of food-specific go/no-go training on body weight change. Our findings highlight that food-specific go/no-go training in overweight individuals can reduce high-calorie food evaluation, but also neural activations in inhibitory control- and reward- related brain regions., (© The Author(s) 2021. Published by Oxford University Press.)

Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity., (© 2023. The Author(s).)

Background: Excess weight in adulthood leads to health complications such as diabetes, hypertension, or dyslipidemia. Recently, excess weight has also been related to brain atrophy and cognitive decline. Reports show that obesity is linked with Alzheimer's disease (AD)-related changes, such as cerebrovascular damage or amyloid-β accumulation. However, to date no research has conducted a direct comparison between brain atrophy patterns in AD and obesity., Objective: Here, we compared patterns of brain atrophy and amyloid-β/tau protein accumulation in obesity and AD using a sample of over 1,300 individuals from four groups: AD patients, healthy controls, obese otherwise healthy individuals, and lean individuals., Methods: We age- and sex-matched all groups to the AD-patients group and created cortical thickness maps of AD and obesity. This was done by comparing AD patients with healthy controls, and obese individuals with lean individuals. We then compared the AD and obesity maps using correlation analyses and permutation-based tests that account for spatial autocorrelation. Similarly, we compared obesity brain maps with amyloid-β and tau protein maps from other studies., Results: Obesity maps were highly correlated with AD maps but were not correlated with amyloid-β/tau protein maps. This effect was not accounted for by the presence of obesity in the AD group., Conclusion: Our research confirms that obesity-related grey matter atrophy resembles that of AD. Excess weight management could lead to improved health outcomes, slow down cognitive decline in aging, and lower the risk for AD.

Theories have suggested that food-specific inhibition training could lead to food devaluation which, in turn, may help people to regulate their eating behavior. In this review, we have synthesized the current literature on this topic by conducting a meta-analysis of studies investigating the effects of food-specific inhibition training on food evaluation. We identified 24 studies-with 36 independent samples, 77 effect sizes, and 3032 participants-that met our inclusion criteria. Effect sizes were analyzed using the robust variance estimation in random effects meta-regression technique. The results indicate that food-specific inhibition training can lead to statistically significant reductions in food evaluation. More specifically, it was observed that the effects of training on participants' food evaluation differed according to the type of evaluation; food-specific inhibition training significantly decreased participants' explicit food evaluation, but not their implicit food evaluation. However, because most of the included studies focused on trained food items and short-term outcomes in normal-weight samples, more research is needed on the continuance of the training effects, as well as on the extent to which effects can be generalized to untrained food items or different populations (e.g., overweight or obese individuals).

Smell perception plays a role in eating behavior and might be involved in the development of obesity. In fact, olfactory function is impaired in obesity and might depend on metabolic health factors. To date, the underlying neural mechanisms remain unclear. Here, we investigate neural processing of food-related odors in normal-weight, overweight and obese individuals. Fifty-three young and healthy participants (28.8 ± 4.4 years, 27 female; 24 normal-weight, 10 overweight, and 19 obese) were presented with high- (chocolate, potato chips) and low-caloric (orange, cucumber) food odors during a functional magnetic resonance imaging (fMRI). We also assessed olfactory identification ability, body mass index (BMI), body fat percentage, insulin resistance, and leptin levels. In brief, olfactory perception of food odors was linked to brain activity in the entorhinal and piriform cortex, and the insula, hippocampus, and amygdala. Insulin resistance was negatively related to olfactory identification. Additionally, perception of sweet versus savory odors was related to a higher brain activity in the right middle/superior frontal gyrus. Finally, we found no effect of obesity status, BMI, metabolic factors, or body fat percentage on neural responses to food odors. Overall, this suggests that food odor processing might depend on factors other than body weight status or associated markers of metabolic health., (Copyright © 2021. Published by Elsevier Ltd.)

Background: Impulsivity increases the risk for obesity and weight gain. However, the precise role of impulsivity in the aetiology of overeating behavior and obesity is currently unknown. Here we examined the relationships between personality-related measures of impulsivity, Uncontrolled Eating, body mass index (BMI), and longitudinal weight changes. In addition, we analyzed the associations between general impulsivity domains and cortical thickness to elucidate brain vulnerability factors related to weight gain., Methods: Students (N = 2318) in their first year of university-a risky period for weight gain-completed questionnaire measures of impulsivity and eating behavior at the beginning of the school year. We also collected their weight at the end of the term (N = 1177). Impulsivity was divided into three factors: stress reactivity, reward sensitivity and lack of self-control. Using structural equation models, we tested a hierarchical relationship, in which impulsivity traits were associated with Uncontrolled Eating, which in turn predicted BMI and weight change. Seventy-one participants underwent T1-weighted MRI to investigate the correlation between impulsivity and cortical thickness., Results: Impulsivity traits showed positive correlations with Uncontrolled Eating. Higher scores in Uncontrolled Eating were in turn associated with higher BMI. None of the impulsivity-related measurements nor Uncontrolled Eating were correlated with longitudinal weight gain. Higher stress sensitivity was associated with increased cortical thickness in the superior temporal gyrus. Lack of self-control was positively associated with increased thickness in the superior medial frontal gyrus. Finally, higher reward sensitivity was associated with lower thickness in the inferior frontal gyrus., Conclusion: The present study provides a comprehensive characterization of the relationships between different facets of impulsivity and obesity. We show that differences in impulsivity domains might be associated with BMI via Uncontrolled Eating. Our results might inform future clinical strategies aimed at fostering self-control abilities to prevent and/or treat unhealthy weight gain., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Overconsumption of high-calorie or unhealthy foods commonly leads to weight gain. Understanding people's neural responses to high-calorie food cues might help to develop better interventions for preventing or reducing overeating and weight gain. In this review, we conducted a coordinate-based meta-analysis of functional magnetic resonance imaging studies of viewing high-calorie food cues in both normal-weight people and people with obesity. Electronic databases were searched for relevant articles, retrieving 59 eligible studies containing 2410 unique participants. The results of an activation likelihood estimation indicate large clusters in a range of structures, including the orbitofrontal cortex (OFC), amygdala, insula/frontal operculum, culmen, as well as the middle occipital gyrus, lingual gyrus, and fusiform gyrus. Conjunction analysis suggested that both normal-weight people and people with obesity activated OFC, supporting that the two groups share common neural substrates of reward processing when viewing high-calorie food cues. The contrast analyses did not show significant activations when comparing obesity with normal-weight. Together, these results provide new important evidence for the neural mechanism underlying high-calorie food cues processing, and new insights into common and distinct brain activations of viewing high-calorie food cues between people with obesity and normal-weight people.

Brain atrophy has been reported in the early stages of Parkinson's disease, but there have been few longitudinal studies. How intrinsic properties of the brain, such as anatomical connectivity, local cell-type distribution and gene expression combine to determine the pattern of disease progression also remains unknown. One hypothesis proposes that the disease stems from prion-like propagation of misfolded alpha-synuclein via the connectome that might cause varying degrees of tissue damage based on local properties. Here, we used MRI data from the Parkinson Progression Markers Initiative to map the progression of brain atrophy over 1, 2 and 4 years compared with baseline. We derived atrophy maps for four time points using deformation-based morphometry applied to T 1 -weighted MRI from 120 de novo Parkinson's disease patients, 74 of whom had imaging at all four time points (50 Men: 24 Women) and 157 healthy control participants (115 Men: 42 Women). In order to determine factors that may influence neurodegeneration, we related atrophy progression to brain structural and functional connectivity, cell-type expression and gene ontology enrichment analyses. After regressing out the expected age and sex effects associated with normal ageing, we found that atrophy significantly progressed over 2 and 4 years in the caudate, nucleus accumbens, hippocampus and posterior cortical regions. This progression was shaped by both structural and functional brain connectivity. Also, the progression of atrophy was more pronounced in regions with a higher expression of genes related to synapses and was inversely related to the prevalence of oligodendrocytes and endothelial cells. In sum, we demonstrate that the progression of atrophy in Parkinson's disease is in line with the prion-like propagation hypothesis of alpha-synuclein and provide evidence that synapses may be especially vulnerable to synucleinopathy. In addition to identifying vulnerable brain regions, this study reveals different factors that may be implicated in the neurotoxic mechanisms leading to progression in Parkinson's disease. All brain maps generated here are available on request., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Context: Chronic obesity is associated with several complications, including cognitive impairment and dementia. However, we have only piecemeal knowledge of the mechanisms linking obesity to central nervous system damage. Among candidate mechanisms are other elements of obesity-associated metabolic syndrome, such as hypertension, dyslipidemia, and diabetes, but also systemic inflammation. While there have been several neuroimaging studies linking adiposity to changes in brain morphometry, a comprehensive investigation of the relationship has so far not been done., Objective: To identify links between adiposity and cognitive dysfunction., Methods: This observational cohort study (UK Biobank), with an 8-year follow-up, included more than 20 000 participants from the general community, with a mean age of 63 years. Only participants with data available on both baseline and follow-up timepoints were included. The main outcome measures were cognitive performance and mediator variables: hypertension, diabetes, systemic inflammation, dyslipidemia, gray matter measures, and cerebrovascular disease (volume of white matter hyperintensities on magnetic resonance imaging)., Results: Using structural equation modeling, we found that body mass index, waist-to-hip ratio, and body fat percentage were positively related to higher plasma C-reactive protein, dyslipidemia, hypertension, and diabetes. In turn, hypertension and diabetes were related to cerebrovascular disease. Finally, cerebrovascular disease was associated with lower cortical thickness and volume and higher subcortical volumes, but also cognitive deficits (largest significant pcorrected = 0.02)., Conclusions: We show that adiposity is related to poor cognition, with metabolic consequences of obesity and cerebrovascular disease as potential mediators. The outcomes have clinical implications, supporting a role for the management of adiposity in the prevention of late-life dementia and cognitive decline., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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.

Previous studies link obesity and components of metabolic health, such as hypertension or inflammation, to increased hospitalizations and mortality of patients with COVID-19. Here, in two overlapping samples of over 1,000 individuals from the UK Biobank we investigate whether metabolic health as measured by waist circumference, dyslipidemia, hypertension, type 2 diabetes, and systemic inflammation is related to increased COVID-19 infection and mortality rate. Using logistic regression and controlling for confounding variables such as socioeconomic status, age, sex or ethnicity, we find that individuals with worse metabolic health (measured on average eleven years prior to 2020) have an increased risk for COVID-19-related death (adjusted odds ratio: 1.75). We also find that specific factors contributing to increased mortality are increased serum glucose levels, systolic blood pressure and waist circumference., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Morys and Dagher.)

Dysregulated neural mechanisms in reward and somatosensory circuits result in an increased appetitive drive for and reduced inhibitory control of eating, which in turn causes obesity. Despite many studies investigating the brain mechanisms of obesity, the role of macroscale whole-brain functional connectivity remains poorly understood. Here, we identified a neuroimaging-based functional connectivity pattern associated with obesity phenotypes by using functional connectivity analysis combined with machine learning in a large-scale (n ~ 2,400) dataset spanning four independent cohorts. We found that brain regions containing the reward circuit positively associated with obesity phenotypes, while brain regions for sensory processing showed negative associations. Our study introduces a novel perspective for understanding how the whole-brain functional connectivity correlates with obesity phenotypes. Furthermore, we demonstrated the generalizability of our findings by correlating the functional connectivity pattern with obesity phenotypes in three independent datasets containing subjects of multiple ages and ethnicities. Our findings suggest that obesity phenotypes can be understood in terms of macroscale whole-brain functional connectivity and have important implications for the obesity neuroimaging community., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Motivation theories of obesity suggest that one of the brain mechanisms underlying pathological eating and weight gain is the dysregulation of dopaminergic circuits. Although these dysregulations likely occur at the microscopic level, studies on grey matter volume report macroscopic differences associated with obesity. One region suggested to play a key role in the pathophysiology of obesity is the nucleus accumbens (NAcc). We performed a meta-analysis of findings regarding NAcc volume and overweight/obesity. We additionally examined whether grey matter volume in the NAcc and other mesolimbic areas depends on the longitudinal trajectory of obesity, using the UK Biobank dataset. To this end, we analysed the data using a latent growth model, which identifies whether a certain variable of interest (eg, NAcc volume) is related to another variable's (body mass index [BMI]) initial values or longitudinal trajectories. Our meta-analysis showed that, overall, NAcc volume is positively related to BMI. However, further analyses revealed that the relationship between NAcc volume and BMI is dependent on age. For younger individuals, such a relationship is positive, whereas, for older adults, it is negative. This was corroborated by our analysis in the UK Biobank dataset, which includes older adults, where we found that a higher BMI was associated with a lower NAcc and thalamus volume. Overall, the present study suggests that increased NAcc volume at a young age might be a vulnerability factor for obesity, whereas, at an older age, decreased NAcc volume with increased BMI might be an effect of prolonged influences of neuroinflammation on the brain., (© 2019 British Society for Neuroendocrinology.)

Theoretical work suggests that obesity is related to enhanced incentive salience of food cues. However, evidence from both behavioral and neuroimaging studies on the topic is mixed. In this work we review the literature on cue reactivity in obesity and perform a preregistered meta-analysis of studies investigating effects of obesity on brain responses to passive food pictures viewing. Further, we examine whether age influences brain responses to food cues in obesity. In the meta-analysis we included 13 studies of children and adults that investigated group differences (obese vs. lean) in responses to food vs. non-food pictures viewing. While we found no significant differences in the overall meta-analysis, we show that age significantly influences brain response differences to food cues in the left insula and the left fusiform gyrus. In the left insula, obese vs. lean brain differences in response to food cues decreased with age, while in the left fusiform gyrus the pattern was opposite. Our results suggest that there is little evidence for obesity-related differences in responses to food cues and that such differences might be mediated by additional factors that are often not considered., (© The Author(s) 2020. Published by Oxford University Press.)

Much of our behaviour is driven by two motivational dimensions-approach and avoidance. These have been related to frontal hemispheric asymmetries in clinical and resting-state EEG studies: Approach was linked to higher activity of the left relative to the right hemisphere, while avoidance was related to the opposite pattern. Increased approach behaviour, specifically towards unhealthy foods, is also observed in obesity and has been linked to asymmetry in the framework of the right-brain hypothesis of obesity. Here, we aimed to replicate previous EEG findings of hemispheric asymmetries for self-reported approach/avoidance behaviour and to relate them to eating behaviour. Further, we assessed whether resting fMRI hemispheric asymmetries can be detected and whether they are related to approach/avoidance, eating behaviour and BMI. We analysed three samples: Sample 1 (n = 117) containing EEG and fMRI data from lean participants, and Samples 2 (n = 89) and 3 (n = 152) containing fMRI data from lean, overweight and obese participants. In Sample 1, approach behaviour in women was related to EEG, but not to fMRI hemispheric asymmetries. In Sample 2, approach/avoidance behaviours were related to fMRI hemispheric asymmetries. Finally, hemispheric asymmetries were not related to either BMI or eating behaviour in any of the samples. Our study partly replicates previous EEG findings regarding hemispheric asymmetries and indicates that this relationship could also be captured using fMRI. Our findings suggest that eating behaviour and obesity are likely to be mediated by mechanisms not directly relating to frontal asymmetries in neuronal activation quantified with EEG and fMRI., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Objective: Binge eating is characterized by episodes of uncontrolled eating, within discrete periods of time. Although it is usually described in obese individuals or as a symptom of Binge Eating Disorder (BED), this behavior can also occur in the normal-weight (NW) population. An interesting premise suggests that impulsivity might contribute to the onset of binge eating and the progression toward weight gain. Drawing upon this evidence, here we explored impulsivity in NW individuals reporting binge-eating episodes through a functional connectivity approach. We hypothesized that, even in the absence of an eating disorder, NW binge eaters would be characterized by connectivity pattern changes in corticostriatal regions implicated in impulsivity, similarly to the results described in BED individuals., Methods: A resting-state functional magnetic resonance imaging study tested 39 NW men and women, with and without binge eating (binge eaters, BE and non-BE). Brain functional connectivity was explored by means of graph theoretic centrality measures and traditional seed-based analysis; trait impulsivity was assessed with self-report questionnaires., Results: The BE group was characterized by a higher degree of trait impulsivity. Brain functional connectivity measures revealed lower degree centrality within the right middle frontal gyrus, left insula/putamen and left temporoparietal regions and a lower functional connectivity between the right middle frontal gyrus and right insula in the BE group., Discussion: The results support previous evidence on BED of altered functional connectivity and higher impulsivity at the roots of overeating behavior, but further extend this concept excluding any potential confounding effect exerted by the weight status., (© 2019 Wiley Periodicals, Inc.)

Emotions can influence our eating behaviors. Facing an acute stressor or being in a positive mood are examples of situations that tend to modify appetite. However, the question of how the brain integrates these emotion-related changes in food processing remains elusive. Here, we designed an emotional priming fMRI task to test if amygdala activity during food pictures differs depending on the emotional context. Fifty-eight female participants completed a novel emotional priming task, in which emotional images of negative, neutral, or positive situations were followed by pictures of either foods or objects. After priming in each trial, participants rated how much they liked the shown foods or objects. We analyzed how brain activity during the contrast "foods > objects" changed according to the emotional context-in the whole brain and in the amygdala. We also examined the potential effect of adiposity (i.e., waist circumference). We observed a higher difference between liking scores for foods and objects after positive priming than after neutral priming. In the left amygdala, activity in the contrast "foods > objects" was higher after neutral priming relative to negative priming. Waist circumference was not significantly related to this emotional priming effect on food processing. Our results suggest that emotional context alters food and nonfood perception, both in terms of liking scores and with regard to engagement of the left amygdala. Moreover, our findings indicate that emotional context has an impact on the salience advantage of food, possibly affecting eating behavior.

Obesity is associated with automatically approaching problematic stimuli, such as unhealthy food. Cognitive bias modification (CBM) could beneficially impact problematic approach behavior. However, it is unclear which mechanisms are targeted by CBM in obesity. Candidate mechanisms include: (1) altering reward value of food stimuli; and (2) strengthening inhibitory abilities. Thirty-three obese adults completed either CBM or sham training during functional magnetic resonance imaging (fMRI) scanning. CBM consisted of implicit training to approach healthy and avoid unhealthy foods. At baseline, approach tendencies towards food were present in all participants. Avoiding vs. approaching food was associated with higher activity in the right angular gyrus (rAG). CBM resulted in a diminished approach bias towards unhealthy food, decreased activation in the rAG, and increased activation in the anterior cingulate cortex. Relatedly, functional connectivity between the rAG and right superior frontal gyrus increased. Analysis of brain connectivity during rest revealed training-related connectivity changes of the inferior frontal gyrus and bilateral middle frontal gyri. Taken together, CBM strengthens avoidance tendencies when faced with unhealthy foods and alters activity in brain regions underpinning behavioral inhibition.

Obese individuals discount future rewards to a higher degree than lean individuals, which is generally considered disadvantageous. Moreover, their decisions are altered more easily by decision-irrelevant cues. Here, we investigated neural correlates of this phenomenon using functional MRI. We tested 30 lean and 26 obese human subjects on a primed delay discounting paradigm using gustatory and visual cues of positive, neutral and negative valence to bias their intertemporal preferences. We hypothesised that activation differences in reward-related and behavioural control areas, and changes in connectivity between these areas, would reflect the effect of these cues. Here, obese subjects were more susceptible to priming with negative gustatory cues towards delayed choices as opposed to lean subjects. This was related to lower activity in the left dorsolateral prefrontal cortex during priming. Modulation of functional connectivity between the dlPFC and the ventromedial PFC by the behavioural priming effect correlated negatively with BMI. This might indicate that default goals of obese individuals were different from those of lean participants, as the dlPFC has been suggested to be involved in internal goal pursuit. The present results further our understanding of the role of the PFC in decision-making and might inform future weight-management approaches based on non-invasive brain stimulation.