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Alterations of the Salience Network in Obesity: A Resting-State fMRI Study
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.
Supplementary resource (1)
Data
August 2012
... It is worth noting that just like resting-state FC, task-based FC (in this case, during stress) can be computed as the correlation between the timeseries of pairs of brain regions [e.g., 13,46). FC was chosen as neural parameter due to the pivotal role of regional interplay for obesity [e.g., 13,19,47]. ASL was selected because it is a quantitative MRI method for measuring rCBF that is increasingly used in neuroscientific FC studies (see e.g., the review of Chen et al. [48]) due to its higher robustness to slow signal noise relative to that of the alternative blood-oxygenation-leveldependent (BOLD) fMRI technique [30]. ...
... Consistent with this function, insula shows enhanced activity to food cues [52] and its responses to food cues correlate positively with BMI [53]. Furthermore, insula and supramarginal gyrus are both parts of the salience resting-state network [47], whose function is to identify the most relevant stimuli for guiding subsequent behavior [54]. Consistently, heightened activity of this network was also reported for obese vs. non-obese people [47]. ...
... Furthermore, insula and supramarginal gyrus are both parts of the salience resting-state network [47], whose function is to identify the most relevant stimuli for guiding subsequent behavior [54]. Consistently, heightened activity of this network was also reported for obese vs. non-obese people [47]. Thus, consistent with the fact that heightened incentive salience was found to be one of if not the most important driver(s) of BMI in non-MS studies [13] and the involvement of anterior insula and supramarginal gyrus in (neural networks underlying) incentive salience of food stimuli, the link between BMI and these regions' FC found here is compatible with a Fig. 4 BMI and functional connectivity of stress-reactive brain regions. ...
Overweight and obesity can worsen disease activity in multiple sclerosis (MS). Although psychobiological stress processing is increasingly recognized as important obesity factor that is tightly connected to proinflammatory metabolic hormones and cytokines, its role for MS obesity remains unexplored. Consequently, we investigated the interplay between body mass index (BMI), neural stress processing (functional connectivity, FC), and immuno-hormonal stress parameters (salivary cortisol and T cell glucocorticoid [GC] sensitivity) in 57 people with MS (six obese, 19 over-, 28 normal-, and four underweight; 37 females, 46.4 ± 10.6 years) using an Arterial-Spin-Labeling MRI task comprising a rest and stress stage, along with quantitative PCR. Our findings revealed significant positive connections between BMI and MS disease activity (i.e., higher BMI was accompanied by higher relapse rate). BMI was positively linked to right supramarginal gyrus and anterior insula FC during rest and negatively to right superior parietal lobule and cerebellum FC during stress. BMI showed associations with GC functioning, with higher BMI associated with lower CD8⁺ FKBP4 expression and higher CD8⁺ FKBP5 expression on T cells. Finally, the expression of CD8⁺ FKBP4 positively correlated with the FC of right supramarginal gyrus and left superior parietal lobule during rest. Overall, our study provides evidence that body mass is tied to neuro-hormonal stress processing in people with MS. The observed pattern of associations between BMI, neural networks, and GC functioning suggests partial overlap between neuro-hormonal and neural-body mass networks. Ultimately, the study underscores the clinical importance of understanding multi-system crosstalk in MS obesity.
... Six studies were classified to have "Good" quality (Table II). Four studies used functional magnetic resonance imaging (fMRI) as an imaging method [22][23][24][25], three used MRI associated with diffusion tensor imaging (DTI) [26][27][28], and one used positron emission tomography (PET) [29]. ...
... Two studies used electroencephalography (EEG) [30,31] and one used magnetoencephalography (MEG) [32]. All selected studies investigated brain areas activated during a task that assessed cognitive function through executive function [25,26,27,28,29], reaction time and accuracy [22,24,[25][26][27][28]30,31], and memory [25,28,29,32]. Tuulari et al. [22] used imagery and cognitive control over food images. ...
... Two studies used electroencephalography (EEG) [30,31] and one used magnetoencephalography (MEG) [32]. All selected studies investigated brain areas activated during a task that assessed cognitive function through executive function [25,26,27,28,29], reaction time and accuracy [22,24,[25][26][27][28]30,31], and memory [25,28,29,32]. Tuulari et al. [22] used imagery and cognitive control over food images. ...
Introdução: A obesidade é considerada uma desordem multifatorial influenciada por fatores hormonais, dietéticos, comportamentais, emocionais, atencionais e controle cognitivo que interferem no equilíbrio ingestão e gasto energético. A influência da obesidade no declínio cognitivo e prejuízos a funções e estruturas cerebrais além de sua associação com processos neurodegenerativos precoces tem sido observada. Objetivo: Esta revisão buscou identificar as áreas corticais mais ativadas em indivíduos obesos, investigar a existência de comprometimento cognitivo e a possível interferência no comportamento alimentar. Além disso, buscou-se identificar os métodos de neuroimagem mais utilizados para avaliação desses processos. Buscou-se estudos publicados 2006 e 2021. Foram pesquisadas as bases de dados indexadas PUBMED, LILACS e SCIELO. Foram selecionados estudos observacionais que comparassem indivíduos obesos (IMC > 30 kg/m²) e não obesos. Foi utilizado o Quality Assessment of Observational Cohort and Cross-Sectional Studies da National Heart, Lung and Blood Institute (NIH) para análise de qualidade metodológica. Resultados: Foram reportados 22.484 títulos. Após a aplicação dos critérios de elegibilidade, foram selecionados 154 artigos. Desses, onze foramincluídos para análise nesta revisão. Nesta análise, diferenças foram encontradas quanto ao tempo de reação, acurácia ou áreas cerebrais inativadas durante os testescognitvosou estímulos com figuras de comida entre os grupos estudados. Conclusão: Mudanças estruturais compatíveis com prejuízos na performance cognitiva a longo prazo foram identificadas, assim como alterações estruturais e funcionais que podem auxiliar o entendimento de comportamento alimentar compulsivo presente em indivíduos obesos.
... Childhood obesity has also been linked to altered organization and properties of reward and motor networks, including lower community structure (modularity) -a property that is critical to the efficiency of domain-specific computations in the brain and information processing [59]. Functional neuroimaging studies have linked obesity to aberrant connectivity specifically in circuits that support executive function and eating behaviors, including salience, reward and Default Mode (DM) networks [60][61][62][63][64][65][66][67][68][69][70][71]. A few studies have reported other obesity-related topological changes as well, such as reduced efficiency and small-worldness, across cortical and subcortical functional networks [72][73][74]. ...
... Extensive topological differences were also estimated in domain-specific functional networks, including attention, cognitive control, limbic, salience, reward, social and DM networks in youth with obesity and overweight relative to those normal BMI. Prior work has specifically identified obesity-related aberrant structural and functional connectivity, including in salience and reward networks [54,55,61,62,67,68]. Prior diffusion MRI studies have also reported changes in structural network properties, such as lower clustering coefficient, in youth with obesity [59]. ...
... Aberrant modulations of the topological properties of large-scale networks, particularly the DM, may adversely impact cognitive processing across domains, since the DM plays a ubiquitous role in cognitive function [115,116]. Aberrant changes in limbic, reward and salience networks in adolescence may have implications for addictive food behaviors, food reward processing and impaired control of food intake, not only in this period but also in adulthood [63,67,[117][118][119]. ...
Background/Objectives
Adverse effects of excess BMI (affecting 1 in 5 children in the US) on brain circuits during neurodevelopmentally vulnerable periods are incompletely understood. This study investigated BMI-related alterations in maturating functional networks and their underlying brain structures, and high-level cognition in early adolescence.
Subjects/Methods
Cross-sectional resting-state fMRI, structural sMRI, neurocognitive task scores, and BMI from 4922 youth [median (IQR) age = 120.0 (13.0) months, 2572 females (52.25%)] from the Adolescent Brain Cognitive Development (ABCD) cohort were analyzed. Comprehensive topological and morphometric network properties were estimated from fMRI and sMRI, respectively. Cross-validated linear regression models assessed correlations with BMI. Results were reproduced across multiple fMRI datasets.
Results
Almost 30% of youth had excess BMI, including 736 (15.0%) with overweight and 672 (13.7%) with obesity, and statistically more Black and Hispanic compared to white, Asian and non-Hispanic youth (p < 0.01). Those with obesity or overweight were less physically active, slept less than recommended, snored more frequently, and spent more time using an electronic device (p < 0.01). They also had lower topological efficiency, resilience, connectivity, connectedness and clustering in Default-Mode, dorsal attention, salience, control, limbic, and reward networks (p ≤ 0.04, Cohen’s d: 0.07-0.39). Lower cortico-thalamic efficiency and connectivity were estimated only in youth with obesity (p < 0.01, Cohen’s d: 0.09-0.19). Both groups had lower cortical thickness, volume and white matter intensity in these networks’ constituent structures, particularly anterior cingulate, entorhinal, prefrontal, and lateral occipital cortices (p < 0.01, Cohen’s d: 0.12-0.30), which also mediated inverse relationships between BMI and regional functional topologies. Youth with obesity or overweight had lower scores in a task measuring fluid reasoning - a core aspect of cognitive function, which were partially correlated with topological changes (p ≤ 0.04).
Conclusions
Excess BMI in early adolescence may be associated with profound aberrant topological alterations in maturating functional circuits and underdeveloped brain structures that adversely impact core aspects of cognitive function.
... Obesity has become the focus of many public health efforts in the United States because of increasing prevalence over the last few decades. In addition to contributing greatly to health care costs (2), excess adiposity associated with obesity is considered a heritable neurobehavioral disorder that is highly sensitive to environmental conditions (3), a major risk factor for premature mortality from cardiovascular and metabolic diseases (4), and has recently been associated with negative cognitive (5-7) and brain (8)(9)(10)(11)(12)(13) health outcomes. Notably, children with obesity commonly become adults with obesity, with 52% of adults over the age of 18 yr considered overweight (1.9 billion adults) or obese (650 million adults) (1). ...
... Cognitive functions during childhood are sensitive to obesity and the health complications associated with obesity (5). Further, childhood obesity has been associated with magnetic resonance imaging (MRI) studies of brain structure (10)(11)(12) and function (fMRI) (8,9,13). Individual differences, such as adiposity and obesity, have been associated with variance in brain structures among children and adolescents. ...
... Further, fMRI studies have identified differences in resting-state functional connectivity (RSFC) associated with obesity across the life span. In adults, obesity has been associated with alterations in salience network connectivity (9) and specific reductions in activity in brain regions associated with memory (hippocampus, angular gyrus, dorsolateral prefrontal cortex) compared with their normal weight counterparts during tasks of episodic memory (8). Collectively, cognitive and brain studies demonstrate robust evidence for negative associations among children and adults with obesity. ...
Purpose:
Childhood obesity is a global health concern, with >340 million youth considered overweight or obese. In addition to contributing greatly to health care costs, excess adiposity associated with obesity is considered a major risk factor for premature mortality from cardiovascular and metabolic diseases, and is also negatively associated with cognitive and brain health. A complementary line of research highlights the importance of cardiorespiratory fitness, a byproduct of engaging in physical activity, on an abundance of health factors, including cognitive and brain health.
Methods:
This study investigated the relationship among excess adiposity (visceral adipose tissue [VAT], subcutaneous abdominal adipose tissue [SAAT]), total abdominal adipose tissue [TAAT], whole-body percent fat [WB%FAT], Body Mass Index (BMI), and fat-free cardiorespiratory fitness (FF-VO2max) on resting-state functional connectivity (RSFC) in 121 (f = 68) children (7-11 years) using a data-driven whole-brain multi-voxel pattern analysis.
Results:
Multi-voxel pattern analysis revealed brain regions that were significantly associated with VAT, BMI, WB%FAT and FF-VO2 measures. Yeo's (2011) RSFC-based 7-network cerebral cortical parcellation was used for labeling the results. Post hoc seed-to-voxel analyses found robust negative correlations of VAT and BMI with areas involved in the visual, somatosensory, dorsal attention, ventral attention, limbic, fronto-parietal and default mode networks. Further, positive correlations of FF-VO2 were observed with areas involved in the ventral attention and fronto-parietal networks. These novel findings indicate that negative health factors in childhood may be selectively and negatively associated with the 7 Yeo-defined functional networks, yet positive health factors (FF-VO2) may be positively associated with these networks.
Conclusions:
These novel results extend the current literature to suggest that BMI and adiposity are negatively associated with, and cardiorespiratory fitness (corrected for fat-free mass) is positively associated with, resting state functional connectivity networks in children.
... 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). ...
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.
... 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). ...
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.
... 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 . ...
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.
... 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]. ...
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.
... 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. ...
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.
... 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]. ...
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.
... 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 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 (Stoeckel et al. 2008;Volkow et al. 2011;Garcia-Garcia et al. 2013), and SN has been reported to involve rapid processing of internal/interoceptive salient stimuli (Garcia-Garcia et al. 2013). The SN integrates processed internal sensory information on which executive control network (ECN) operates to regulate reward and cognitive functions (Seeley 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 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 (Stoeckel et al. 2008;Volkow et al. 2011;Garcia-Garcia et al. 2013), and SN has been reported to involve rapid processing of internal/interoceptive salient stimuli (Garcia-Garcia et al. 2013). The SN integrates processed internal sensory information on which executive control network (ECN) operates to regulate reward and cognitive functions (Seeley et al. 2007). ...
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.
... In contrast, BF children also showed lower connectivity between the MH and reward-related brain areas compared to the EF-fed children group. More specifically, MH, insula, and putamen are key regions within the salience network, which is involved in the processing of salience stimuli, eating motivation, and the hedonic-driven desire to consume food (69)(70)(71)(72). In this sense, putamen and insula are known to promote approaching behavior to foods with palatable properties, i.e., foods with high content of lipids, simple sugars, and energy (69). ...
... In contrast, BF children also showed lower connectivity between the MH and reward-related brain areas compared to the EF-fed children group. More specifically, MH, insula, and putamen are key regions within the salience network, which is involved in the processing of salience stimuli, eating motivation, and the hedonic-driven desire to consume food (69)(70)(71)(72). In this sense, putamen and insula are known to promote approaching behavior to foods with palatable properties, i.e., foods with high content of lipids, simple sugars, and energy (69). ...
Breastfeeding (BF) is the gold standard in infant nutrition; knowing how it influences brain connectivity would help understand the mechanisms involved, which would help close the nutritional gap between infant formulas and breast milk. We analyzed potential long-term differences depending on the diet with an experimental infant formula (EF), compared to a standard infant formula (SF) or breastfeeding (BF) during the first 18 months of life on children's hypothalamic functional connectivity (FC) assessed at 6 years old. A total of 62 children participating in the COGNIS randomized clinical trial (Clinical Trial Registration: www.ClinicalTrials.gov , identifier: NCT02094547) were included in this study. They were randomized to receive an SF ( n = 22) or a bioactive nutrient-enriched EF ( n = 20). BF children were also included as a control study group (BF: n = 20). Brain function was evaluated using functional magnetic resonance imaging (fMRI) and mean glucose levels were collected through a 24-h continuous glucose monitoring (CGM) device at 6 years old. Furthermore, nutrient intake was also analyzed during the first 18 months of life and at 6 years old through 3-day dietary intake records. Groups fed with EF and BF showed lower FC between the medial hypothalamus (MH) and the anterior cingulate cortex (ACC) in comparison with SF-fed children. Moreover, the BF children group showed lower FC between the MH and the left putamen extending to the middle insula, and higher FC between the MH and the inferior frontal gyrus (IFG) compared to the EF-fed children group. These areas are key regions within the salience network, which is involved in processing salience stimuli, eating motivation, and hedonic-driven desire to consume food. Indeed, current higher connectivity found on the MH-IFG network in the BF group was associated with lower simple sugars acceptable macronutrient distribution ranges (AMDRs) at 6 months of age. Regarding linoleic acid intake at 12 months old, a negative association with this network (MH-IFG) only in the BF group was found. In addition, BF children showed lower mean glucose levels compared to SF-fed children at 6 years old. Our results may point out a possible relationship between diet during the first 18 months of life and inclined proclivity for hedonic eating later in life.
Clinical trial registration
https://www.clinicaltrials.gov/ , identifier NCT02094547.
... It is known that executive control and the salience network serve control functions during external goal-directed tasks and act separately according to a model of functional segregation [43][44][45]. More in-depth, salience network is involved in a broad monitoring function, perceiving salient stimuli regardless of relevance [46]; on the other hand, the executive control network is related to selective external stimuli matching task goals [47]. ...
PurposeTo compare resting-state functional connectivity (RSFC) of obese patients responders or non-responders to sleeve gastrectomy (SG) with a group of obese patients with no past medical history of metabolic or bariatric surgery.MethodsMR images were acquired at 1.5 Tesla. Resting-state fMRI data were analyzed with statistical significance threshold set at p < 0.05, family-wise error (FWE) corrected.ResultsSixty-two subjects were enrolled: 20 controls (age range 25–64; 14 females), 24 responders (excess weight loss > 50%; age range 23–68; 17 females), and 18 non-responders to sleeve gastrectomy (SG) (excess weight loss < 50%; age range 23–67; 13 females). About within-network RSFC, responders showed significantly lower RSFC with respect to both controls and non-responders in the default mode and frontoparietal networks, positively correlating with psychological scores. Non-responders showed significantly higher (p < 0.05, family-wise error (few) corrected) RSFC in regions of the lateral visual network as compared to controls. Regarding between-network RSFC, responders showed significantly higher anti-correlation between executive control and salience networks (p < 0.05, FWE corrected) with respect to both controls and non-responders. Significant positive correlation (Spearman rho = 0.48, p = 0.0012) was found between % of excess weight loss and executive control-salience network RSFC.Conclusion
There are differences in brain functional connectivity in either responders or non-responders patients to SG. The present results offer new insights into the neural correlates of outcome in patients who undergo SG and expand knowledge about neural mechanisms which may be related to surgical response.
... 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 ...
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.
... 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 ...
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.
... In participants with excess weight, a differential 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. ...
Hunger and satiety 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 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 (BMI). Forty participants (16 overweight/obese) underwent two resting-state functional MRI scans whilst being fasted and sated. The 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: 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, 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 homeostatic state. 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.
... 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. ...
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.
... Salience network (SN) is considered to a core hub in exploring salient stimuli, and modulate the attention and working memory resources for that [53,54] . The crucial view is the SN mediate dynamic communication between other neural circuits referring to internally oriented attention and externally oriented cognition [53,55] . This study showed both hyper-(SN seeds and regions of bilateral anterior insula and bilateral inferior frontal gyrus) and hypo-connectivity (SN seeds and region of bilateral anterior cingulate gyrus and middle cingulate gyrus) within the SN compared PBD-I with PBD-II. ...
Background: The symptoms of pediatric bipolar disorder (PBD)-I and PBD-II differ, but accurate identification at an early stage is difficult and may prevent effective treatment of this disorder. Therefore, it is urgent to elucidate a biological marker based on objective imaging indicators to help distinguish the two. Therefore, this research aims to compare the functional connectivity between PBD-I patient and PBD-II patient in different brain networks.
Methods: Our study enrolled 31 PBD-I and 23 PBD-II patients from 12 to 17 years of age. They were analyzed by resting state-functional connectivity through Independent component analysis（ICA）.
Results: We found differences between PBD-I and PBD-II in functional connectivity of the default network, frontoparietal network, salience network and limbic system. In addition, the clinical features, cognitive functions are associated with the functional connectivity of the intrinsic networks in PBD-I and PBD-II separately.
Conclusion: This research is the first to find differences in functional connectivity between PBD-I and PBD-II, suggesting that abnormality of the functional connectivity within large networks may be biomarkers that help differentiate PBD-I from PBD-II in the future.
... 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). ...
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.
... Several core functional brain networks have been identified (Deco, Jirsa, & McIntosh, 2010), including the salience network (Seeley, 2019), the central-executive network , and the default mode network (Harrison et al., 2008;Raichle, 2015). Alterations in the functional connectivity of such networks are associated with a wide variety of disorders, including obesity (García-García et al., 2013), schizophrenia (Whitfield-Gabrieli & Ford, 2012), and depression (Mulders, van Eijndhoven, Schene, Beckmann, & Tendolkar, 2015), and functional connectivity can predict treatment response (Cao et al., 2018;Moreno-Ortega et al., 2019;Reggente et al., 2018). ...
Human cognition arises from information exchange within and between functionally connected brain networks. Alterations in such signal propagation across networks are linked to numerous disorders. Brain-wide signal propagation can be experimentally studied with simultaneous transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI), where TMS pulses introduce a signal at a certain network node and fMRI charts its propagation through the network. Yet, this approach ignores the fact that the (network) impact of a TMS pulse depends on brain state, where brain state fluctuates spontaneously from moment to moment (e.g. oscillatory state) as well as depending on what a participant does (neurocognitive state). Here, we assessed TMS-evoked fMRI activations as a function of neurocognitive state (eyes open versus eyes closed in complete darkness) and oscillatory state (low versus high pre-TMS alpha power, as measured with simultaneous electroencephalography (EEG)). We applied supra- versus sub-threshold triple-pulse TMS to the right posterior parietal cortex in eight participants, while simultaneously recording EEG and fMRI during two different ocular states. In this first application of the multimodal TMS-EEG-fMRI paradigm to a cognitive network hub, we did not find evidence for a brain state modulation of TMS-induced signal propagation. Instead, we found state-independent TMS-evoked fMRI responses mostly in sensory areas such as the insula, superior temporal gyrus, anterior cingulate cortex, and thalamus, but also in the frontal eye fields. Interestingly, neurocognitive state did seem to modulate the fMRI response to indirect TMS effects such as sensory stimulation. These results lead to several important insights for future cognitive multimodal TMS experiments.
... 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. ...
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). ...
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 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. ...
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.
... /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. ...
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.
... 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. ...
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.
... 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. ...
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.
... 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. ...
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.
... 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. ...
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.
Objective
This study aimed to explore the relationship between white matter hyperintensities (WMHs) and cognitive impairment related to metabolic syndrome (MetS) and the underlying neural network mechanisms.
Methods
This cross‐sectional study included 50 participants with MetS and WMHs (MetS‐WMHs), 45 with MetS without WMHs, and 50 control participants. All participants underwent resting‐state functional magnetic resonance imaging and a detailed cognitive evaluation. A graph theory analysis based on resting‐state functional magnetic resonance imaging was conducted to calculate functional network properties. A mediation analysis was conducted to determine the relationship between WMHs and MetS‐related cognitive impairment.
Results
Compared with the control group, the participants in the MetS‐WMHs group displayed lower global efficiency, local efficiency, and nodal efficiency, mainly located in the regions of the salience network. Furthermore, a significant correlation was observed between functional network efficiency and cognitive performance. Mediation analysis indicated that WMHs served as a mediating variable between MetS and cognitive decline, affecting attention/executive function, language, and global cognitive function.
Conclusions
WMHs mediated the association between MetS and cognitive function, with a decline in the efficiency of functional brain networks being a probable neural mechanism.
Introduction:
Brain insulin reactivity has been reported in connection with systematic energy metabolism, enhancement in cognition, olfactory sensitivity and neuroendocrine circuits. High receptor densities exist in regions important for sensory processing. The main aim of the study was to examine whether intranasal insulin would modulate the activity of areas in charge of olfactory-visual integration.
Methods:
As approach, a placebo-controlled double-blind within crossover design was chosen. The experiments were conducted in a research unit of a university hospital. On separate mornings, twenty-six healthy normal-weight males aged between 19 and 31 years received either 40 IU intranasal insulin or placebo vehicle. Subsequently, they underwent 65 min of functional magnetic resonance imaging whilst performing an odor identification task. Functional brain activations of olfactory, visual and multisensory integration as well as insulin vs. placebo were assessed. Regarding the odor identification task, reaction time, accuracy, pleasantness and intensity measurements were taken to examine the role of integration and treatment. Blood samples were drawn to control for peripheral hormone concentrations.
Results:
Intranasal insulin administration during olfactory-visual stimulation revealed strong bilateral engagement of frontoinsular cortices, anterior cingulate, prefrontal cortex, mediodorsal thalamus, striatal and hippocampal regions (p ≤ .001 FWE corrected). In addition, the integration contrast showed increased activity in left intraparietal sulcus, left inferior frontal gyrus, left superior frontal gyrus and left middle frontal gyrus (p ≤ .013 FWE corrected).
Conclusions:
Intranasal insulin application in lean men led to enhanced activation in multisensory olfactory-visual integration sites and salience hubs which indicates stimuli valuation modulation. This effect can serve as a basis for understanding the connection of intracerebral insulin and olfactory-visual processing.
Introduction:
The habenula, a brain region involved in aversion, might negatively modulate caloric intake. Functional Magnetic Resonance Imaging (fMRI) studies reported associations between weight loss and habenula functional connectivity. However, whether habenula resting state functional connectivity (rsFC) and reward-related activity is altered in obesity is yet unknown.
Methods:
Using data from the Human Connectome Project, we included 300 subjects with various BMIs and a healthy long-term blood glucose (HbA1c). Additionally, we investigated a potential BMI x HbA1c interaction in a separate cohort including subjects with prediabetes (n = 72). Habenula rsFC was assessed using a region of interest (ROI)-to-ROI analysis. Furthermore, a separate analysis using gambling task fMRI data focussed on reward-related habenular activity.
Results:
We did not find an association between BMI and habenular rsFC for any of the ROIs. For the exploratory analysis of the BMI x HbA1c effect, a significant interaction effect was found for the habenula-ventral tegmental area (VTA) connection, but this did not survive multiple comparisons correction. Monetary punishment compared to reward activated the bilateral habenula in the BMI sample, but this activity was not associated with BMI.
Discussion:
In conclusion, we did not find evidence for an association between BMI and habenula rsFC or reward-related activity. However, there might be an interaction between BMI and HbA1c for the habenula-VTA rsFC, suggestive of a role of habenula in glucose regulation. Future studies should focus on metabolic parameters in their experimental design, to confirm our findings and explore the precise role of the habenula in metabolism.
Obesity and components of the metabolic syndrome (MetS) are associated with differences in brain structure and function and in general and food-related cognition in adults. Here, we review evidence for similar phenomena in children and adolescents, with a focus on the implications of extant research for possible underlying mechanisms and potential interventions for obesity and MetS in youth. Current evidence is limited by a relative reliance on small cross-sectional studies. However, we find that youth with obesity and MetS or MetS components show differences in brain structure, including alterations in grey matter volume and cortical thickness across brain regions subserving reward, cognitive control and other functions, as well as in white matter integrity and volume. Children with obesity and MetS components also show some evidence for hyperresponsivity of food reward regions and hyporesponsivity of cognitive control circuits during food-related tasks, altered brain responses to food tastes, and altered resting-state connectivity including between cognitive control and reward processing networks. Potential mechanisms for these findings include neuroinflammation, impaired vascular reactivity, and effects of diet and obesity on myelination and dopamine function. Future observational research using longitudinal measures, improved sampling strategies and study designs, and rigorous statistical methods, promises to further illuminate dynamic relationships and causal mechanisms. Intervention studies targeted at modifiable biological and behavioural factors associated with paediatric obesity and MetS can further inform mechanisms, as well as test whether brain and behaviour can be altered for beneficial outcomes.
Objective:
Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level.
Methods:
In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied.
Results:
Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD.
Conclusions:
Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.
A growing body of preclinical and clinical literature suggests that brain-gut-microbiota interactions may contribute to obesity pathogenesis. In this study, we use a machine learning approach to leverage the enormous amount of microstructural neuroimaging and fecal metabolomic data to better understand key drivers of the obese compared to overweight phenotype. Our findings reveal that although gut-derived factors play a role in this distinction, it is primarily brain-directed changes that differentiate obese from overweight individuals. Of the key gut metabolites that emerged from our model, many are likely at least in part derived or influenced by the gut-microbiota, including some amino-acid derivatives. Remarkably, key regions outside of the central nervous system extended reward network emerged as important differentiators, suggesting a role for previously unexplored neural pathways in the pathogenesis of obesity.
Over the past 50 years, our food supply has changed dramatically. Now, much of our food is considered to be highly processed, and some have argued that this has significantly contributed to the obesity epidemic. While studies of food addictions are becoming more accepted and are attracting more scientific and media interest, the notion tve intake of certain types of foods can produce aspects of substance use disorder remains controversial. Many studies have demonstrated that highly palatable foods can lead not only to criteria of substance use disorder and addiction as defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), but also neurochemical changes in brain reward systems that regulate addictive behaviors. In this chapter, we review the historical and latest research on the addictive nature of highly processed food, with a special focus on causes of food addiction, long-term effects of addictive overeating, and the treatment landscape. Further, this chapter reviews how food addiction may relate to, as well as inform treatments for, other addiction, including alcohol abuse, drug use, and gambling.
Background
Obesity is a disease that may involve disrupted connectivity of brain networks. Bariatric surgery is an effective treatment for obesity, and the positive effects on obesity-related conditions may be enhanced by exercise. Herein, we aimed to investigate the possible synergistic effects of Roux-en-Y Gastric Bypass (RYGB) and exercise training on brain functional networks.
Methods
Thirty women eligible for bariatric surgery were randomly assigned to a Roux-en-Y gastric bypass (RYGB: n = 15, age = 41.0 ± 7.3 years) or RYGB plus Exercise Training (RYGB + ET: n = 15, age = 41.9 ± 7.2 years). Clinical, laboratory, and brain functional connectivity parameters were assessed at baseline, and 3 (POST3) and 9 months (POST9) after surgery. The 6-month, three-times-a-week, exercise intervention (resistance plus aerobic exercise) was initiated 3 months post-surgery (for RYGB + ET).
Results
Exercise superimposed on bariatric surgery (RYGB + ET) increased connectivity between hypothalamus and sensorial regions (seed-to-voxel analyses of hypothalamic connectivity), and decreased default mode network (DMN) and posterior salience (pSAL) network connectivity (ROI-to-ROI analyses of brain networks connectivity) when compared to RYGB alone (all p-FDR < 0.05). Increases in basal ganglia (BG) network connectivity were only observed in the exercised training group (within-group analyses).
Conclusion
Exercise training is an important component in the management of post-bariatric patients and may improve the hypothalamic connectivity and brain functional networks that are involved in controlling food intake.
Trial registration
Clinicaltrial.gov: NCT02441361.
Background
Obesity is a multi-systemic disease with complex etiology. And consistent evidence indicated obesity or overweight subjects render brain structure changes. Increasing evidence indicates these subjects have shown widespread structural brain gray matter volume (GMV) changes. However, results from other neuroimaging studies have been inconsistent. Consequently, the question remains whether body mass index (BMI), a gold standard to define obesity/overweight, is associated with brain structural changes.Methods
This study will apply an updated meta-analysis of voxel-based GMV studies to compare GMV changes in overweight and obese subjects. Online databases were used to build on relevant studies published before May 2022. The updated Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) explores GMV changes in individuals with overweight and obesity and further examines the correlation between GMV and obesity-related variables, specifically body mass index (BMI).ResultsThis research included fourteen studies and provided a whole-brain analysis of GMV distribution in overweight and obese individuals. It revealed lower GMV in brain regions, including the left putamen and right precentral gyrus, in individuals with overweight and obesity compared to lean controls. Further, meta-regression analyses revealed GMV in the left middle occipital gyrus was negatively correlated with the BMI of the whole sample.ConclusionGMV decreased was reported in reward circuit processing areas and sensorimotor processing areas of individuals with overweight and obesity diagnoses, suggesting an underlying structural basis for reward processing and sensorimotor processing dysregulation in overweight and obese subjects. Our results also suggest that GMV in occipital gyrus, a key region for food visual and gustatory encoding, is negatively associated with BMI. These results provide further evidence for the dysregulated reward circuit in individuals with overweight and obesity.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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-
An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them.
Correlations in spontaneous brain activity provide powerful access to large-scale organizational principles of the CNS. However, making inferences about cognitive processes requires a detailed understanding of the link between these couplings and the structural integrity of the CNS. We studied the impact of multiple sclerosis, which leads to the severe disintegration of the central white matter, on functional connectivity patterns in spontaneous cortical activity. Using a data driven approach based on the strength of a salient pattern of cognitive pathology, we identified distinct networks that exhibit increases in functional connectivity despite the presence of strong and diffuse reductions of the central white-matter integrity. The default mode network emerged as a core target of these connectivity modulations, showing enhanced functional coupling in bilateral inferior parietal cortex, posterior cingulate, and medial prefrontal cortex. These findings imply a complex and diverging relation of anatomical and functional connectivity in early multiple sclerosis and, thus, add an important observation for understanding how cognitive abilities and CNS integrity may be reflected in the intrinsic covariance of functional signals.
The majority of research on obesity (OB) has focused primarily on clinical features (eating behavior, adiposity measures) or peripheral appetite-regulatory peptides (leptin, ghrelin). However, recent functional neuroimaging studies have demonstrated that some reward circuitry regions that are associated with appetite-regulatory hormones are also involved in the development and maintenance of OB. Prader-Willi syndrome (PWS), characterized by hyperphagia and hyperghrelinemia reflecting multi-system dysfunction in inhibitory and satiety mechanisms, serves as an extreme model of genetic OB. Simple (non-PWS) OB represents an OB-control state.
This study investigated subcortical food motivation circuitry and prefrontal inhibitory circuitry functioning in response to food stimuli before and after eating in individuals with PWS compared with OB. We hypothesized that groups would differ in limbic regions (that is, hypothalamus, amygdala) and prefrontal regions associated with cognitive control (that is, dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC) after eating.
A total of 14 individuals with PWS, 14 BMI- and age-matched individuals with OB, and 15 age-matched healthy-weight controls viewed food and non-food images while undergoing functional MRI before (pre-meal) and after (post-meal) eating. Using SPM8, group contrasts were tested for hypothesized regions: hypothalamus, nucleus accumbens (NAc), amygdala, hippocampus, OFC, medial PFC and DLPFC.
Compared with OB and HWC, PWS demonstrated higher activity in reward/limbic regions (NAc, amygdala) and lower activity in the hypothalamus and hippocampus in response to food (vs non-food) images pre-meal. Post meal, PWS exhibited higher subcortical activation (hypothalamus, amygdala, hippocampus) compared with OB and HWC. OB showed significantly higher activity versus PWS and HWC in cortical regions (DLPFC, OFC) associated with inhibitory control.
In PWS, compared with OB per se, results suggest hyperactivations in subcortical reward circuitry and hypoactivations in cortical inhibitory regions after eating, which provides evidence of neural substrates associated with variable abnormal food motivation phenotypes in PWS and simple OB.
To examine the association between eating in the absence of hunger (EAH) and adiposity in children.
Two cross-sectional studies in community settings.
For study 1, 348 children (178 girls and 170 boys) aged 7-9 years were recruited as part of the Physical Exercise and Appetite in Children Study. In study 2, participants were a subsample of children aged 9-12 years (N=316; 192 girls and 124 boys) from the Twins Early Development Study.
EAH was operationalized as intake of highly palatable sweet snacks after a mixed meal at school (study 1) or home (study 2). Weight (kg) and height (m) measurements were used to calculate the body mass index (BMI) s.d. scores. Children were grouped using the standard criteria for underweight, healthy weight, overweight and obesity. The healthy weight range was further subdivided into lower healthy weight (<or=50th centile) and higher healthy weight (>50th centile) to examine the distribution of EAH across the adiposity continuum.
In both studies, EAH showed a significant positive association with adiposity in boys after adjusting for covariates (P<0.001), with a linear increase in the intake across underweight, healthy weight and overweight groups. The association between EAH and adiposity was not significant in girls in either study, although in study 1, results showed a quadratic trend, with EAH increasing through the underweight and healthy weight ranges and decreasing in overweight and obese groups.
EAH is a behavioural phenotype that is not specific to overweight children but instead shows a graded association with adiposity across the weight continuum, particularly in boys. In this study, the effect was less pronounced in girls, which may reflect social desirability pressures constraining food intake among heavier girls.
Cerebral cortical activity is heavily influenced by interactions with the basal ganglia. These interactions occur via cortico-basal ganglia-thalamo-cortical loops. The putamen is one of the major sites of cortical input into basal ganglia loops and is frequently activated during pain. This activity has been typically associated with the processing of pain-related motor responses. However, the potential contribution of putamen to the processing of sensory aspects of pain remains poorly characterized. In order to more directly determine if the putamen can contribute to sensory aspects of pain, nine individuals with lesions involving the putamen underwent both psychophysical and functional imaging assessment of perceived pain and pain-related brain activation. These individuals exhibited intact tactile thresholds, but reduced heat pain sensitivity and widespread reductions in pain-related cortical activity in comparison with 14 age-matched healthy subjects. Using magnetic resonance imaging to assess structural connectivity in healthy subjects, we show that portions of the putamen activated during pain are connected not only with cortical regions involved in sensory-motor processing, but also regions involved in attention, memory and affect. Such a framework may allow cognitive information to flow from these brain areas to the putamen where it may be used to influence how nociceptive information is processed. Taken together, these findings indicate that the putamen and the basal ganglia may contribute importantly to the shaping of an individual subjective sensory experience by utilizing internal cognitive information to influence activity of large areas of the cerebral cortex.
Objective:
Studies suggest that cognitive deficits and attentional biases play a role in the development and maintenance of obesity and eating disorders. In this study, we simultaneously examine attentional biases, as well as inhibitory control and mental flexibility, which are keys to controlling unwanted behaviors and thoughts in obese patients with and without binge eating disorder.
Methods:
16 obese patients with binge eating disorder and 16 patients without binge eating disorder were compared with 16 normal-weight controls on a "food/body-mental flexibility task", which allows the investigation of inhibitory control, mental flexibility and attention for stimuli related to the body and food.
Results:
All obese patients made significantly more errors (i.e., pressing a key when a distracter displayed) and more omissions (i.e., not pressing a key when a target displayed) than controls in both food and body sections of the task. Obese participants with binge eating disorder made significantly more errors and omissions than those without binge eating disorder. No difference between groups was found concerning mental flexibility and cognitive biases for food- and body-related targets.
Discussion:
These results suggest that obese patients have a general inhibition problem and difficulty focusing attention, which do not depend on the types of stimuli processed. The results also suggest that these cognitive deficits are more severe in obese patients with binge eating disorder, which indicates that there is a continuum of increasing inhibition and cognitive problems with increasingly disordered eating. These cognitive deficits may contribute to problematic eating behaviors.
Obese humans, compared with normal-weight humans, have less striatal D2 receptors and striatal response to food intake; weaker striatal response to food predicts weight gain for individuals at genetic risk for reduced dopamine (DA) signaling, consistent with the reward-deficit theory of obesity. Yet these may not be initial vulnerability factors, as overeating reduces D2 receptor density, D2 sensitivity, reward sensitivity, and striatal response to food. Obese humans also show greater striatal, amygdalar, orbitofrontal cortex, and somatosensory region response to food images than normal-weight humans do, which predicts weight gain for those not at genetic risk for compromised dopamine signaling, consonant with the reward-surfeit theory of obesity. However, after pairings of palatable food intake and predictive cues, DA signaling increases in response to the cues, implying that eating palatable food contributes to increased responsivity. Using fMRI, we tested whether normal-weight adolescents at high- versus low-risk for obesity showed aberrant activation of reward circuitry in response to receipt and anticipated receipt of palatable food and monetary reward. High-risk youth showed greater activation in the caudate, parietal operculum, and frontal operculum in response to food intake and in the caudate, putamen, insula, thalamus, and orbitofrontal cortex in response to monetary reward. No differences emerged in response to anticipated food or monetary reward. Data indicate that youth at risk for obesity show elevated reward circuitry responsivity in general, coupled with elevated somatosensory region responsivity to food, which may lead to overeating that produces blunted dopamine signaling and elevated responsivity to food cues.
Obesity is a risk factor for stroke and neurodegenerative disease. Excess body fat has been linked to impaired glucose metabolism, insulin resistance, and impulsivity and may be a precursor to decline in attention and executive cognitive function. Here, we investigated the effects of high BMI on regional cerebral blood flow (rCBF) using single photon emission computed tomography (SPECT) imaging in healthy subjects. A total of 16 adult men and 20 adult women were recruited from the community between January 2003 and July 2009 as part of a healthy brain study (HBS) conducted at the Amen Clinics, a private medical facility. Participants in the study were screened to exclude medical, neurological, and psychiatric conditions, including substance abuse. Subjects were categorized as normal or overweight according to BMI. Using a two sample t-test, we determined the effects of BMI on rCBF in normal vs. overweight subjects. Subjects were matched for age and gender. Statistical parametric mapping (SPM) revealed a higher BMI in healthy individuals that is associated with decreased rCBF in Broadmann areas 8, 9, 10, 11, 32, and 44, brain regions involved in attention, reasoning, and executive function (P < 0.05, corrected for multiple comparisons). We found that an elevated BMI is associated with decreased rCBF in the prefrontal cortex of a healthy cohort. These results indicate that elevated BMI may be a risk factor for decreased prefrontal cortex function and potentially impaired executive function.
The ability to resist the urge to eat requires the proper functioning of neuronal circuits involved in top-down control to oppose the conditioned responses that predict reward from eating the food and the desire to eat the food. Imaging studies show that obese subjects might have impairments in dopaminergic pathways that regulate neuronal systems associated with reward sensitivity, conditioning and control. It is known that the neuropeptides that regulate energy balance (homeostatic processes) through the hypothalamus also modulate the activity of dopamine cells and their projections into regions involved in the rewarding processes underlying food intake. It is postulated that this could also be a mechanism by which overeating and the resultant resistance to homoeostatic signals impairs the function of circuits involved in reward sensitivity, conditioning and cognitive control.
One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for 8 standard statistical tests: (1) the difference between independent means, (2) the significance of a product-moment correlation, (3) the difference between independent rs, (4) the sign test, (5) the difference between independent proportions, (6) chi-square tests for goodness of fit and contingency tables, (7) 1-way analysis of variance (ANOVA), and (8) the significance of a multiple or multiple partial correlation.
Consistent with the theory that individuals with hypofunctioning reward circuitry overeat to compensate for a reward deficit, obese versus lean humans have fewer striatal D2 receptors and show less striatal response to palatable food intake. Low striatal response to food intake predicts future weight gain in those at genetic risk for reduced signaling of dopamine-based reward circuitry. Yet animal studies indicate that intake of palatable food results in downregulation of D2 receptors, reduced D2 sensitivity, and decreased reward sensitivity, implying that overeating may contribute to reduced striatal responsivity. Thus, we tested whether overeating leads to reduced striatal responsivity to palatable food intake in humans using repeated-measures functional magnetic resonance imaging. Results indicated that women who gained weight over a 6 month period showed a reduction in striatal response to palatable food consumption relative to weight-stable women. Collectively, results suggest that low sensitivity of reward circuitry increases risk for overeating and that this overeating may further attenuate responsivity of reward circuitry in a feedforward process.
The intensity of the taste of a food is affected mostly by the amount of sugars (mono- and disaccharides) or salt it contains. To season savory-tasting foods mainly table salt (NaCl) is used and to sweeten foods, sugars like sucrose are used. Foods with highly intense tastes are consumed in smaller amounts. The optimal taste intensity of a food is the intensity at which it is perceived as most pleasant. When taste intensity decreases or increases from optimal, the pleasantness of a food decreases. Here, we investigated the brain representation of sweet and salty taste intensity using functional magnetic resonance imaging. Fifteen subjects visited twice and tasted a range of 4 watery solutions (0-1 M) of either sucrose or NaCl in water. Middle insula activation increased with increasing concentration for both NaCl and sucrose. Despite similar subjective intensity ratings, anterior insula activation by NaCl increased more with concentration than that by sucrose. Amygdala activation increased with increasing NaCl concentration but not sucrose concentration. In conclusion, sweet and salty taste intensity are represented in the middle insula. Amygdala activation is only modulated by saltiness. Further research will need to extrapolate these results from simple solutions to real foods.
A distributed network of brain regions is linked to drug-related cue responding. However, the relationships between smoking cue-induced phasic activity and possible underlying differences in brain structure, tonic neuronal activity and connectivity between these brain areas are as yet unclear. Twenty-two smokers and 22 controls viewed smoking-related and neutral pictures during a functional arterial spin labeling scanning session. T1, resting functional, and diffusion tensor imaging data were also collected. Six brain areas, dorsal lateral prefrontal cortex (dlPFC), dorsal medial prefrontal cortex (dmPFC), dorsal anterior cingulate cortex/cingulate cortex, rostral anterior cingulate cortex (rACC), occipital cortex, and insula/operculum, showed significant smoking cue-elicited activity in smokers when compared with controls and were subjected to secondary analysis for resting state functional connectivity (rsFC), structural, and tonic neuronal activity. rsFC strength between rACC and dlPFC was positively correlated with the cue-elicited activity in dlPFC. Similarly, rsFC strength between dlPFC and dmPFC was positively correlated with the cue-elicited activity in dmPFC while rsFC strength between dmPFC and insula/operculum was negatively correlated with the cue-elicited activity in both dmPFC and insula/operculum, suggesting these brain circuits may facilitate the response to the salient smoking cues. Further, the gray matter density in dlPFC was decreased in smokers and correlated with cue-elicited activity in the same brain area, suggesting a neurobiological mechanism for the impaired cognitive control associated with drug use. Taken together, these results begin to address the underlying neurobiology of smoking cue salience, and may speak to novel treatment strategies and targets for therapeutic interventions.
Obesity indices (i.e. BMI, waist-to-hip ratio) show differential relationships to other health outcomes, though their association to neurocognitive outcome is unclear.
We examined whether central obesity would be more closely associated with cognitive function in 1,703 participants from the Baltimore Longitudinal Study of Aging.
Longitudinal mixed-effects regression models showed multiple obesity indices were associated with poorer performance in a variety of cognitive domains, including global screening measures, memory, and verbal fluency tasks. Obesity was associated with better performance on tests of attention and visuospatial ability. An obesity index by age interaction emerged in multiple domains, including memory and attention/executive function.
Obesity indices showed similar associations to cognitive function, and further work is needed to clarify the physiological mechanisms that link obesity to poor neurocognitive outcome.
Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
Combining genetic and neuroimaging techniques may elucidate the biological underpinnings of individual differences in neurophysiology and potential vulnerabilities to disease. The TaqIA A1 variant is associated with diminished dopamine D(2) receptor density, higher body mass, and food reinforcement. It also moderates the relationship between brain response to food and future weight gain. This suggests that the polymorphism is associated with a fundamental difference in the neurophysiology of food that may predispose toward overeating. An alternative possibility is that factors, such as impulsivity, eating style, reward drive, and perception, which may covary with the polymorphism, influence reward coding and eating behavior. To distinguish between these alternatives, we used functional magnetic resonance imaging to measure neural response to the ingestion of palatable and caloric milkshakes in healthy subjects with (A1+; n = 13) and without (A1-; n = 13) the TaqIA A1 allele. The groups were selected from a larger group to be matched for linked individual factors such as age, gender, education, body mass index, impulsivity, eating style, and perceptual responses to the milkshake. We demonstrate an interaction between genotype (A1+ vs A1-) and stimulus (milkshake vs a tasteless/odorless baseline) in the midbrain, thalamus, and orbital frontal cortex; whereas A1- shows increased responses to milkshake, A1+ shows decreased responses to milkshake relative to baseline. This interaction occurs despite similar ratings of milkshake pleasantness, intensity, and familiarity. We therefore conclude that there is a specific association between the TaqIA A1 polymorphism and brain response during ingestion of a palatable food.
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.
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.