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Abstract

Obesity is a major health problem in modern societies. It has been related to abnormal functional organization of brain networks believed to process homeostatic (internal) and/or salience (external) information. This study used resting-state functional magnetic resonance imaging analysis to delineate possible functional changes in brain networks related to obesity. A group of 18 healthy adult participants with obesity were compared with a group of 16 lean participants while performing a resting-state task, with the data being evaluated by independent component analysis. Participants also completed a neuropsychological assessment. Results showed that the functional connectivity strength of the putamen nucleus in the salience network was increased in the obese group. We speculate that this abnormal activation may contribute to overeating through an imbalance between autonomic processing and reward processing of food stimuli. A correlation was also observed in obesity between activation of the putamen nucleus in the salience network and mental slowness, which is consistent with the notion that basal ganglia circuits modulate rapid processing of information. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.

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... Moreover, high BMI was associated with reduced functional cohesion of the DMN in a sample of siblings with and without obesity (Doucet et al., 2018). Importantly, three studies did not find any difference in FC between individuals with obesity, obese and overweight individuals relative to lean BMI controls or any association between BMI and FC in the DMN (Doornweerd et al., 2017;Faul et al., 2019;García-García et al., 2013). ...
... Sub-analysis of Rs-FC data highlighted a main effect of the degree of obesity with the FPN, however declined to mention whether the effect was positive or negative. Two studies did not find differences in FC between OB and CTRL and or any association between BMI and FC in the FPN (Beyer et al., 2017;García-García et al., 2013). Only one study, investigated the association between BMI and the FC of the ECN and reported that high BMI was associated with reduced within network connectivity of the ECN (Doucet et al., 2018). ...
... The sensorimotor network (SMN) was also investigated based on the hypothesis that high BMI may be associated with alterations in processing of the sensory cues. Four studies investigated Rs-FC of the SMN and suggest there is no association between BMI and SMN Rs-FC (Beyer et al., 2017;García-García et al., 2013;Kullmann et al., 2012). Only one study reported reduced FC within the dorsal SMN submodule of the SMN in OB siblings compared to their lean BMI sibling (Doucet et al., 2018). ...
Article
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.
... Multiple task-based functional MRI studies have also shown associations between BMI and brain activations in impulse control and reward processing paradigms [22][23][24][25][26][27][28][29] . During resting conditions, studies reported associations between BMI and connectivity of specific regions [30][31][32][33] and larger networks involved in cognitive control and reward systems [34][35][36] . A recent study suggested regional functional connectivity patterns related to inter-individual variations in obesity phenotypes using machine learning 37,38 . ...
... Further contextualization with manifold eccentricity and graph theoretical parameters indicated segregation of association cortices in individuals with higher BMI. Prior fMRI studies reported atypical intrinsic functional connectivity in individuals with obesity, at both nodal and global network levels, relative to individuals with healthy weight 30,34,35,[101][102][103] . Our findings complement these previous reports focusing on the analysis of connectivity patterns of specific areas [30][31][32]35 alongside prior graph-theoretical analyses 30,34,103 in the context of person-to-person variations in BMI. ...
... Prior fMRI studies reported atypical intrinsic functional connectivity in individuals with obesity, at both nodal and global network levels, relative to individuals with healthy weight 30,34,35,[101][102][103] . Our findings complement these previous reports focusing on the analysis of connectivity patterns of specific areas [30][31][32]35 alongside prior graph-theoretical analyses 30,34,103 in the context of person-to-person variations in BMI. Prior functional connectivity studies found that individuals with obesity showed increased connectivity in nodes belonging to frontoparietal and default mode networks 30,35,101 . ...
Article
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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.
... Likewise, FC within the default mode network (DMN) has been found to reduce as a function of increased BMI [31,33]. Given that FC in the default mode network has been purported to support attention and awareness of internal states, such as appetite or hunger signals [34][35][36], it is surprising that some intensive exercise interventions for individuals with obesity have resulted in reduction of default mode network functional connectivity [37]. Besides these large-scale resting-state networks alterations, increased FC has also been found in smaller reward-related regions such as the middle frontal gyrus, left ventromedial prefrontal cortex and lateral orbitofrontal cortex [38,39] as well as greater resting-state FC between these reward-related regions and self-control regions in children with obesity [38]. ...
... Other than gender, most studies did not measure additional biopsychosocial sample characteristics related to obesity other than BMI (see Table 1). Five studies considered hunger levels at the time of scanning [32,34,39,46,47], three studies considered comorbid diabetes [30,34,48], three considered binge-eating [34,49,50] and only two considered comorbid psychiatric disorders [49,51]. Factors including medication, hypertension, hyperglycaemia, high cholesterol, insulin sensitivity, history of metabolic disorder, and sedentary lifestyle were also seldom considered, with each factor only having been considered by no more than a single study (see Table 1 below). ...
... Other than gender, most studies did not measure additional biopsychosocial sample characteristics related to obesity other than BMI (see Table 1). Five studies considered hunger levels at the time of scanning [32,34,39,46,47], three studies considered comorbid diabetes [30,34,48], three considered binge-eating [34,49,50] and only two considered comorbid psychiatric disorders [49,51]. Factors including medication, hypertension, hyperglycaemia, high cholesterol, insulin sensitivity, history of metabolic disorder, and sedentary lifestyle were also seldom considered, with each factor only having been considered by no more than a single study (see Table 1 below). ...
Article
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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.
... A seed-based correlation study observed decreased FC between hypothalamus and left insula and between hypothalamus and dorsal anterior cingulate cortex (dACC) after a prolonged fast in OB (Wijngaarden MA et al., 2015), suggesting abnormal cross talk between SN and regions important for homeostasis. Further, regions within SN showed hyperactivation in response to food pictures stimuli in obese individuals (Garcia-Garcia I et al., 2013;Stoeckel LE et al., 2008;Volkow ND et al., 2011) and SN has been reported to involve rapid processing of internal/interoceptive salient stimuli (Garcia-Garcia I et al., 2013). The SN integrates processed internal sensory information on which ECN operates to regulate reward and cognitive functions (Seeley WW et al., 2007). ...
... A seed-based correlation study observed decreased FC between hypothalamus and left insula and between hypothalamus and dorsal anterior cingulate cortex (dACC) after a prolonged fast in OB (Wijngaarden MA et al., 2015), suggesting abnormal cross talk between SN and regions important for homeostasis. Further, regions within SN showed hyperactivation in response to food pictures stimuli in obese individuals (Garcia-Garcia I et al., 2013;Stoeckel LE et al., 2008;Volkow ND et al., 2011) and SN has been reported to involve rapid processing of internal/interoceptive salient stimuli (Garcia-Garcia I et al., 2013). The SN integrates processed internal sensory information on which ECN operates to regulate reward and cognitive functions (Seeley WW et al., 2007). ...
Article
Previous fMRI studies have showed obesity-related alterations in intrinsic functional connectivity (FC) within and between different resting-state networks (RSNs). However, few studies have examined dynamic functional connectivity (DFC). Thus, we employed resting-state fMRI with independent component analysis (ICA) and DFC analysis to investigate alterations in FC within and between RSNs in 56 individuals with obesity (OB) and 46 normal-weight controls (NW). ICA identified 6 RSNs including basal ganglia (BG), salience-(SN), right-(rECN)/left-(lECN) executive-control and anterior-(aDMN)/posterior-(pDMN) default-mode network. The DFC analysis identified four FC states. OB compared to NW had more occurrences and a longer mean dwell time (MDT) in state 2 (positive connectivity of BG with other RSN) and also had higher FC of BG-SN in other states. Body mass index (BMI) was positively correlated with MDT and FCs of BG-aDMN (state 2) and BG-SN (state 4). DFC analysis within more refined nodes of RSNs showed that OB had more occurrences and a longer MDT in state 1 in which caudate had positive connections with the other network nodes. The findings suggest an association between caudate-related and BG-related positive FC in obesity, which was not revealed by traditional FC analysis, highlighting the utility of adding DFC to more conventional methods.
... Our results showing that higher presence of VAT is associated with lower FA, are in line with those of other studies aimed at analysing the possible association between body fat mass with brain structure and function principally in obese and elderly people. There is evidence suggesting that adiposity and obesity are associated with altered functional connectivity across different brain regions 9 and with normal-weight population has been reported that higher VAT is associated with lower functional brain connectivity 5 . Additionally, it seems that several multiple measures of brain microstructure impairs with adiposity 10 . ...
... In summary, it seems that adiposity provides both positive and negative effects on brain connectivity. In fact, obesity studies reported that visceral adiposity and BMI -which could be interpreted as the total fat present in the body in overweight and obese populations 5 -are negatively associated with brain connectivity [9][10][11] , while other studies with normal weight populations such as Croll et al. 12 and ours observed that TFM is positively associated with brain connectivity. According to this information, the authors suggest that the presence of fat may enhance brain connectivity and, probably, overall brain health. ...
Article
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A lack of exercise leads to being overweight or obese affecting regional brain structure and functional connectivity associated with impaired cognitive function and dementia. In recent decades, several studies of healthy individuals suggest that adiposity may also produce negative independent effects on the brain. We aimed to investigate the relationship between body composition – total fat mass (TFM) and visceral adipose tissue (VAT) – with white matter (WM) integrity using a whole-brain approach in military pilots. Twenty-three military helicopter pilots (Mage = 36.79; SD = 8.00; MBMI = 25.48; SD = 2.49) took part in the study. Brain volumes were studied using diffusion tensor imaging technique by means of a 3T Magnetom Tim Trio. Measurements of body mass index (BMI), TFM and VAT were obtained using Dual-energy X-ray Absorptiometry (DXA). The results showed that, on one hand, higher TFM was associated with higher white matter fractional anisotropy (FA) and, on the other hand, higher VAT was associated with lower FA. Data showed that TFM and VAT are the critical factors underlying WM integrity in combat helicopter pilots. The authors suggest that fat presence enhance brain connectivity while there is no excess, specifically in VAT.
... Moreover, previous studies have shown similarities between drug addiction and food addiction in individuals with overweight and obesity [27,28]. These reward-related brain regions exhibit abnormal activation during food-or addiction-related stimuli [29,30]. Studies have shown that marijuana can increase activity in many brain regions, especially reward pathways, including the bilateral amygdala, hippocampus, and OFC [25]. ...
... Based on resting-state fMRI imaging data, we found a positive correlation between food cravings and the functional connection between the bilateral OFC, which can completely mediate the relationship between BMI and proactive control. This result partially verifies Hypothesis 3. Previous neuroimaging studies have shown that overweight or obese participants exhibited abnormal activation in food-related reward tasks [29,30]. Similar to the results found in the food-tasting task, OFC activation indicates pleasantness [47,48]. ...
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Background: Overweight people have been revealed to have poor cognitive flexibility. Cognitive flexibility reflects proactive and reactive control abilities. However, the impairment had not been explicitly positioned at the cognitive stage. Therefore, this study provides increased support for impairment of cognitive flexibility due to overweight. Method: The study included 34 overweight and 35 normal-weight participants. They were required to complete the food and flower target AX-continuous performance test (AX-CPT), including the resting-state fMRI and cue-triggered food craving subscales. We compared the performance difference between the two tasks. Furthermore, we investigated whether the cue-triggered food cravings and the corresponding brain regions mediated the effect of overweight on the two control mechanisms. Result: Significant differences were found only in the food target AX-CPT task, where overweight participants performed worse. Cue-triggered food cravings mediated this relationship. Additionally, we found that the brain regions associated with cue-triggered food cravings (bilateral SFG) can completely mediate the relationship between BMI and the z-value of the fat mass index and sensitivity to proactive control. Conclusion: In the food target task, overweight participants performed worse in both control mechanisms. Moreover, we also revealed the potential mechanism by which being overweight might affect the two control mechanisms through cue-triggered food cravings.
... Normal ingestive behaviour is under the control of the extended reward network, which includes brain regions from the core reward network including the nucleus accumbens, ventral tegmental area and the substantia nigra, and is regulated by cognitive network regions including the prefrontal cortex 88,89 . The extended reward network is involved in the processing of reward stimuli and modulation of food-seeking behaviour 90,91 , inhibitory control 92 , cognitive performance monitoring 93,94 , interoceptive and sensory awareness 88,95,96 , and integrating salient information to make decisions regarding food intake [97][98][99][100] . This processing includes brain regions concerned with interconnecting brain networks such as the reward network, the salience network, the emotional regulation network, the somatosensory system and the cortical inhibition network (prefrontal control) 31,33,90,99 ( fig. 2). ...
... This processing includes brain regions concerned with interconnecting brain networks such as the reward network, the salience network, the emotional regulation network, the somatosensory system and the cortical inhibition network (prefrontal control) 31,33,90,99 ( fig. 2). The salience network is responsible for monitoring the homeostatic state of the body to make adaptive adjustments to real or expected disturbances in homeostasis through the autonomic nervous system, as well as behavioural responses 98,101 . In food addiction (as in substance abuse), the saliency of a specific type of reward (food or drug) becomes greater at the expense of other rewards 32,48 . ...
Article
Normal eating behaviour is coordinated by the tightly regulated balance between intestinal and extra-intestinal homeostatic and hedonic mechanisms. By contrast, food addiction is a complex, maladaptive eating behaviour that reflects alterations in brain–gut–microbiome (BGM) interactions and a shift of this balance towards hedonic mechanisms. Each component of the BGM axis has been implicated in the development of food addiction, with both brain to gut and gut to brain signalling playing a role. Early-life influences can prime the infant gut microbiome and brain for food addiction, which might be further reinforced by increased antibiotic usage and dietary patterns throughout adulthood. The ubiquitous availability and marketing of inexpensive, highly palatable and calorie-dense food can further shift this balance towards hedonic eating through both central (disruptions in dopaminergic signalling) and intestinal (vagal afferent function, metabolic endotoxaemia, systemic immune activation, changes to gut microbiome and metabolome) mechanisms. In this Review, we propose a systems biology model of BGM interactions, which incorporates published reports on food addiction, and provides novel insights into treatment targets aimed at each level of the BGM axis.
... Research has demonstrated that people with obesity show abnormal activation in core structures (insula and ACC) of the salience network during exposure to visual food stimuli [59,60]. Notably, too, at rest, people with higher BMIs can show abnormal intrinsic connectivity within the salience network [61][62][63]. Our findings extend previous work by showing how intra-cortical myelin of the salience network is reduced among young adults with higher BMIs. ...
... Hence, we speculate that different levels of intra-cortical myelin within the VAN may underlie the functional integrity of this network. In tandem with previous research [61], our findings suggest that abnormal intra-cortical myelination within the salience network may contribute to overeating and/or reduced energy expenditure in obesity through creating imbalances between autonomic homeostatic processing and salient reward processing of visual food cues. ...
Article
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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.
... These findings were predominantly observed in uni-and heteromodal association cortices that encompass integrative default mode and frontoparietal networks and are reflective of an increased differentiation of these areas to other brain networks. Prior fMRI studies reported atypical intrinsic functional connectivity in individuals with obesity, at both local node and global network levels, relative to individuals with a healthy weight Chen et al., 2018;García-García et al., 2013Park et al., 2016Park et al., , 2018. Our findings complement these previous reports focusing on the analysis of connectivity patterns of specific areas Lips et al., 2014;Park et al., 2015) alongside prior graph theoretical analyses (García-García et al., 2015;Park et al., 2016Park et al., , 2018 in the context of person-to-person variations in BMI. ...
... Our findings complement these previous reports focusing on the analysis of connectivity patterns of specific areas Lips et al., 2014;Park et al., 2015) alongside prior graph theoretical analyses (García-García et al., 2015;Park et al., 2016Park et al., , 2018 in the context of person-to-person variations in BMI. Seed-based and graph theoretical functional connectivity studies found that individuals with obesity showed increased connectivity in nodes belonging to frontoparietal and default mode networks, relative to individuals with healthy weight García-García et al., 2013. These findings are complemented by studies reporting positive associations between overall connectivity degree and broad variability in BMI, again with frequent findings in transmodal areas (Park et al., 2016(Park et al., , 2018. ...
Preprint
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A bstract 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 association between functional connectome organization and BMI variations. We capitalized on connectome manifold learning techniques, which represent macroscale functional connectivity patterns 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 an increasingly segregated modular architecture and a disruption in the hierarchical integration of different brain system. Transcriptomic decoding and subsequent gene enrichment analyses identified genes previously implicated in genome-wide associations to BMI and specific cortical, striatal, and cerebellar cell types. These findings provide novel insights for functional connectome substrates of BMI variations in healthy young adults and point to potential molecular associations.
... Recent studies have used resting-state functional magnetic resonance imaging (rs-fMRI) technology to understand the neural mechanisms underlying obesity from the perspective of brain intrinsic functional organization. Some studies have shown that higher BMI is associated with greater resting-state functional connectivity (rsFC) of the posterior module of DMN [5] and salience network [6], as well as reduced rsFC within DMN [7,8], salience network [7,9], and frontoparietal [7] networks. Other studies have observed higher internetwork rsFC between DMN and sensorimotor network in obesity [7], and speculated that this might relate to altered internal states and external information processing, which in turn could contribute to weight gain. ...
... Task fMRI studies have shown an increased response to food cues in the left anterior and right mid insular cortex for obese subjects relative to normal-weight individuals [36], and the activation in the anterior insula aroused by food cues is positively associated with BMI [37]. Two studies on obesity have demonstrated that insula showed lower HC with primary and secondary auditory cortices [5], and greater FC with ACC, amygdala, and basal ganglia [6], suggesting the insulainvolved functional reorganization with BMI increase. Patients with anorexia nervosa exhibited lower IHFC in insula relative to healthy controls, further suggesting that the functional interplay between bilateral insula is associated with abnormal salience encoding for food [23]. ...
Article
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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. 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. 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). 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.
... Garcia-Garcia et al. 2013 [33] used non-invasive diffusion tensor imaging to find the correlation between the functional neuroimaging indices of obese patients. The functional indices contain amplitude low-frequency fluctuation (AlF) and regional homogeneity ...
Preprint
Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy dropped from 80 to 75 years, as obese people struggle with different chronic diseases. This report will address the problems of obesity in children and adults using ML datasets to feature, predict, and analyze the causes of obesity. By engaging neural ML networks, we will explore neural control using diffusion tensor imaging to consider body fats, BMI, waist \& hip ratio circumference of obese patients. To predict the present and future causes of obesity with ML, we will discuss ML techniques like decision trees, SVM, RF, GBM, LASSO, BN, and ANN and use datasets implement the stated algorithms. Different theoretical literature from experts ML \& Bioinformatics experiments will be outlined in this report while making recommendations on how to advance ML for predicting obesity and other chronic diseases.
... Interestingly, there is a growing body of literature investigating various aspects of reading, reading dysfunction, and functional connectivity networks. For example, one investigation used a Word Reading subtest from the Wechsler Individual Achievement Test-Second Edition WIAT-II, [WIAT-II] [37] and found that, in typically developing children (ages [8][9][10][11][12][13][14], word reading was associated with increased functional connectivity between the left precentral gyrus and other motor regions. In addition, the authors found that the connectivity associated with word reading, between left fusiform gyrus and either the left inferior frontal gyrus opercularis (Broca's area) and the left inferior parietal lobule was negative in children, but positive in adults, suggesting that positive connectivity between these regions was beneficial for word reading in adults, but not children. ...
Article
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Scholastic performance is the key metric by which schools measure student's academic success, and it is important to understand the neural-correlates associated with greater scholastic performance. This study examines resting-state functional connectivity (RsFc) associated with scholastic performance (reading and mathematics) in preadolescent children (7-9 years) using an unbiased whole-brain connectome-wide multi-voxel pattern analysis (MVPA). MVPA revealed four clusters associated with reading composite score, these clusters were then used for whole-brain seed-based RsFc analysis. However, no such clusters were found for mathematics composite score. Post hoc analysis found robust associations between reading and RsFc dynamics with areas involved with the somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, and default mode networks. These findings indicate that reading ability may be associated with a wide range of RsFc networks. Of particular interest, anticorrelations were observed between the default mode network and the somatomotor, dorsal attention, ventral attention, and frontoparietal networks. Previous research has demonstrated the importance of anticorrelations between the default mode network and frontoparietal network associated with cognition. These results extend the current literature exploring the role of network connectivity in scholastic performance of children.
... Both RYGB and LSG have similar effects on weight loss and have been shown to be associated with lower hunger scores and changes in food preference [3,4]. At baseline, resting-state functional brain magnetic resonance imaging (MRI) studies have shown that patients with obesity have alterations in the connections relating to metabolic sensing and reward processing [5,6]. After bariatric surgery, these connections and alterations in brain signaling often normalize [7][8][9]. ...
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Background: Bariatric surgery is proven to change eating behavior and cause sustained weight loss, yet the exact mechanisms underlying these changes are not clearly understood. We explore this in a novel way by examining how bariatric surgery affects the brain-gut-microbiome (BGM) axis. Methods: Patient demographics, serum, stool, eating behavior questionnaires, and brain magnetic resonance imaging (MRI) were collected before and 6 months after laparoscopic sleeve gastrectomy (LSG). Differences in eating behavior and brain morphology and resting-state functional connectivity in core reward regions were correlated with serum metabolite and 16S microbiome data. Results: LSG resulted in significant weight loss and improvement in maladaptive eating behaviors as measured by the Yale Food Addiction Scale (YFAS). Brain imaging showed a significant increase in brain volume of the putamen (p.adj < 0.05) and amygdala (p.adj < 0.05) after surgery. Resting-state connectivity between the precuneus and the putamen was significantly reduced after LSG (p.adj = 0.046). This change was associated with YFAS symptom count. Bacteroides, Ruminococcus, and Holdemanella were associated with reduced connectivity between these areas. Metabolomic profiles showed a positive correlation between this brain connection and a phosphatidylcholine metabolite. Conclusion: Bariatric surgery modulates brain networks that affect eating behavior, potentially through effects on the gut microbiota and its metabolites.
... Decreased gray matter volumes (GMVs) were also found in the insula, parahippocampus, and amygdala in smokers compared to nonsmokers [23,24]. Furthermore, increasing evidence has identified an association between obesity and decreased functional connectivity within networks that comprise the medial prefrontal cortex and default mode network (DMN) in healthy adults [25], while a higher educational level could decrease the risk of dementia compared with those with fewer years of formal education [4]. In addition, depression, as a severe form of psychological distress, has been associated with subcortical and hippocampal neuronal loss [26] and accompanies cognitive impairment in old adults [27]. ...
Article
There are increasing concerns regarding the association of vascular risk factors (VRFs) and cognitive decline in the Alzheimer's disease (AD) spectrum. Currently, we investigated whether the accumulating effects of VRFs influenced gray matter volumes and subsequently led to cognitive decline in the AD spectrum. Mediation analysis was used to explore the association among VRFs, cortical atrophy, and cognition in the AD spectrum. 123 AD spectrum were recruited and VRF scores were constructed. Multivariate linear regression analysis revealed that higher VRF scores were correlated with lower Mini-Mental State Examination scores and higher Alzheimer's Disease Assessment Scale-Cognitive Subscale scores, indicating higher VRF scores lead to severer cognitive decline in the AD spectrum. In addition, subjects with higher VRF scores suffered severe cortical atrophy, especially in medial prefrontal cortex and medial temporal lobe. More importantly, common circuits of VRFs- and cognitive decline associated with gray matter atrophy were identified. Further, using mediation analysis, we demonstrated that cortical atrophy regions significantly mediated the relationship between VRF scores and cognitive decline in the AD spectrum. These findings highlight the importance of accumulating risk in the vascular contribution to AD spectrum, and targeting VRFs may provide new strategies for the therapeutic and prevention of AD.
... Interestingly, in our study higher BMI also predicted lower connectivity between the ventral DC and lowand high-level visual areas: the left lingual gyrus, the bilateral calcarine cortex, and the left cuneal cortex, and a smaller cluster located in the left temporal occipital fusiform gyrus. Various studies have reported abnormalities in the connectivity of the ventral DC in individuals with overweight/obesity ( Baek et al., 2017 ;Contreras-Rodríguez et al., 2017 ;García -García et al., 2013 ;Nummenmaa et al., 2012 ;Olivo et al., 2016 ;Park et al., 2015 ;Steward et al., 2016 ), as well as reduced connectivity of the fusiform gyri and temporal visual areas ( García-García et al., 2015 ;Kullmann et al., 2013 ). Lower connectivity between these areas may be linked to a dissociation between perceptive and reward mechanisms, which can be one of the factors leading to overeating in obesity. ...
Article
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Previous studies have shown that individuals with overweight and obesity may experience attentional biases and reduced inhibition toward food stimuli. However, evidence is scarce as to whether the attentional bias is present even before stimuli are consciously recognized. Moreover, it is not known whether or not differences in the underlying brain morphometry and connectivity may co-occur with attentional bias and impulsivity towards food in individuals with different BMIs. To address these questions, we asked fifty-three participants (age M = 23.2, SD = 2.9, 13 males) to perform a breaking Continuous Flash Suppression (bCFS) task to measure the speed of subliminal processing, and a Go/No-Go task to measure inhibition, using food and nonfood stimuli. We collected whole-brain structural magnetic resonance images and functional resting-state activity. A higher BMI predicted slower subliminal processing of images independently of the type of stimulus (food or nonfood, p = 0.001, εp2 = 0.17). This higher threshold of awareness is linked to lower grey matter (GM) density of key areas involved in awareness, high-level sensory integration, and reward, such as the orbitofrontal cortex [t = 4.55, p = 0.003], the right temporal areas [t = 4.18, p = 0.002], the operculum and insula [t = 4.14, p = 0.005] only in individuals with a higher BMI. In addition, individuals with a higher BMI exhibit a specific reduced inhibition to food in the Go/No-Go task [p = 0.02, εp2 = 0.02], which is associated with lower GM density in reward brain regions [orbital gyrus, t = 4.97, p = 0.005, and parietal operculum, t = 5.14, p < 0.001] and lower resting-state connectivity of the orbital gyrus to visual areas [fusiform gyrus, t = -4.64, p < 0.001 and bilateral occipital cortex, t = -4.51, p < 0.001 and t = -4.34, p < 0.001]. Therefore, a higher BMI is predictive of non food-specific slower visual subliminal processing, which is linked to morphological alterations of key areas involved in awareness, high-level sensory integration, and reward. At a late, conscious stage of visual processing a higher BMI is associated with a specific bias towards food and with lower GM density in reward brain regions. Finally, independently of BMI, volumetric variations and connectivity patterns in different brain regions are associated with variability in bCFS and Go/No-Go performances.
... Electroconvulsive therapy was able to normalize the abnormal functional connectivity found in depression (Wang et al. 2019). The putamen is a region within the SN that activates during salient stimuli, such as pain, monetary stimuli, and salience detection (Garcia-Garcia et al. 2013). The increased FC between the NAc and SN in patients with CID may indicate that hyperconnectivity or imbalance between salience detection and reward processing is involved in the neuropathological mechanism of chronic insomnia. ...
Article
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Previous research has shown that acute sleep deprivation can influence the reward networks. However, it is unclear whether and how the intrinsic reward network is altered in chronic insomnia disorder (CID). In the present study, we aimed to investigate whether the reward network is altered in patients with CID using resting-state functional magnetic resonance imaging (fMRI) data. Forty-two patients with CID and 33 healthy controls (HCs) were enrolled and underwent resting-state fMRI. Nucleus accumbens (NAc) - based functional connectivity (NAFC) was evaluated to explore the differences in the reward network between the CID and HC groups. Pearson correlation analysis was used to evaluate the clinical significance of altered NAFC networks. Compared to those in the HC group, increased NAFC was found in the salience and limbic networks, while decreased NAFC was found in the default mode network (DMN) and within the reward circuit in patients with CID. In addition, decreased FC between the NAc and DMN was associated with insomnia severity, while NAFC within the reward network was associated with depression symptoms in patients with CID. These findings showed that the reward network is dysfunctional and associated with depression symptom in patients with CID. Future studies of CID should consider both insomnia and depression symptoms to disentangle the role of insomnia and depression in the relationship under study.
... These cognitive alterations often correspond to obesity-related variability in cortico-basal ganglia pathways that support decisionmaking and reward processing. For example, obesity is associated with reduced D2-receptor binding (Volkow et al., 2008b;de Weijer et al., 2011), altered reactivity to food cues in ventral and dorsal striatal regions (Stice et al., 2008(Stice et al., , 2010Burger and Stice, 2012), modified corticostriatal connectivity (García-García et al., 2012;Marqués-Iturria et al., 2015), and individual differences in genetic markers of dopamine availability (Noble et al., 1994;Nisoli et al., 2007;Stice et al., 2008). These observations have led to the hypothesis that risk for obesity may be engendered by a cluster of neurobiological phenotypes associated with addiction, mediated by hypersensitive mesolimbic dopaminergic pathway (Volkow et al., 2008a(Volkow et al., , 2012Tomasi and Volkow, 2013). ...
Article
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Unhealthy weight gain relates, in part, to how people make decisions based on prior experience. Here we conducted post hoc analysis on an archival data set to evaluate whether individual differences in adiposity, an anthropometric construct encompassing a spectrum of body types, from lean to obese, associate with signatures of asymmetric feedback learning during value-based decision-making. In a sample of neurologically healthy adults (N = 433), ventral striatal responses to rewards, measured using fMRI, were not directly associated with adiposity, but rather moderated its relationship with feedback-driven learning in the Iowa Gambling Task tested outside the scanner. Using a biologically-inspired model of basal ganglia-dependent decision processes, we found this moderating effect of reward reactivity to be explained by an asymmetrical use of feedback to drive learning; that is, with more plasticity for gains than for losses, stronger reward reactivity leads to decisions that minimize exploration for maximizing long-term outcomes. Follow-up analysis confirmed that individual differences in adiposity correlated with signatures of asymmetric use of feedback cues during learning, suggesting that reward reactivity may especially relate to adiposity, and possibly obesity risk, when gains impact future decisions more than losses.
... PFC modulating responses to high-calorie foods has strong linkage to executive-attention [20], inhibitory-control [21] as well as emotional-regulation [22]. Besides reports of brain responses to food cue stimulation, a number of resting-state fMRI studies have been performed to examine abnormal functional connectivity (FC) in brain regions within resting-state networks (RSNs) including the default-mode network (DMN), salience network (SN) and frontoparietal network (FPN) which are involved in self-referential, food reward and executive control processing [23][24][25]. Obese subjects showed increased FC strength in the precuneus and decreased FC strength in the right anterior cingulate cortex [25]; a seed-based correlation analysis revealed increased FC between the posterior cingulate cortex (PCC) and precuneus, and between PCC and PFC [26]. In addition, one newly published paper from our group not only investigated differences in FC in the DMN, SN and FPN, but also examined alteration in inter-network connectivity which showed increased connectivity between the SN and FPN in obesity [27]. ...
Article
Obese subjects show enhanced brain responses in motivation and reward neurocircuitry encompassing sensory and somatic integration-interception, motivation–reward (striatal), emotion, and memory processes, which attenuate frontal region activation during food cues. Bariatric surgery (BS) is the only reliable treatment for morbid obesity. Unfortunately, it is unknown how BS affects neurocircuitry after weight loss. We aimed to examine effects of BS on the basal activity of brain areas involved in reward and motivation processing, emotion, memory, and gut–brain interaction. We combined resting-state fMRI with amplitude of low-frequency fluctuation (ALFF) and Granger causality analysis (GCA) to assess interactions between regions within the frontal-mesolimbic circuitry in 16 obese subjects (OB) and 22 normal-weight (NW) subjects. The OB group was studied at baseline and 1 month post BS. Comparisons between OB and NW, and pre- and post BS, showed significant differences in ALFF in areas involved in drive (caudate, orbitofrontal cortex [OFC]), arousal (thalamus), and conditioning/memory (amygdala, hippocampus) (P < 0.05, FDR correction). GCA revealed that in the OB group, the OFC had greater connectivity to limbic regions (amygdala, hippocampus, and medial thalamus) and the caudate. Post BS, the connectivity of the OFC to limbic regions decreased, whereas the connectivity from the amygdala and hippocampus to the caudate and thalamus was enhanced, particularly in subjects with lower body mass index (BMI). OFC activation in the OB group was associated with BMI prior to surgery, and changes in OFC post surgery were associated with alterations in BMI. Overall, the functional connectivity of the OFC was significantly decreased. As it is important for salience attribution and connected to limbic brain regions involved with emotional reactivity and conditioning after BS, its significant association with BMI changes indicates the contribution of OFC changes to the improved control of eating behavior after surgery.
... Resting-state brain networks also exhibit obesity-related differences in connectivity (28)(29)(30). Obesity has been associated with decreased global and local efficiency, as well as modularity of functional networks throughout the brain (23,31), including the default mode network (DMN (32)). Furthermore, individuals with obesity show enhanced resting-state connectivity between regions involved in reward valuation and decision making such as the NAc, the anterior cingulate cortex (ACC), and ventromedial PFC (vmPFC (33)), suggesting that altered reward network function in obesity is not specific to valuation of food cues but may reflect more fundamental context-independent disruptions. ...
Article
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.
... Several studies have characterized the differences between appetite regulation in subjects with obesity and those with normal-weight using fMRI resting-state functional connectivity. These studies show that compared with normal-weight controls, subjects with obesity demonstrate increased resting-state functional connectivity in rewardrelated areas and those that comprise the salience network, including the insula, anterior cingulate cortex, striatum, amygdala, and orbitofrontal cortex [76][77][78]. Since hyperactivation of reward areas in response to visual images of palatable foods seen in obesity vs. normal-weight is highly established as discussed above, describing the taskdependent functional connectivity is critical to closely mimic the day-to-day neural response that an individual with obesity experiences when seeing visual food cues. ...
Article
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Oxytocin (OXT), shown to decrease food intake in animal models and men, is a promising novel treatment for obesity. We have shown that in men with overweight and obesity, intranasal (IN) OXT reduced the functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent signal in the ventral tegmental area (VTA), the origin of the mesolimbic dopaminergic reward system, in response to high-calorie food vs. nonfood images. Here, we employed functional connectivity fMRI analysis, which measures the synchrony in activation between neural systems in a context-dependent manner. We hypothesized that OXT would attenuate the functional connectivity of the VTA with key food motivation brain areas only when participants viewed high-calorie food stimuli. This randomized, double-blind, and placebo-controlled crossover study of 24 IU IN OXT included ten men with overweight or obesity (mean ± SEM BMI: 28.9 ± 0.8 kg/m²). Following drug administration, subjects completed an fMRI food motivation paradigm including images of high and low-calorie foods, nonfood objects, and fixation stimuli. A psychophysiological interaction analysis was performed with the VTA as seed region. Following OXT administration, compared with placebo, participants exhibited significantly attenuated functional connectivity between the VTA and the insula, oral somatosensory cortex, amygdala, hippocampus, operculum, and middle temporal gyrus in response to viewing high-calorie foods (Z ≥ 3.1, cluster-corrected, p < 0.05). There was no difference in functional connectivity between VTA and these brain areas when comparing OXT and placebo for low-calorie food, nonfood, and fixation images. In men with overweight and obesity, OXT attenuates the functional connectivity between the VTA and food motivation brain regions in response to high-calorie visual food images. These findings could partially explain the observed anorexigenic effect of OXT, providing insight into the mechanism through which OXT ameliorates food cue-induced reward anticipation in patients with obesity. Additional studies are ongoing to further delineate the anorexigenic effect of OXT in obesity.
... homeostatic and cognitive state) and external factors (i.e. social environment) and have been found altered in obese/ overweight individuals [25][26][27]. In particular, dysfunctions in the connectivity between these regions may reflect obesity-related defects in inhibitory control and attention processes involved in food intake behavior, and an increased motivation to internal signals, such as appetite or food-related reward [28]. ...
Article
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There are reported gender differences in brain connectivity associated with obesity. In the elderlies, the neural endophenotypes of obesity are yet to be elucidated. We aim at exploring the brain metabolic and connectivity correlates to different BMI levels in elderly individuals, taking into account gender as variable of interest.We evaluated the association between BMI, brain metabolism and connectivity, in elderly females and males, by retrospectively collecting a large cohort of healthy elderly subjects (N=222; age=74.03±5.88 [61.2-85.9] years; M/F=115/107; BMI=27.00±4.02 [19.21-38.79] kg/m2). Subjects underwent positron emission tomography with [18F]FDG. We found that, in females, high BMI was associated with increased brain metabolism in the orbitofrontal cortex (R=0.44; p<0.001). A significant BMI-by-gender interaction was present (F=7.024, p=0.009). We also revealed an altered connectivity seeding from these orbitofrontal regions, namely expressing as a decreased connectivity in crucial control/decision making circuits, and as an abnormally elevated connectivity in reward circuits, only in females. Our findings support a link between high BMI and altered brain metabolism and neural connectivity, only in elderly females. These findings indicate a strong gender effect of high BMI and obesity that brings to considerations for medical practice and health policy.
... Garcia-Garcia et al. 2013 [33] used non-invasive diffusion tensor imaging to find the correlation between the functional neuroimaging indices of obese patients. The functional indices contain amplitude low-frequency fluctuation (AlF) and regional homogeneity ...
Technical Report
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Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy dropped from 80 to 75 years, as obese people struggle with different chronic diseases. This report will address the problems of obesity in children and adults using ML datasets to feature, predict, and analyze the causes of obesity. By engaging neural ML networks, we will explore neural control using diffusion tensor imaging to consider body fats, BMI, waist & hip ratio circumference of obese patients. To predict the present and future causes of obesity with ML, we will discuss ML techniques like decision trees, SVM, RF, GBM, LASSO, BN, and ANN and use datasets to implement the stated algorithms. Different theoretical literature from experts in ML & Bioinformatics experiments will be outlined in this report while making recommendations on how to advance ML for predicting obesity and other chronic diseases.
... We hypothesized that MBSR would be associated with increased RS connectivity compared with the control condition. Based on previous fMRI research on MBSR, we selected several key brain regions of interest (ROIs) and ICs to focus our investigation [54][55][56][57][58][59][60] (Fig 1). Our second aim was to investigate the association of RS change post-intervention with 6-month outcomes for psychological and anthropometric factors. ...
Article
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Obesity is associated with significant comorbidities and financial costs. While behavioral interventions produce clinically meaningful weight loss, weight loss maintenance is challenging. The objective was to improve understanding of the neural and psychological mechanisms modified by mindfulness that may predict clinical outcomes. Individuals who intentionally recently lost weight were randomized to Mindfulness-Based Stress Reduction (MBSR) or a control healthy living course. Anthropometric and psychological factors were measured at baseline, 8 weeks and 6 months. Functional connectivity (FC) analysis was performed at baseline and 8 weeks to examine FC changes between regions of interest selected a priori , and independent components identified by independent component analysis. The association of pre-post FC changes with 6-month weight and psychometric outcomes was then analyzed. Significant group x time interaction was found for FC between the amygdala and ventromedial prefrontal cortex, such that FC increased in the MBSR group and decreased in controls. Non-significant changes in weight were observed at 6 months, where the mindfulness group maintained their weight while the controls showed a weight increase of 3.4% in BMI. Change in FC at 8-weeks between ventromedial prefrontal cortex and several ROIs was associated with change in depression symptoms but not weight at 6 months. This pilot study provides preliminary evidence of neural mechanisms that may be involved in MBSR’s impact on weight loss maintenance that may be useful for designing future clinical trials and mechanistic studies.
... Obesity is associated with perturbed FC and disrupted functional organization in large-scale resting-state brain networks implied in reward [7], salience [8], and internal monitoring [9]. In particular, individuals with overweight or obesity exhibit altered FC in ventral and dorsal-striatal circuits, comprising the prefrontal, anterior cingulate, insular, and parietal cortices [10], consistent with the role of striatal-cortical dopaminergic circuits in reward, motivation, and incentive sensitization, and within the salience network [11], which is also in line with heightened incentive salience processing of food stimuli in this population. ...
Article
Background and Aims Deep repetitive Transcranial Magnetic Stimulation (deep rTMS) over the bilateral insula and prefrontal cortex (PFC) can promote weight-loss in obesity, preventing cardiometabolic complications as Type 2 Diabetes (T2D). To investigate the changes in the functional brain integration after dTMS, we conducted a resting-state functional connectivity (rsFC) study in obesity. Methods and Results This preliminary study was designed as a randomized, double-blind, sham-controlled study: 9 participants were treated with high-frequency stimulation (realTMS group), 8 were sham-treated. Out of the 17 enrolled patients, 6 were affected by T2D. Resting-state fMRI scans were acquired at baseline (T0) and after the 5-week intervention (T1). Body weight was measured at three time points [T0, T1, 1-month follow-up visit (FU1)]. A mixed-model analysis showed a significant group-by-time interaction for body weight (p=.04), with a significant decrease (p<.001) in the realTMS group. The rsFC data revealed a significant increase of degree centrality for the realTMS group in the medial orbitofrontal cortex (mOFC) and a significant decrease in the occipital pole. Conclusion An increase of whole-brain functional connections of the mOFC, together with the decrease of whole-brain functional connections with the occipital pole, may reflect a brain mechanism behind weight-loss through a diminished reactivity to bottom-up visual-sensory processes in favor of increased reliance on top-down decision-making processes. Trial registration number ClinicalTrials.gov NCT03009695.
... Magnetic resonance imaging (MRI) studies have also demonstrated relationships between obesity and white matter (WM) disruption in several tracts, including the corpus callosum, internal capsule and thalamic radiation Repple et al., 2018 ). Several functional magnetic resonance imaging (fMRI) studies have reported differences in brain activity levels between participants who are lean and those with obesity in various resting-state networks, including the default-mode network, salience network, prefrontal and temporal lobe networks ( Ding et al., 2020 ;Garcia-Garcia et al., 2013Kullmann et al., 2012 ;Coveleskie et al., 2015 ). However, the exact mechanisms underlying the links between obesity and structural and functional brain alterations remain largely unknown. ...
Article
Background Metabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables. Methods The study included 57 participants with severe obesity (mean BMI=43.1 ± 4.3 kg/m²) who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N = 36), 12 months (N = 29), and 24 months (N = 14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N = 46) or severe obesity (N = 46). Results We found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks. Conclusions Bariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery.
... The ability to suppress dominant responses and resist irrelevant stimuli is called inhibitory control 1 and is believed to play a key role in the regulation of body weight. 2 In comparison with normalweight individuals, obese adults not only have reduced brain volume (e.g., frontal cortex and anterior cingulate cortex), but show greater activation when responding to food cues in brain regions involved in the regulation of food intake [e.g., the salience network 3 and the hypothalamic network 4 under both fasting or sated conditions. 5 In addition, obese people exhibit lower dopamine D2 receptor density in the striatum, which is associated with higher metabolic activity in the prefrontal regions involved in inhibitory control and could be a potential mechanism contributing to overeating. ...
Article
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Background/Objectives To the best of our knowledge, there have been no previous studies conducted on the long-term effects of an exercise intervention on deficits in inhibitory control in obese individuals. The aim of this study was thus to examine the effect of 12 weeks of a combination of aerobic and resistance exercise on behavioral and cognitive electrophysiological performance involving cognitive interference inhibition in obese individuals. Methods Thirty-two qualified healthy obese women were randomly divided into either an exercise group (EG, age: 34.76 ± 5.52 years old; BMI: 29.35 ± 3.52 kg/m²) or a control group (CG, age: 33.84 ± 7.05 years old; BMI: 29.61 ± 4.31 kg/m²). All participants performed the Stroop task, with electrophysiological signals being collected simultaneously before and after a 12-week intervention. The estimated V̇O2max, muscular strength, and body fat percentage (measured with dual-energy X-ray absorptiometry) were also assessed within one week before and after the intervention. Participants in the EG group engaged in 30 min of moderate-intensity aerobic exercise combined with resistance exercise, 5 sessions per week for 12 weeks, while the participants in the CG group maintained their regular lifestyle without engaging in any type of exercise. Results The results revealed that although a 12-week exercise intervention did not enhance the behavioral indices [e.g., accuracy rates (ARs) and reaction times (RTs)] in the EG group, significantly shorter N2 and P3 latencies and greater P2 and P3 amplitudes were observed. Furthermore, the fat percentage distribution (e.g. total body fat %, trunk fat %, and leg fat %) and level of physical fitness (e.g. estimated V̇O2max and muscular strength) in the EG group were significantly improved. The changes prior to and after the intervention in the P3 amplitude and trunk fat percentage were significantly negatively correlated in the EG group (r = −0.521, p = 0.039). Conclusions These findings suggested that 12 weeks of aerobic exercise combined with resistance exercise in obese women affects cognitive function broadly, but not specifically in terms of inhibitory control. The percentage of decreased trunk fat may play a potential facilitating role in inhibition processing in obesity.
... Recent studies using functional neuroimaging, specifically blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI), have linked activation of distinct regions in the brain with changes in gut hormones and peptides (Bogdanov et al., 2020). Patients with obesity and normal weight cohorts exhibit differences in rsfMRI activity (García-García et al., 2013;Kullmann et al., 2012), and brain regions important for cognitive control, inhibition motivation, reward, and salience are involved in the neuropathology of obesity (Dong et al., 2015;Lepping et al., 2015;Zhang et al., 2015). Spontaneous low-frequency (0.01-0.08 Hz) fluctuations (LFFs) of bloodoxygen-level-dependent fMRI signals (Biswal et al., 1995) are closely related to the spontaneous neuronal activities occurring during the resting-state (Lu et al., 2007;Mantini et al., 2007), and numerous studies have used fractional amplitude of lowfrequency fluctuations (fALFF) to quantify brain activity changes following VSG and RYGB (Li et al., 2018;Zeighami et al., 2021). ...
Article
Background Plausible phenotype mechanisms following bariatric surgery include changes in neural and gastrointestinal physiology. This pilot study aims to investigate individual and combined neurologic, gut microbiome, and plasma hormone changes pre- versus post-vertical sleeve gastrectomy (VSG), Roux-en-Y gastric bypass (RYGB), and medical weight loss (MWL). We hypothesized post-weight loss phenotype would be associated with changes in central reward system brain connectivity, differences in postprandial gut hormone responses, and increased gut microbiome diversity. Methods Subjects included participants undergoing VSG, n = 7; RYGB, n = 9; and MWL, n = 6. Ghrelin, glucagon-like peptide-1, peptide-YY, gut microbiome, and resting state functional magnetic resonance imaging (rsfMRI; using fractional amplitude of low-frequency fluctuations [fALFF]) were measured pre- and post-intervention in fasting and fed states. We explored phenotype characterization using clustering on gut hormone, microbiome, and rsfMRI datasets and a combined analysis. Results We observed more widespread fALFF differences post-bariatric surgery versus post-MWL. Decreased post-prandial fALFF was seen in food reward regions post-RYGB. The highest number of microbial taxa that increased post-intervention occurred in the RYGB group, followed by VSG and MWL. The combined hormone, microbiome, and MRI dataset most accurately clustered samples into pre- versus post-VSG phenotypes followed by RYGB subjects. Conclusion The data suggest surgical weight loss (VSG and RYGB) has a bigger impact on brain and gut function versus MWL and leads to lesser post-prandial activation of food-related neural circuits. VSG subjects had the greatest phenotype differences in interactions of microbiome, rsfMRI, and gut hormone features, followed by RYGB and MWL. These results will inform future prospective research studying gut-brain changes post-bariatric surgery.
... David Cardenas et al. have demonstrated that PIA and sedentary lifestyle led to obesity conditions, correlated with disruption in cognitive function, and affected the structure of any regions in brain tissue (García-García et al., 2013). The aim is to evaluate the probable relationship between total fat mass, visceral AT, and white matter in subcortical structure in brain tissue of military pilots. ...
Article
Adipose tissue is a dynamic organ in the endocrine system that can connect organs by secreting molecules and bioactive. Hence, adipose tissue really plays a pivotal role in regulating metabolism, inflammation, energy homeostasis, and thermogenesis. Disruption of hub bioactive molecules secretion such as adipokines leads to dysregulate metabolic communication between adipose tissue and other organs in non-communicable disorders. Moreover, a sedentary lifestyle may be a risk factor for adipose tissue function. Physical inactivity leads to fat tissue accumulation and promotes obesity, Type 2 diabetes, cardiovascular disease, neurodegenerative disease, fatty liver, osteoporosis, and inflammatory bowel disease. On the other hand, physical activity may ameliorate and protect the body against metabolic disorders, triggering thermogenesis, metabolism, mitochondrial biogenesis, β-oxidation, and glucose uptake. Furthermore, physical activity provides an inter-organ association and cross-talk between different tissues by improving adipose tissue function, reprogramming gene expression, modulating molecules and bioactive factors. Also, physical activity decreases chronic inflammation, oxidative stress and improves metabolic features in adipose tissue. The current review focuses on the beneficial effect of physical activity on the cardiovascular, locomotor, digestive, and nervous systems. In addition, we visualize protein-protein interactions networks between hub proteins involved in dysregulating metabolic induced by adipose tissue.
... Kullmann et al. have firstly utilized the ICA method to study the brain network of obese subjects with resting-state fMRI, and alteration in default mode network (DMN) and temporal lobe network were found between lean and obese participants (Kullmann et al., 2012). Later, changes in the salience network (SN), sensorimotor network (SMN), reward circuit and fronto-parietal network (FPN) were also found to be related with obesity based on the ICA method (Ding et al., 2020;García-García et al., 2013;Park et al., 2020). ...
Article
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Obesity was found to be related with the changes of brain functions in human beings. There were several brain areas that were verified to be correlated with the obesity, including the parietal cortex, frontal cortex and so on. However, the cortical regions found from different studies were discrepant due to the different ages, gender distribution and satiation degree of participants. We found that the regional homogeneity of right angular gyrus were smaller in obese undergraduates than that in normal-weight undergraduates. Moreover, functional connectivity of the left middle temporal cortex and the right angular gyrus were found to be smaller in obese group than that in normal-weight group by setting the right angular gyrus as seed region. In addition, multiple regression analysis suggested that the right superior frontal gyrus and left middle temporal gyrus were significantly correlated with their body mass index for normal-weight undergraduates, but no significant correlation was found for obese group. In summary, these findings indicated the functional changes of the cortex in obese undergraduates, which might be significant for providing imaging-based biomarkers for intervention and therapy of obesity.
... Magnetic resonance imaging (MRI) studies have also demonstrated relationships between obesity and white matter (WM) disruption in several tracts, including the corpus callosum, internal capsule and thalamic radiation (7,14). Several functional magnetic resonance imaging (fMRI) studies have reported differences in brain activity levels between participants who are lean and those with obesity in various resting-state networks, including the default-mode network, salience network, prefrontal and temporal lobe networks (15)(16)(17)(18)(19). However, the exact mechanisms underlying the links between obesity and structural and functional brain alterations remain largely unknown. ...
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Background: Metabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables. Methods: The study included 57 participants with severe obesity who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N=36), 12 months (N=29), and 24 months (N=14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N=46) or severe obesity (N=46). Results: We found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as insulin resistance index and blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks. Conclusions: Bariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery.
... The extended reward system involves regions associated with salience and cortical inhibition (prefrontal control) networks [39,[91][92][93]. In obesity, the salience network integrates salient information to make decisions regarding food intake [94][95][96][97] and, together with the executive control network, inhibits reward impulses [98,99]. When viewed together with these reports, the study results suggest that in individuals with high BMI, ELAs may further increase the engagement of emotion regulation and reward regions, perhaps contributing to increased food seeking behaviors, as measured by YFAS. ...
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Background: Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods: Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results: Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions: The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling.
... /2021 pattern within the executive control network has been observed in fMRI activation studies using food stimuli (Franssen et al., 2020). Recently, it has also been shown that obesity is related to prominent functional connectivity alterations mainly in prefrontal regions during resting-state as well as in response to food stimuli (García-García et al., 2013;Kullmann et al., 2012). Thus, our resting-state findings might further add to the possibility of disrupted communication between the executive control network and regions regulating metabolic needs in individuals with excess weight. ...
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Hunger and satiety states drive eating behaviours via changes in brain function. The hypothalamus is a central component of the brain networks that regulate food intake. Animal research parsed the roles of the lateral hypothalamus (LH) and the medial hypothalamus (MH) in hunger and satiety respectively. Here, we examined how hunger and satiety change information flow between human LH and MH brain networks, and how these interactions are influenced by body mass index. Forty participants (15 overweight/obese) underwent two resting-state functional MRI scans: after overnight fasting (fasted state) and following a standardised meal (sated state). The direction and valence (excitatory/inhibitory influence) of information flow between the MH and LH was modelled using spectral dynamic causal modelling. Our results revealed two core networks interacting across homeostatic state and weight status: subcortical bidirectional connections between the LH, MH and the substantia nigra pars compacta (prSN), and cortical top-down inhibition from frontoparietal and temporal areas. During fasting relative to satiety, we found higher inhibition between the LH and prSN, whereas the prSN received greater top-down inhibition from across the cortex. Individuals with higher BMI showed that these network dynamics occur irrespective of fasted or satiety states. Our findings reveal fasting affects brain dynamics over a distributed hypothalamic-midbrain-cortical network. This network is less sensitive to state-related fluctuations among people with obesity.
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Obese individuals exhibit brain functional abnormalities in multiple regions implicated in reward/motivation, emotion/memory, homeostatic regulation and executive-control when exposed to food-cues and during rest. However, it remains unclear whether abnormal brain responses to food-cues might account for or relate to their abnormal activity in resting-state. This information would be useful for understanding the neural mechanism behind hyperactive responses to food-cues, a critical marker of obesity. Resting-state functional magnetic resonance (RS-fMRI) and cue-reactivity fMRI task with high- (HiCal) and low-caloric (LoCal) food-cues were employed to investigate brain baseline activity and food cue-induced activation differences in 44 obese participants (OB), in 37 overweight participants (OW) and in 37 normal weight (NW) controls. One-way ANOVAs showed there was a group difference in left hippocampus/amygdala activity during resting-state and under food-cues (PFWE<0.05); post-hoc tests showed OB group had both greater basal activity and food cue-induced activation than OW and NW groups; OW had higher activity in the hippocampus/amygdala than NW group only during resting-state. In OB group, resting-state activity in the left hippocampus/amygdala was correlated with their activation induced by HiCal food-cues. Further, in OB, hippocampus/amygdala resting activity and HiCal food cue-induced activation were positively correlated with body mass index (BMI). Mediation analysis showed that the relationship between BMI and hippocampus/amygdala response to HiCal food-cues was fully mediated by their resting-state activity. These findings suggest the close association between obesity and brain functional abnormality in hippocampus/amygdala. They also indicate that resting-state activity in hippocampus/amygdala has a great impact on these regions’ responses to food-cues.
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Objective: Brain imaging studies have shown insula-related functional and structural abnormalities in patients with obesity. Laparoscopic sleeve gastrectomy is currently an effective procedure for treating obesity, which promotes acute recovery of brain functional and structural abnormalities in obese patients. The aim of this study was to investigate the long-term impact of laparoscopic sleeve gastrectomy on insula-related structural and functional connectivity. Methods: Diffusion tensor imaging and resting-state functional magnetic resonance imaging were employed to investigate laparoscopic sleeve gastrectomy-induced changes in insula-related structural connectivity and corresponding resting-state functional connectivity in 25 obese patients prior to (PreLSG) and 12 months post-surgery (PostLSG12). Results: Results showed significant increases in fractional anisotropy and axial diffusivity between the right insula and anterior cingulate cortex, and higher fractional anisotropy of left insula-putamen, left insula-caudate and anterior cingulate cortex-right posterior cingulate cortex/precuneus at PostLSG12 compared with PreLSG. There were significant negative correlations between axial diffusivity of right insula-anterior cingulate cortex and body mass index, and fractional anisotropy of right insula-anterior cingulate cortex with scores on external eating at PostLSG12. Anxiety and depressive status ratings were negatively correlated with fractional anisotropy of left insula-putamen at PostLSG12. In addition, there was a significant decrease in resting-state functional connectivity between left insula and left caudate. Conclusions: These findings demonstrate long-term changes in insula-related structural and functional connectivity abnormalities promoted by laparoscopic sleeve gastrectomy, which highlight its strong association with long-term weight loss and improvement in eating behaviors.
Article
Objective: The effects of sleeve gastrectomy (SG) on functional connectivity (FC) and associations with weight loss and eating-related cognitive control were investigated. Methods: In a longitudinal study, 14 SG patients (13 female; 42.1 presurgery BMI) completed study visits 1 month pre surgery and 12 months post surgery. Patients completed the Dutch Eating Behavior Questionnaire and resting-state functional magnetic resonance imaging scanning to measure FC. Data were analyzed using a seed-to-voxel approach in the CONN Toolbox to investigate pre-/postsurgery changes (n = 12) and to conduct predictive analysis (n = 14). Results: Seed-to-voxel analysis revealed changes in magnitude (decreases) and directionality (positively correlated to anticorrelated) of FC pre to post surgery within and between default mode network, salience network, and frontoparietal network nodes [Family-Wise Error (FWE) corrected at P < 0.05]. Baseline FC of the nucleus accumbens (with insula) and hypothalamus (with precentral gyrus) predicted 12-month post-SG % total weight loss (FWE-P < 0.05). Baseline FC of the hippocampus, frontoparietal network, and default mode network nodes predicted improvement in cognitive control of eating behavior 12 months after SG (FWE-P < 0.05). Conclusions: Our findings demonstrate changes in FC magnitude and directionality post versus pre surgery within and between resting-state networks and frontal, paralimbic, and visual areas in SG patients. Baseline FC predicted weight loss and changes in cognitive control of food intake behavior at 12 months. These could serve as predictive biomarkers for bariatric surgery.
Article
Background Bipolar disorder (BD) has been linked to abnormalities in the communication and gray matter volume (GMV) of large-scale brain networks, as reflected by impaired resting-state functional connectivity (rs-FC) and aberrant voxel-based morphometry (VBM). However, identifying patterns of large-scale network abnormality in BD has been elusive. Methods Whole-brain seed-based rs-FC and VBM studies comparing individuals with BD and healthy controls (HCs) were retrieved from multiple databases. Multilevel kernel density analysis was used to identify brain networks in which BD was linked to hyper-connectivity or hypo-connectivity with each a priori network and the overlap between dysconnectivity and GMV changes. Results Thirty-six seed-based rs-FC publications (1526 individuals with BD and 1578 HCs) and 70 VBM publications (2715 BD and 3044 HCs) were included in the meta-analysis. Our results showed that BD was characterized by hypo-connectivity within the default network (DN), hyper-connectivity within the affective network (AN), and ventral attention network (VAN) and hypo- and hyper-connectivity within the frontoparietal network (FN). Hyper-connectivity between-network of AN-DN, AN-FN, AN-VAN, AN-thalamus network (TN), VAN-TN, VAN-DN, VAN-FN, and TN-sensorimotor network were found. Hypo-connectivity between-network was observed between the FN and DN. Decreased GMV was found in the insula, inferior frontal gyrus, and anterior cingulate cortex. Limitations Differential weights in the number of included studies and sample size of FC and VBM might have a disproportionate influence on the meta-analytic results. Conclusions These results suggest that BD is characterized by both structural and functional abnormalities of large-scale neurocognitive networks, especially in the DN, AN, VAN, FN, and TN.
Article
Structural brain differences have been described in first-episode schizophrenia spectrum disorders (FES), and often overlap with those evident in the metabolic syndrome (MetS). We examined the associations between body mass index (BMI) and brain structures involved in food intake regulation in minimally treated FES patients (n = 117) compared to healthy controls (n = 117). The effects of FES diagnosis, BMI and their interactions on our selected prefrontal cortical thickness and subcortical gray matter volume regions of interest (ROIs) were investigated with hierarchical multivariate regressions, followed by post-hoc regressions for the individual ROIs. In a secondary analysis, we examined the relationships of other MetS risk factors and psychopathology with the brain ROIs. Both illness and BMI significantly predicted the grouped prefrontal cortical thickness ROIs, whereas only BMI predicted the grouped subcortical volume ROIs. For the individual ROIs, schizophrenia diagnosis predicted thinner left and right frontal pole and right lateral OFC thickness, and increased BMI predicted thinner left and right caudal ACC thickness. There were no significant main or interaction effects for diagnosis and BMI on any of the individual subcortical volume ROIs. Secondary analyses suggest associations between several brain ROIs and individual MetS risk factors, but not with psychopathology. Our findings indicate differential, independent effects for FES diagnosis and BMI on brain structures. Limited evidence suggests that the BMI effects are more prominent in FES. Exploratory analyses suggest associations between other MetS risk factors and some brain ROIs.
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Objective: To investigate alterations in functional-connectivity (FC) within and interactions between between resting-state- networks (RSNs) involved in salience, executive-control and interoception in subjects with obesity (OB). Methods: Using RS-fMRI with independent component analysis and FC, we investigated alterations within and interactions between RSNs in 35 OB and 35 normal weight (NW) controls. Results: Compared to NW, OB showed reduced FC strength in the ventromedial prefrontal cortex (VMPFC) and posterior cingulate cortex (PCC)/precuneus within the default-mode network (DMN), dorsal anterior cingulate cortex (dACC) within the salience network (SN), bilateral dorsolateral prefrontal cortex (DLPFC)/angular gyrus (ANG) within the frontoparietal network (FPN), and increased FC strength in the insula (INS, PFWE<0.0125). The dACC FC strength was negatively correlated with craving for food-cues, left DLPFC FC strength was negatively correlated with Yale-Food-Addiction-Scale scores, and right INS FC strength was positively correlated with craving for high-calorie food-cues. Compared to NW, OB also showed increased FC between SN and FPN driven by altered FC of bilateral INS and ACC-ANG. Conclusion: Alterations in FC within and between the SN, DMN and FPN might contribute to the high incentive value of food (craving), lack of control of over eating (compulsive overeating) and increased awareness of hunger (impaired interoception) in obesity.
Article
Abnormal activities in reward-related regions are associated with overeating or obesity. Preliminary studies have shown that changes in neural activity in obesity include not only regional reward regions abnormalities but also impairments in the communication between reward-related regions and multiple functional areas. A recent study has shown that the transitions between different neural networks are nonrandom and hierarchical, and that activation of particular brain networks is more likely to occur after other brain networks. The aims of this study were to investigate the key nodes of reward-related regions in obese males and explore the hierarchical integrated processing of key nodes. Twenty-four obese males and 24 normal-weight male controls of similar ages were recruited. The fMRI data were acquired using 3.0 T MRI. The fMRI data preprocessing was performed in DPABI and SPM 12. Degree centrality analyses were conducted using GRETNA toolkit, and Granger causality analyses were calculated using DynamicBC toolbox. Decreased degree centrality was observed in left ventral medial prefrontal cortex (vmPFC) and right parahippocampal/hippocampal gyrus in group with obesity. The group with obesity demonstrated increased effective connectivity between left vmPFC and several regions (left inferior temporal gyrus, left supplementary motor area, right insular cortex, right postcentral gyrus, right paracentral lobule and bilateral fusiform gyrus). Increased effective connectivity was observed between right parahippocampal/hippocampal gyrus and left precentral/postcentral gyrus. Decreased effective connectivity was found between right parahippocampal/hippocampal gyrus and left inferior parietal lobule. This study identified the features of hierarchical interactions between the key reward nodes and multiple function networks. These findings may provide more evidence for the existing view of hierarchical organization in reward processing.
Preprint
Obesity is associated with significant comorbidities and financial costs. While behavioral interventions produce clinically meaningful weight loss, weight loss maintenance is challenging. The objective was to improve understanding of the neural and psychological mechanisms modified by mindfulness that may predict clinical outcomes. Individuals who intentionally recently lost weight were randomized to Mindfulness-Based Stress Reduction (MBSR) or a control healthy living course. Anthropometric and psychological factors were measured at baseline, 8 weeks and 6 months. Functional connectivity (FC) analysis was performed at baseline and 8 weeks to examine FC changes between regions of interest selected a priori, and independent components identified by independent component analysis. The association of pre-post FC changes with 6-month weight and psychometric outcomes was then analyzed. Significant group x time interaction was found for FC between the amygdala and ventromedial prefrontal cortex, such that FC increased in the MBSR group and decreased in controls. Non-significant changes in weight were observed at 6 months, where the mindfulness group maintained their weight while the controls showed a weight increase of 3.4% in BMI. Change in FC at 8-weeks between ventromedial prefrontal cortex and several ROIs was associated with change in depression symptoms but not weight at 6 months. This pilot study provides preliminary evidence of neural mechanisms that may be involved in MBSR’s impact on weight loss maintenance that may be useful for designing future clinical trials and mechanistic studies.
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Obesity is associated with negative physical and mental health outcomes. Being overweight/obese is also associated with executive functioning impairments and structural changes in the brain. However, the impact of body mass index (BMI) on the relationship between brain dynamics and executive function (EF) is unknown. The goal of the study was to assess the modulatory effects of BMI on brain dynamics and EF. A large sample of publicly available neuroimaging and neuropsychological assessment data collected from 253 adults (18–45 years; mean BMI 26.95 kg/m ² ± 5.90 SD) from the Nathan Kline Institute (NKI) were included ( http://fcon_1000.projects.nitrc.org/indi/enhanced/ ). Participants underwent resting-state functional MRI and completed the Delis-Kaplan Executive Function System (D-KEFS) test battery (1). Time series were extracted from 400 brain nodes and used in a co-activation pattern (CAP) analysis. Dynamic CAP metrics including dwell time (DT), frequency of occurrence, and transitions were computed. Multiple measurement models were compared based on model fit with indicators from the D-KEFS assigned a priori (shifting, inhibition, and fluency). Multiple structural equation models were computed with interactions between BMI and the dynamic CAP metrics predicting the three latent factors of shifting, inhibition, and fluency while controlling for age, sex, and head motion. Models were assessed for the main effects of BMI and CAP metrics predicting the latent factors. A three-factor model (shifting, inhibition, and fluency) resulted in the best model fit. Significant interactions were present between BMI and CAP 2 (lateral frontoparietal (L-FPN), medial frontoparietal (M-FPN), and limbic nodes) and CAP 5 (dorsal frontoparietal (D-FPN), midcingulo-insular (M-CIN), somatosensory motor, and visual network nodes) DTs associated with shifting. A higher BMI was associated with a positive relationship between CAP DTs and shifting. Conversely, in average and low BMI participants, a negative relationship was seen between CAP DTs and shifting. Our findings indicate that BMI moderates the relationship between brain dynamics of networks important for cognitive control and shifting, an index of cognitive flexibility. Furthermore, higher BMI is linked with altered brain dynamic patterns associated with shifting.
Article
Objective This study aimed to investigate regional neural activity and regulation of patterns in the reorganized neural network of obesity and explore the correlation between brain activities and eating behavior. Methods A total of 23 individuals with obesity and 23 controls with normal weight were enrolled. Functional magnetic resonance imaging (fMRI) data were acquired using 3.0‐T MRI. Amplitude of low‐frequency fluctuation and functional connectivity (FC) analyses were conducted using Data Processing Assistant for resting‐state fMRI and Resting‐State fMRI Data Analysis Toolkit (REST). Results The group with obesity showed increased amplitude of low‐frequency values in left fusiform gyrus/amygdala, inferior temporal gyrus (ITG), hippocampus/parahippocampal gyrus, and bilateral caudate but decreased values in right superior temporal gyrus. The group with obesity showed increased FC between left caudate and right superior temporal gyrus, left fusiform gyrus/amygdala and left ITG, right caudate and left fusiform gyrus/amygdala, and right caudate and left hippocampus/parahippocampal gyrus. Dutch Eating Behavior Questionnaire‐Emotional scores were positively correlated with FC between left hippocampus/parahippocampal gyrus and right caudate but negatively correlated with FC between left fusiform gyrus/amygdala and left ITG. Conclusions The study indicated the reorganized neural network presented as a bilateral cross‐regulation pattern across hemispheres between reward and various appetite‐related functional processing, thus affecting emotional and external eating behavior. These results could provide further evidence for neuropsychological underpinnings of food intake and their neuromodulatory therapeutic potential in obesity.
Article
Objective The current study examined whether adolescents with weight status ranging from lean to obesity showed weight‐related differences in the default mode network (DMN), the executive function network (EFN), and the salience network (SN). Methods One hundred sixty‐four adolescents participated in a resting‐state functional connectivity scan. A general linear model was used to examine differences in scan patterns among adolescents with lean weight, overweight, and obesity. Results Adolescents with obesity compared with those with lean weight showed stronger within‐SN connectivity among the medial orbitofrontal cortex, olfactory tubercle, and pallidum; however, they showed lower connectivity between the amygdala and SN regions (nucleus accumbens, thalamus, putamen). Those with obesity also showed lower connectivity between SN (amygdala, caudate) and DMN (parahippocampus, hippocampus, precuneus) regions. Adolescents with obesity compared with those with lean weight showed lower connectivity between SN (medial orbitofrontal cortex) and EFN (ventrolateral prefrontal cortex) regions. Conclusions Obesity appears to be related to stronger connectivity within and between regions implicated in determining the salience of stimuli, which may have implications for reward processing. Lower connectivity between SN and EFN regions may suggest that executive‐control efforts are going “off‐line” when salience and reward‐processing regions are engaged in adolescents who have obesity.
Article
In this paper, we present a transdisciplinary framework and testable hypotheses regarding the process of fetal programming of energy homeostasis brain circuitry. Our model proposes that key aspects of energy homeostasis brain circuitry already are functional by the time of birth (with substantial interindividual variation); that this phenotypic variation at birth is an important determinant of subsequent susceptibility for energy imbalance and childhood obesity risk; and that this brain circuitry exhibits developmental plasticity, in that it is influenced by conditions during intrauterine life, particularly maternal–placental–fetal endocrine, immune/inflammatory, and metabolic processes and their upstream determinants. We review evidence that supports the scientific premise for each element of this formulation, identify future research directions, particularly recent advances that may facilitate a better quantification of the ontogeny of energy homeostasis brain networks, highlight animal and in vitro-based approaches that may better address the determinants of interindividual variation in energy homeostasis brain networks, and discuss the implications of this formulation for the development of strategies targeted towards the primary prevention of childhood obesity.
Article
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.
Article
Despite bariatric surgery being the most effective treatment for obesity, a proportion of subjects have suboptimal weight loss post-surgery. Therefore, it is necessary to understand the mechanisms behind the variance in weight loss and identify specific baseline biomarkers to predict optimal weight loss. Here, we employed functional magnetic resonance imaging (fMRI) with baseline whole-brain resting-state functional connectivity (RSFC) and a multivariate prediction framework integrating feature selection, feature transformation and classification to prospectively identify obese patients that exhibited optimal weight loss at six months post-surgery. Siamese network, which is a multivariate machine learning method suitable for small sample analysis, and K-nearest neighbor (KNN) were cascaded as the classifier (Siamese-KNN). In the leave-one-out cross-validation, the Siamese-KNN achieved an accuracy of 83.78%, which was substantially higher than results from traditional classifiers. RSFC patterns contributing to the prediction consisted of brain networks related to salience, reward, self-referential and cognitive processing. Further RSFC feature analysis indicated that the connection strength between frontal and parietal cortices was stronger in the optimal versus the suboptimal weight loss group. These findings show that specific RSFC patterns could be used as neuroimaging biomarkers to predict individual weight loss post-surgery and assist in personalized diagnosis for treatment of obesity.
Article
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 .
Thesis
Obesity is a substantial problem in the U.S., with growing rates particularly at early developmental stages (e.g., childhood, adolescents). Several factors may contribute to the development of overeating and obesity, including elevated craving in response to food-related cues, individual susceptibility to food-related cues, and neural changes associated with behavioral phenotypes implicated in obesity. The current dissertation aims to shed light on these contributing factors, in an effort to better understand obesity risk and contribute to the development of effective interventions. Study 1 aimed to test the incentive-sensitization theory of addiction by examining food motivation, hunger, and consumption in a cue-rich compared to neutral environment. Participants (n = 126) were randomized to either a naturalistic fast-food laboratory or a neutral laboratory, where they provided self-reported ratings of “wanting,” “liking,” and hunger, and engaged in a task assessing food motivation and food consumption. Study 1 found that “wanting,” hunger, and consumption were greater in the cue-rich compared to neutral laboratory, while “liking” did not differ between conditions. This study provides support for the incentive-sensitization theory as applied to eating behavior. Study 2 developed and tested a novel paradigm for identifying two phenotypes of cue-responsivity, sign-tracking and goal-tracking. Children aged 5-7 (n = 64) engaged in a Pavlovian conditioning task designed to assess propensity to engage with a cue (sign-tracking) versus the location of a reward (goal-tracking). Children then engaged in tasks assessing food motivation and inhibitory control. Contrary to hypotheses, Study 1 did not find a distinct goal-tracking phenotype, and did not find sign-tracking behavior to be associated with either food motivation or inhibitory control. Considerations for how to examine these phenotypes in future research are discussed. Study 3 examined how resting state functional connectivity (rsFC) relates to obesity, food consumption, food motivation, and inhibitory control in adolescents (n = 164) aged 13-16 who ranged from lean to obese. Participants completed tasks assessing food motivation and inhibitory control, then on a second visit underwent a resting-state scan and then completed a food consumption task in a cue-rich environment. Obesity and elevated food motivation were found to be marked by altered connectivity in areas in the salience network (e.g., caudate, NAcc, OFC) and the default mode network (e.g., PCC, hippocampus). However, obesity was not found to be associated with behavioral outcomes, thus these behaviors were not found to mediate associations between obesity and rsFC patterns. These findings provide suggestions as to effective prevention and intervention targets. The current dissertation provides evidence for a strong role of elevated food motivation (especially in the context of food cues) in the overconsumption of palatable foods. Clinical implications and suggestions for intervention are discussed.
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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.
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Electroacupuncture (EA) is a safe and effective method for treating obesity. However, how it modulates reward-related brain activity/functional connectivity and gut hormones remains unclear. We employed resting-state functional magnetic resonance imaging (RS-fMRI) and resting-state functional connectivity (RSFC) to investigate EA induced changes in resting-state activity and RSFC in reward-related regions and its association with gut hormones in overweight/obese subjects who received real (n = 20) and Sham (n = 15) stimulation. Results showed reduced leptin levels was positively correlated with reduced body mass index (BMI) and negatively correlated with increased cognitive-control as measured with Three-Factor-Eating-Questionnaire (TFEQ). Significant time effects on RSFC between dorsal caudate (DC) and precuneus were due to significant increased RSFC strength in both EA and Sham groups. In addition, increased RSFC of DC-precuneus was negatively correlated with reduced BMI and leptin levels in the EA group. Mediation analysis showed that the relationship between increased DC-precuneus RSFC strength and reduced BMI was mediated by reduced leptin levels. These findings reflect the association between EA-induced brain reward-related RSFC and leptin levels, and decreased leptin levels mediated altered DC-precuneus RSFC strength and consequent weight-loss, suggesting the potential role of EA in reducing weight and appetite.
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Independent component analysis (ICA) of functional mag- netic resonance imaging (fMRI) data reveals spatially inde- pendent patterns of functional activation. The purely data- driven approach of ICA makes statistical inference difficult. The purpose of this study was to develop a hybrid ICA in the frequency domain that enables statistical inference while preserving advantages of a data-driven ICA. Three normal volunteers were scanned with fMRI while they performed a working memory task. Their data were analyzed with fre- quency domain hybrid ICA. In each of the subjects, the pat- terns of activation corresponded to areas expected to be ac- tive during the fMRI task. This investigation demonstrates that a hybrid ICA in the frequency domain can statistically map functional activation while preserving the ability of ICA to blindly separate noise sources from the data.
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Functional magnetic resonance imaging (fMRI) was used to determine whether visual responses to food in the human amygdala and related corticolimbic structures would be selectively altered by changes in states of hunger. Participants viewed images of motivationall y relevant (food) and motivationally irrelevant (tool) objects while undergoing fMRI in alternately hungry and satiated conditions. Food- related visual stimuli elicited greater responses in the amygdala, parahippocampal gyrus, and anterior fusiform gyrus when participants were in a hungry state relative to a satiated state. The state-dependent activation of these brain structures did not generalize to the motivationally irrelevant objects. These results support the hypothesis that the amygdala and associated inferotemporal regions are involved in the integration of subjective interoceptive states with relevant sensory cues processed along the ventral visual stream. The brain's limited capacity for handling information necessi- tates the selective allocation of processing resources to stimuli that are relevant to current drives and motivational needs. How the brain assigns salience to environmental cues related to relevant events has yet to be fully understood. The amygdala may play an important role in this process because of its neural connections, which link interoceptive information with information regarding sensory events in the external world (Amaral, Price, Pitkanen, & Carmichael, 1992; Herzog & Van Hoesen, 1976). Although there is support for this function of the amygdala in nonhuman animals, the evidence is more tentative in the human brain. Animal studies have documented that the amygdala and asso- ciated limbic forebrain regions play a crucial role in the coordi-
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Although cells in many brain regions respond to reward, the cortical-basal ganglia circuit is at the heart of the reward system. The key structures in this network are the anterior cingulate cortex, the orbital prefrontal cortex, the ventral striatum, the ventral pallidum, and the midbrain dopamine neurons. In addition, other structures, including the dorsal prefrontal cortex, amygdala, hippocampus, thalamus, and lateral habenular nucleus, and specific brainstem structures such as the pedunculopontine nucleus, and the raphe nucleus, are key components in regulating the reward circuit. Connectivity between these areas forms a complex neural network that mediates different aspects of reward processing. Advances in neuroimaging techniques allow better spatial and temporal resolution. These studies now demonstrate that human functional and structural imaging results map increasingly close to primate anatomy.
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The APOE epsilon4 allele is a risk factor for late-life pathological changes that is also associated with anatomical and functional brain changes in middle-aged and elderly healthy subjects. We investigated structural and functional effects of the APOE polymorphism in 18 young healthy APOE epsilon4-carriers and 18 matched noncarriers (age range: 20-35 years). Brain activity was studied both at rest and during an encoding memory paradigm using blood oxygen level-dependent fMRI. Resting fMRI revealed increased "default mode network" (involving retrosplenial, medial temporal, and medial-prefrontal cortical areas) coactivation in epsilon4-carriers relative to noncarriers. The encoding task produced greater hippocampal activation in epsilon4-carriers relative to noncarriers. Neither result could be explained by differences in memory performance, brain morphology, or resting cerebral blood flow. The APOE epsilon4 allele modulates brain function decades before any clinical or neurophysiological expression of neurodegenerative processes.