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Affected connectivity organization of the reward system structure in obesity
... Twenty-four out of thirty-one retrieved studies 10,[23][24][25][26][27][28][29][30][31][32]46,[49][50][51][52][53][54][55][56][57][58][59] used samples of adults. Five studies 35,60-63 were performed on adolescents between 12 and 19 years, and two studies 64,65 were performed on children between 7 and 11 years. ...
... All selected studies used a cross-sectional approach. The majority of the studies (n = 24) 11,[23][24][25][26]30,31,35,46,49,50,52,[54][55][56][57][58][59][60][61][62][63][64][65] used BMI as a measure of obesity, while the rest used WC (n = 1), 28 total body fat percentage (n = 2), 10,27 both BMI and WC (n = 3), 32,51,53 or both BMI and waistto-hip ratio (WHR; n = 1). 29 Across selected studies, 23 studies 10,11,[23][24][25][26][27][28][29][30][31][50][51][52]54,57,58,[60][61][62][63][64]66 performed a whole-brain analysis, four studies 35,55,56,65 utilized an ROI approach, and four studies 32,46,49,53 used both approaches. ...
... The majority of the studies (n = 24) 11,[23][24][25][26]30,31,35,46,49,50,52,[54][55][56][57][58][59][60][61][62][63][64][65] used BMI as a measure of obesity, while the rest used WC (n = 1), 28 total body fat percentage (n = 2), 10,27 both BMI and WC (n = 3), 32,51,53 or both BMI and waistto-hip ratio (WHR; n = 1). 29 Across selected studies, 23 studies 10,11,[23][24][25][26][27][28][29][30][31][50][51][52]54,57,58,[60][61][62][63][64]66 performed a whole-brain analysis, four studies 35,55,56,65 utilized an ROI approach, and four studies 32,46,49,53 used both approaches. An overview of the included studies is presented in Table 2. ...
Obesity is a major global health problem leading to serious complications. It has been consistently associated with alterations in brain structure. Diffusion tensor imaging is used to examine brain white matter microstructure by assessing the dynamics of water diffusion in white matter tracts. Fractional anisotropy and mean diffusivity are two parameters measuring the directionality and rate of diffusion, respectively. Changes in these indices associated with obesity have been previously reported in numerous fiber tracts. This systematic review investigates microstructural white matter alterations in obesity using diffusion tensor imaging. A computerized search was performed in PubMed, Web of Science, and Livivo databases. Based on the inclusion/exclusion criteria, 31 cross-sectional studies comparing individuals with obesity and lean controls were identified. The studies included mixed-gender samples of children, young, middle-aged, and older adults. The majority of included studies reported decreased fractional anisotropy and increased mean diffusivity associated with elevated body mass index, suggesting white matter abnormalities. Nevertheless, a pattern of alterations is inconsistent across studies. This could be explained by several potential biases assessed by the National Institute of Health quality assessment tool. Furthermore, a direct assessment of body fat is recommended for a more accurate characterization of the brain–body relationship.
... Regarding the structural connectivity of the reward network in obesity, studies showed contradicting results, with both higher and lower structural connectivity between striatum and frontal cortex associated with weight status [27][28][29]. For other white matter tracts, studies have consistently reported associations of higher body mass index (BMI) and lower WM microstructure, possibly mediated by the negative metabolic impact of obesity [30,31]. ...
... In this study, we aimed to investigate the association of structural reward network connectivity, obesity, and genetic variations linked to obesity in a well-characterized population-based sample. Based on previous studies, we hypothesized that a higher BMI would relate to lower reward network connectivity [27]. More exploratory, we investigated whether FTO and Taq1A polymorphisms had interactive or independent effects on structural connectivity within the reward network [19,32]. ...
... We did not perform a formal power analysis before the study. Yet, we estimate our power to be sufficient (β = 0.98, based on N = 150 in the under-and normal-weight group, N = 197 in the overweight and obese group, alpha = 0.05 and the lowest Cohen's d reported in ref. [27] of d = 0.44 for FA CC difference, calculated using 'pwr' in R version 3.6.1). ...
Background
Obesity is of complex origin, involving genetic and neurobehavioral factors. Genetic polymorphisms may increase the risk for developing obesity by modulating dopamine-dependent behaviors, such as reward processing. Yet, few studies have investigated the association of obesity, related genetic variants, and structural connectivity of the dopaminergic reward network.
Methods
We analyzed 347 participants (age range: 20–59 years, BMI range: 17–38 kg/m²) of the LIFE-Adult Study. Genotyping for the single nucleotid polymorphisms rs1558902 (FTO) and rs1800497 (near dopamine D2 receptor) was performed on a microarray. Structural connectivity of the reward network was derived from diffusion-weighted magnetic resonance imaging at 3 T using deterministic tractography of Freesurfer-derived regions of interest. Using graph metrics, we extracted summary measures of clustering coefficient and connectivity strength between frontal and striatal brain regions. We used linear models to test the association of BMI, risk alleles of both variants, and reward network connectivity.
Results
Higher BMI was significantly associated with lower connectivity strength for number of streamlines (β = −0.0025, 95%—C.I.: [−0.004, −0.0008], p = 0.0042), and, to lesser degree, fractional anisotropy (β = −0.0009, 95%—C.I. [−0.0016, −0.00008], p = 0.031), but not clustering coefficient. Strongest associations were found for left putamen, right accumbens, and right lateral orbitofrontal cortex. As expected, the polymorphism rs1558902 in FTO was associated with higher BMI (F = 6.9, p < 0.001). None of the genetic variants was associated with reward network structural connectivity.
Conclusions
Here, we provide evidence that higher BMI correlates with lower reward network structural connectivity. This result is in line with previous findings of obesity-related decline in white matter microstructure. We did not observe an association of variants in FTO or near DRD2 receptor with reward network structural connectivity in this population-based cohort with a wide range of BMI and age. Future research should further investigate the link between genetics, obesity and fronto-striatal structural connectivity.
... In addition, network-based statistics (NBS) (i.e., edgewise comparisons) revealed a decreased functional network strength (i.e., lower functional connectivity) in the corticostriatal/cortico-thalamic network of adults with OB [19]. Finally, a diffusion MRI study showed reduced (structural) node strength (i.e., sum of the weights of all the edges connected to each node) and normalized the clustering coefficient (i.e., segregation) in subjects with OB (N = 31, 12-39 years old) compared with HW controls, with more pronounced results in the reward network [20]. Altogether, these studies suggest that OB is associated with an imbalance between local segregation and global integration, and disrupted networks, which may lead to less efficient information processing in the brain network. ...
... The second aim of this study was to determine the effect of a specialized multidisciplinary weight reduction OB program on structural brain connectivity and network organization. Based on previous studies in adults with OB [18][19][20], we expected that children with OB would display a reduced clustering coefficient, characteristic path length, and small-worldness compared with HW controls and that these alterations would resolve following treatment. At the regional level, significant differences in brain network organization were expected to be most pronounced in the reward network. ...
... Overall, these findings suggest that the structural connectomes of children with a higher BMI are more segregated into local clusters of connections. Previous neuroimaging studies reported a reduced normalized clustering coefficient in adolescents and adults with OB compared with HW controls [18][19][20], whereby the majority of participants reached the pubertal stage. The different findings between child and adult studies may be due to the effects of brain maturation [38,39]. ...
Previous studies suggest that obesity (OB) is associated with disrupted brain network organization; however, it remains unclear whether these differences already exist during childhood. Moreover, it should be investigated whether deviant network organization may be susceptible to treatment.
Here, we compared the structural connectomes of children with OB with age-matched healthy weight (HW) controls (aged 7–11 years). In addition, we examined the effect of a multidisciplinary treatment program, consisting of diet restriction, cognitive behavioral therapy, and physical activity for children with OB on brain network organization. After stringent quality assessment criteria, 40 (18 OB, 22 HW) data sets of the total sample of 51 participants (25 OB, 26 HW) were included in further analyses. For all participants, anthropometric measurements were administered twice, with a 5-month interval between pre- and post tests. Pre- and post T1- and diffusion-weighted imaging scans were also acquired and analyzed using a graph-theoretical approach and network-based statistics.
Global network analyses revealed a significantly increased normalized clustering coefficient and small-worldness in children with OB compared with HW controls. In addition, regional analyses revealed increased betweenness centrality, reduced clustering coefficient, and increased structural network strength in children with OB, mainly in the motor cortex and reward network. Importantly, children with OB lost a considerable amount of their body mass after the treatment; however, no changes were observed in the organization of their brain networks.
This is the first study showing disrupted structural connectomes of children with OB, especially in the motor and reward network. These results provide new insights into the pathophysiology underlying childhood obesity. The treatment did result in a significant weight loss, which was however not associated with alterations in the brain networks. These findings call for larger samples to examine the impact of short-term and long-term weight loss (treatment) on children’s brain network organization.
... Given its complexity, its activity is closely associated to that of other main networks, such as the salience network, the emotional arousal network and the executive network (Gupta et al., 2015). Brain structural and functional connectivity changes in the reward system, closely resembling those observed in addiction (Michaud et al., 2017), have also been reported in obesity (Marqués-Iturria et al., 2015;Blechert et al., 2016;Carnell et al., 2017;Papageorgiou et al., 2017;Verdejo-Román et al., 2017), affecting several tracts (e.g., the anterior thalamic radiation, accumbofrontal fasciculus, forceps minor (FMi), cingulum, superior longitudinal fasciculus, inferior fronto-occipital fasciculus (Cho et al., 2013;Marqués-Iturria et al., 2015;Kullmann et al., 2016;Nangunoori et al., 2016;Papageorgiou et al., 2017)) of the reward pathway (Sesack and Grace, 2010;Xu et al., 2012;Bracht et al., 2015;Yang et al., 2017). Only few studies, however, have investigated whether structural connectivity might be disrupted in people with genetic risk for obesity (Dennis et al., 2014;Spieker et al., 2015), reporting somewhat conflicting results. ...
... Given its complexity, its activity is closely associated to that of other main networks, such as the salience network, the emotional arousal network and the executive network (Gupta et al., 2015). Brain structural and functional connectivity changes in the reward system, closely resembling those observed in addiction (Michaud et al., 2017), have also been reported in obesity (Marqués-Iturria et al., 2015;Blechert et al., 2016;Carnell et al., 2017;Papageorgiou et al., 2017;Verdejo-Román et al., 2017), affecting several tracts (e.g., the anterior thalamic radiation, accumbofrontal fasciculus, forceps minor (FMi), cingulum, superior longitudinal fasciculus, inferior fronto-occipital fasciculus (Cho et al., 2013;Marqués-Iturria et al., 2015;Kullmann et al., 2016;Nangunoori et al., 2016;Papageorgiou et al., 2017)) of the reward pathway (Sesack and Grace, 2010;Xu et al., 2012;Bracht et al., 2015;Yang et al., 2017). Only few studies, however, have investigated whether structural connectivity might be disrupted in people with genetic risk for obesity (Dennis et al., 2014;Spieker et al., 2015), reporting somewhat conflicting results. ...
... We have investigated whether an association existed between genotype, body mass index (BMI) and diffusivity parameters of WM, reflective of WM microstructural integrity, in the ''risk tracts'' (anterior thalamic radiation and accumbofrontal fasciculi) and the ''obesity-associated tracts'' (FMi, cingulum, superior longitudinal fasciculus, inferior frontooccipital fasciculus). These tracts were selected for their role in reward and punishment sensitivity (Sesack and Grace, 2010;Xu et al., 2012;Bracht et al., 2015;Yang et al., 2017), and for their involvement in obesity (Cho et al., 2013;Marqués-Iturria et al., 2015;Kullmann et al., 2016;Nangunoori et al., 2016;Papageorgiou et al., 2017). Moreover, we explored whether WM diffusivity could be related to specific personality traits in terms of punishment and reward sensitivity, as measured by the BIS/BAS (Carver and White, 1994) questionnaire. ...
Background: Neurovascular coupling is associated with white matter (WM) structural integrity, and it is regulated by specific subtypes of dopaminergic receptors. An altered activity of such receptors, highly expressed in reward-related regions, has been reported in carriers of obesity-risk alleles of the fat mass and obesity associated (FTO) gene. Among the reward-related regions, the thalamus and the nucleus accumbens are particularly vulnerable to blood pressure dysregulation due to their peculiar anatomo-vascular characteristics, and have been consistently reported to be altered in early-stage obesity. We have thus hypothesized that a disruption in thalamus and nucleus accumbens WM microstructure, possibly on neurovascular basis, could potentially be a predisposing factor underlying the enhanced risk for obesity in the risk-allele carriers.
Methods: We have tested WM integrity in 21 male participants genotyped on the FTO risk single nucleotide polymorphisms (SNP) rs9939609, through a deterministic tractography analysis. Only homozygous participants (9 AA, 12 TT) were included. 11 tracts were selected and categorized as following according to our hypothesis: “risk tracts”, “obesity-associated tracts”, and a control tract (forcpes major). We investigated whether an association existed between genotype, body mass index (BMI) and WM microstructural integrity in the “risk-tracts” (anterior thalamic radiation and accumbofrontal fasciculus) compared to other tracts. Moreover, we explored whether WM diffusivity could be related to specific personality traits in terms of punishment and reward sensitivity, as measure by the BIS/BAS questionnaire.
Results: An effect of the genotype and an interaction effect of genotype and BMI were detected on the fractional anisotropy (FA) of the “risk tracts”. Correlations between WM diffusivity parameters and measures of punishment and reward sensitivity were also detected in many WM tracts of both networks.
Conclusions: A disruption of the structural connectivity from the nucleus accumbens and the thalamus might occur early in carriers of the FTO AA risk-allele, and possibly act as a predisposing factor to the development of obesity.
... Adult studies have reported detrimental effects of obesity on the integrity of the brain's white matter tracts and their connections [51][52][53][54][55], and associated deficits in executive function [56]. Pediatric studies have reported reduced cortical thickness (particularly in prefrontal areas) and hippocampal volume in children with obesity or overweight [57,58]. ...
... 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]. ...
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.
... Overall twenty studies [23][24][25][26][27]32,33,46,[49][50][51][52][53][54]56,[59][60][61][62]66,70 indicated significantly reduced FA in subjects with obesity compared to healthy controls. ...
... Six out of twenty-eight studies 54,55,57,58,63,64 did not indicate any significant differences in FA between subjects with obesity and healthy lean controls. ...
... These effects become increasingly prominent at midlife, when higher total body fat and waist circumference translate to increased fractional anisotropy (FA) and lower mean diffusivity (MD) of WM fibers [1][2][3][4]. Overweight adults demonstrate decreased WM connectivity, lower fiber density, and reduced FA in fibers connecting different parts of the taste-reward network [5][6][7]. Several studies point to alterations in brain connectivity in the homeostatic and reward networks of the brain that control the reflexive and behavioral aspects of eating and hence contribute to the pathogenesis of obesity [8]. These alterations, whether they cause or are being caused by obesity, are prominent to the extent that patterns of structural WM connectivity can differentiate the brains of overweight young adults from those with a normal weight with high accuracy [5]. ...
... While sexual dimorphisms in WM connectivity have been examined in prior work [22][23][24], there are comparatively recent investigations linking lifestylerelated risk factors, such as obesity, diabetes, and hypertension, with sex differences [7,25,26]. Biological sex not only alters brain connectivity but also affects energy homeostasis, body fat distribution, and the likelihood of obesity, where women are more likely to be obese but men are more prone to obesity-related chronic diseases [27,28]. Sex can also differentially affect the life-long trajectory of WM development characterized by more advanced development of WM in preadolescent girls and a steeper slope of age-related changes in WM structure in men [28]. ...
Background:
Obesity is an increasingly recognized modifiable risk factor for Alzheimer's disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity.
Objective:
We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity.
Methods:
A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm.
Results:
We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status.
Conclusion:
BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD.
... The orbitofrontal region plays a role in reward processing whilst the dorsolateral and ventrolateral regions play a role in regulating behaviour. Lastly, the medial portion of the prefrontal cortex plays a role in motivation and decision making Marqués-Iturria et al., 2015). The abnormal functioning of these circuits may contribute in the emergence and maintenance of HRBs. ...
... These are risk factors for cerebrovascular disease, impeding glucose and oxygen supply in the brain that further damages the structure and function of the neurons (Kemeny, 2003). The role of reward processing is affected in obesity Marqués-Iturria et al., 2015) and stress (Porcelli et al., 2012) and is mediated by the orbitofrontal regions, also called as secondary gustatory cortex. ...
Health risk behaviours (HRB) across the lifespan have been associated with higher cumulative physiological burden as measured by allostatic load (AL). This study examines the contribution of HRB and their effects on multisystem biological risk associated with morbidity and early mortality. We systematically reviewed the literature to assess the links between HRB and AL. Twenty-six eligible human studies were included in our assessment of the current literature investigating the association of different HRB that included overeating/obesity, alcohol, smoking, drug use, physical inactivity and sleep impairments in relation to AL. We found that 50% of obesity and substance abuse, 75% of sleep and 62.5% of combined HRB studies showed a significant association with AL. Lifestyle coping behaviours therefore have a significant contribution to AL. This study is among the first to explore multiple domains of HRB in relation to AL. Further research should focus on evaluating lifestyle factors that adapt HRB as a strategy to cope with chronic stress to help decrease AL and resulting long-term negative health consequences.
... The pars opercularis is a key region for the integration of sensoryhedonic properties of food (e.g., taste, texture, palatability) given its involvement along with the anterior portions of the insula in the primary gustatory cortex (Kumar et al., 2016). Orbitofrontal regions are known as a second gustatory cortex and for their role in reward-processing, a function affected in overweight (García-García et al., 2013aMarqués-Iturria et al., 2015) and stress (Porcelli et al., 2012). Dorsolateral (i.e., middle and superior frontal gyrus) and ventrolateral portions (i.e., inferior frontal gyrus) of the prefrontal cortex are involved in regulating behaviour through executive functions such as inhibitory control. ...
... Structural modifications in this region have been consistently reported in several mental disorders (Anticevic et al., 2012) and stress (Leritz et al., 2011), but not in obesity (García-García et al., 2013b). However, the precuneus overlaps with reward-salience processing regions, a network which is affected in obesity (García-García et al., 2013a,b;Horstmann et al., 2015;Marqués-Iturria et al., 2015). In the study of Chiappelli et al. (2017), the increase of AL was related to decreases in the cortical thickness of parietal regions as the paracentral and postcentral gyrus, the inferior and superior parietal cortex, and the precuneus, similar to the results that we observed with overweight participants. ...
Overweight and stress interact in complex ways. Excess weight promotes chronic low-grade inflammatory states that can mobilise the hypothalamic-pituitary-adrenal (HPA) axis. HPA axis activation resulting from frequent stress situations can modify energy uptake and expenditure. Separately, both conditions have been linked to changes in brain integrity and executive performance. The organism adapts to situations of caloric surplus through boosting immune, neuroendocrine and cardiometabolic systems to restore energy homeostasis. The allostatic load model establishes that the cumulative effects of adapting to challenging scenarios may result in adverse health situations in the future. There is sufficient evidence to consider that a state of overweight is inherently linked to a higher chronic physiological stress, or allostatic load. Our hypothesis was that, independently of the effects of visceral adiposity, the aggregated effects of the biological alterations related to overweight would be enough detrimental to brain structure and executive functioning. Lean-to-obese volunteers aged 21 to 40 years were recruited from primary health care centres belonging to the Consorci Sanitari de Terrassa. Subjects underwent a medical and neuropsychological examination, as well as a magnetic resonance imaging acquisition at the Hospital Clínic de Barcelona. The allostatic load index consisted of the sum of several biomarkers representing physiological stress. Overweight subjects had a greater allostatic load than healthy weight participants. The allostatic load escalation was negatively correlated with the morphology of cortical areas and tracts known to be ascribed to circuits involved in cognitive control, reward-processing and the integration of visceral-sensory signalling. Finally, the intensification in this index correlated with worse cognitive flexibility.
... Several studies demonstrate direct associations between individual differences in behaviour and white matter connectivity (for an overview see 23 ), thereby complementing functional measures as provided by functional MRI. In the context of ingestive behaviour, studies on white matter tractography have reported both decreased and increased integrity of white matter tracts in obese compared to normal weight individuals 24,25 , with some data indicating reduced connectivity in reward networks 25,26 , while others report increased white matter integrity of accumbal circuits 24 in participants with higher BMI scores. One reason for this apparent controversy, besides genetic variability 27,28 , might be the uncontrolled impact of individual eating behaviour on brain structure. ...
... The few existing DTI tractography studies in the field of ingestive behaviour have produced mixed findings regarding the wiring within reward networks. While one study reported greater connectivity from regions of the reward network to cortical areas in an overweight compared to a normal weight group 24 , others found lower numbers of streamlines between the NAc and the rest of the reward network in obese individuals 26 . Inconsistent findings have previously also been reported for other DTI measures such as fractional anisotropy (FA), and been discussed as a potential consequence of competing metabolic processes affecting white matter integrity in overweight and obesity such as insulin resistance, inflammation and dyslipidaemia (for an overview see 45 . ...
Dopaminergic brain structures like the nucleus accumbens (NAc) are thought to encode the incentive salience of palatable foods motivating appetitive behaviour. Animal studies have identified neural networks mediating the regulation of hedonic feeding that comprise connections of the NAc with the ventral tegmental area (VTA) and the lateral hypothalamus (LH). Here, we investigated how structural connectivity of these pathways relates to individual variability in decisions on sweet food consumption in humans. We therefore combined probabilistic tractography on diffusion imaging data from 45 overnight fasted lean to overweight participants with real decisions about high and low sugar food consumption. Across all individuals, sugar preference and connectivity strength were not directly related, however, multiple regression analysis revealed interaction of mesolimbic structure and sugar preference to depend on individuals’ BMI score. In overweight individuals (BMI: ≥25 kg/m², N = 22) higher sugar preference was thereby specifically related to stronger connectivity within the VTA-NAc pathway while the opposite pattern emerged in participants with normal BMI (BMI: <25 kg/m², N = 23). Our structural results complement previous functional findings on the critical role of the human mesolimbic system for regulating hedonic eating in overweight individuals.
... [19][20][21] Marqués-Iturria et al used DTI to reconstruct and compare obese (n=31) and non-obese (n=32) subjects' brain reward networks based on white matter volume and microstructure, the authors reported that obese subjects displayed a lower number of fibers and decreased integrity of connections in addition to reduced network clustering strength among the orbitofrontal cortex and striatum nuclei including the accumbens, caudate, and putamen when compared with non-obese subjects. 22 In a separate study, Kullmann et al used DTI and multiparametric mapping to examine the effect of increasing BMI among lean, overweight, and obese subjects on brain white matter. 23 Results indicated that white matter structures showed reduced myelin and increased water with increasing BMI in the corticospinal tract and fiber tracts linking limbic structures with prefrontal regions. ...
... 15 In addition, lower number of fibers and integrity of connections in the reward system are correlated with obesity. 22 Similarly, neural networks that are highly interconnected and modulate the body shape processing (eg, frontal-temporal regions) have been found to be underactive in people with an eating disorder. 43,44 Taken together, brain circuits and networks that modulate reward sensitivity, self-perception, and feeding behavior may be altered in obese individuals. ...
Purpose:
Obesity is a complex and multifactorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with the brain's propensity toward disturbances in mood and cognition. Herein, we characterize alterations in brain structures and networks among obese subjects (ie, body mass index [BMI] ≥30 kg/m2) when compared with non-obese controls.
Patients and methods:
We obtained noninvasive diffusion tensor imaging and generalized q-sampling imaging scans of 20 obese subjects (BMI=37.9±5.2 SD) and 30 non-obese controls (BMI=22.6±3.4 SD). Graph theoretical analysis and network-based statistical analysis were performed to assess structural and functional differences between groups. We additionally assessed for correlations between diffusion indices, BMI, and anxiety and depressive symptom severity (ie, Hospital Anxiety and Depression Scale total score).
Results:
The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (Elocal), global efficiency (Eglobal), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal-temporal regions in obese subjects compared with non-obese controls.
Conclusion:
We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese.
... Alterations in reward-seeking have been described in overweight 25 and stress 42 studies. A study from our group has also described an abnormal configuration of the reward-processing network 43 . In this study, obese participants also showed a disturbed composition (i.e., low FA) in tracts ascribed to such network (i.e., striatum, accumbens, and orbitofrontal cortex). ...
... Thirty-one overweight and 21 lean controls formed the final sample. Fifty participants (29 overweight-to-obese and 21 healthy weight controls) of this final sample were included from previous studies 15,43,59,[73][74][75][76][77][78] . The study has been conducted following the Helsinki Declaration and has been approved by the University of Barcelona's Institutional Ethics Committee (CBUB) and the Institutional Review Board (IRB 00003099, assurance No.: FWA00004225; http://www.ub.edu/recerca/comissiobioetica.htm). ...
Overweight and stress are both related to brain structural abnormalities. The allostatic load model states that frequent disruption of homeostasis is inherently linked to oxidative stress and inflammatory responses that in turn can damage the brain. However, the effects of the allostatic load on the central nervous system remain largely unknown. The current study aimed to assess the relationship between the allostatic load and the composition of whole-brain white matter tracts in overweight subjects. Additionally, we have also tested for grey matter changes regarding allostatic load increase. Thirty-one overweight-to-obese adults and 21 lean controls participated in the study. Our results showed that overweight participants presented higher allostatic load indexes. Such increases correlated with lower fractional anisotropy in the inferior fronto-occipital fasciculi and the right anterior corona radiata, as well as with grey matter reductions in the left precentral gyrus, the left lateral occipital gyrus, and the right pars opercularis. These results suggest that an otherwise healthy overweight status is linked to long-term biological changes potentially harmful to the brain.
... The pars opercularis is a key region for the integration of sensoryhedonic properties of food (e.g., taste, texture, palatability) given its involvement along with the anterior portions of the insula in the primary gustatory cortex (Kumar et al., 2016). Orbitofrontal regions are known as a second gustatory cortex and for their role in reward-processing, a function affected in overweight (García-García et al., 2013aMarqués-Iturria et al., 2015) and stress (Porcelli et al., 2012). Dorsolateral (i.e., middle and superior frontal gyrus) and ventrolateral portions (i.e., inferior frontal gyrus) of the prefrontal cortex are involved in regulating behavior through executive functions such as inhibitory control. ...
... Structural modifications in this region have been consistently reported in several mental disorders (Anticevic et al., 2012) and stress (Leritz et al., 2011), but not in obesity (García-García et al., 2013b). However, the precuneus overlaps with reward-salience processing regions, a network which is affected in obesity (García-García et al., 2013a,b;Horstmann et al., 2015;Marqués-Iturria et al., 2015). In the study of Chiappelli et al. (2017), the increase of AL was related to decreases in the cortical thickness of parietal regions as the paracentral and postcentral gyrus, the inferior and superior parietal cortex, and the precuneus, similar to the results that we observed with overweight participants. ...
Objective: Overweight (body mass index or BMI ≥ 25 kg/m2) and stress interact with each other in complex ways. Overweight promotes chronic low-inflammation states, while stress is known to mediate caloric intake. Both conditions are linked to several avoidable health problems and to cognitive decline, brain atrophy, and dementia. Since it was proposed as a framework for the onset of mental illness, the allostatic load model has received increasing attention. Although changes in health and cognition related to overweight and stress are well-documented separately, the association between allostatic load and brain integrity has not been addressed in depth, especially among overweight subjects.
Method: Thirty-four healthy overweight-to-obese and 29 lean adults underwent blood testing, neuropsychological examination, and magnetic resonance imaging to assess the relationship between cortical thickness and allostatic load, represented as an index of 15 biomarkers (this is, systolic and diastolic arterial tension, glycated hemoglobin, glucose, creatinine, total cholesterol, HDL and LDL cholesterol, triglycerides, c-reactive protein, interleukin-6, insulin, cortisol, fibrinogen, and leptin).
Results: Allostatic load indexes showed widespread positive and negative significant correlations (p < 0.01) with cortical thickness values depending on body-weight status.
Conclusion: The increase of allostatic load is linked to changes in the gray matter composition of regions monitoring behavior, sensory-reward processing, and general cognitive function.
... Balodis et al. (2013) found increased activity in the ventral striatum and ventromedial prefrontal cortex in anticipation of monetary reward. This is consistent with evidence of altered structural connectivity in fronto-striatal circuits in obese individuals, and implies a general reward-processing deficit (Marqués Iturria et al. 2015). However, other studies have failed to find an association between brain monetary processing and body mass index (BMI) (Simon et al. 2015). ...
... These results are consistent with a previous study that found reduced frontal cortex related functional connectivity in obese individuals during passive viewing of high palatable food images (García-García et al. 2013). Two recent studies have also reported altered white matter microstructure in fiber pathways linking frontal and subcortical areas in excess weight adults (Kullmann et al. 2015; Marqués-Iturria et al. 2015). Frontal areas play a crucial role in dietary choices. ...
Overvaluation of palatable food is a primary driver of obesity, and is associated with brain regions of the reward system. However, it remains unclear if this network is specialized in food reward, or generally involved in reward processing. We used functional magnetic resonance imaging (fMRI) to characterize functional connectivity during processing of food and monetary rewards. Thirty-nine adults with excess weight and 37 adults with normal weight performed the Willingness to Pay for Food task and the Monetary Incentive Delay task in the fMRI scanner. A data-driven graph approach was applied to compare whole-brain, task-related functional connectivity between groups. Excess weight was associated with decreased functional connectivity during the processing of food rewards in a network involving primarily frontal and striatal areas, and increased functional connectivity during the processing of monetary rewards in a network involving principally frontal and parietal areas. These two networks were topologically and anatomically distinct, and were independently associated with BMI. The processing of food and monetary rewards involve segregated neural networks, and both are altered in individuals with excess weight.
... Decreased fiber density between the ventromedial PFC and the anterior insula as well as between the thalamus and regions of the executive control network was also reported (Gupta et al., 2015). The second study assessed white matter connectivity in a limited reward network and found fewer reconstructed white matter fibers between reward network regions including the orbitofrontal cortex (OFC), caudate, putamen and accumbens as well as lower fiber integrity within the same tracts in obese individuals (Marqués-Iturria et al., 2015). Given the limited nature of tractography analyses in obesity, further investigation is warranted and has the potential to clarify the role anatomical white matter connectivity patterns may play in the disease. ...
... This study builds on previous analysis on white matter connectivity in taste-reward circuitry. Marqués-Iturria et al's (2015) publication is, to our knowledge, the only previous study to examine reward network connectivity in obese individuals. Their analysis reported obesity being associated with lower connectivity of the bilateral caudate and nucleus accumbens to reward network regions (i.e., lateral OFC, medial OFC, caudate, putamen and accumbens). ...
Despite the prevalence of obesity, our understanding of its neurobiological underpinnings is insufficient. Diffusion weighted imaging and calculation of white matter connection strength are methods to describe the architecture of anatomical white matter tracts. This study aimed to characterize white matter architecture within taste-reward circuitry in a population of obese individuals. Obese (n=18, age = 28.7 ± 8.3 years) and healthy control (n=24, age = 27.4 ± 6.3 years) women underwent diffusion weighted imaging. Using probabilistic fiber tractography (FSL PROBTRACKX2 toolbox) we calculated connection strength within 138 anatomical white matter tracts. Obese women displayed lower and greater connectivity within taste-reward circuitry compared to controls (Wilks’ λ < 0.001; p < 0.001). Connectivity was lower in white matter tracts connecting insula, amygdala, prefrontal cortex, orbitofrontal cortex and striatum. Connectivity was greater between the amygdala and anterior cingulate cortex. This study indicates that lower white matter connectivity within white matter tracts of insula-fronto-striatal taste-reward circuitry are associated with obesity as well as greater connectivity within white matter tracts connecting the amygdala and anterior cingulate cortex. The specificity of regions suggests sensory integration and reward processing are key associations that are altered in and might contribute to obesity.
... While changes in microstructure are observed in the ventral striatum of obese adults [45,46], it is unclear when this association emerges over the life course. We hypothesized that this association might emerge over fetal development, providing the basis for a coordinated brain-body predisposition to early adiposity. ...
Neonatal adiposity is associated with a higher risk of obesity and cardiometabolic risk factors in later life. It is however unknown if central food intake regulating networks in the ventral striatum are altered with in-utero abdominal growth, indexed by neonatal adiposity in our current study. We aim to examine the relationship between striatal microstructure and abdominal adipose tissue compartments (AATCs) in Asian neonates from the Growing Up in Singapore Toward healthy Outcomes mother-offspring cohort.
About 109 neonates were included in this study. Magnetic resonance imaging (MRI) was performed for the brain and abdominal regions between 5 to 17 days of life. Diffusion-weighted imaging of the brain was performed for the derivation of caudate and putamen fractional anisotropy (FA). Abdominal imaging was performed to quantify AATCs namely superficial subcutaneous adipose tissue (sSAT), deep subcutaneous adipose tissue (dSAT), and internal adipose tissue (IAT). Absolute and percentage adipose tissue of total abdominal volume (TAV) were calculated.
We showed that AATCs at birth were significantly associated with increased FA in bilateral ventral caudate heads which are part of the ventral striatum (sSAT: βleft = 0.56, p < 0.001; βright = 0.65, p < 0.001, dSAT: βleft = 0.43, p < 0.001; βright = 0.52, p < 0.001, IAT: βleft = 0.30, p = 0.005; βright = 0.32, p = 0.002) in neonates with low birth weights adjusted for gestational age.
Our study provides preliminary evidence of a potential relationship between neonatal adiposity and in-utero programming of the ventral striatum, a brain structure that governs feeding behavior.
... Data suggest that binge eating behavior is related to alterations in neural circuitry associated with inhibitory control (Bartholdy, Dalton, O'Daly, Campbell, & Schmidt, 2016;Reiter, Heinze, Schlagenhauf, & Deserno, 2017). Similar alterations that have been reported in obesity (Gearhardt et al., 2011;Marques-Iturria et al., 2015). Altered activity in networks associated with inhibitory control and with reward have been associated with maladaptive food-related decision-making in obesity (Devoto et al., 2018). ...
Objective
Research on potential brain circuit abnormalities in binge eating disorder (BED) is limited. Here, we assess white matter (WM) microstructure in obese women with BED.
Method
Diffusion tensor imaging data were acquired, and tract‐based spatial statistics used to examine WM in women with BED who were obese (n = 17) compared to normal‐weight (NWC) (n = 17) and to women who were obese (OBC) (n = 13). Body mass index (BMI) was a covariate in the analyses.
Results
The BED group (vs. NWC) had greater axial diffusion (AD) in the forceps minor, anterior thalamic radiation, superior and inferior longitudinal fasciculus, that is, in pathways connecting fronto‐limbic regions. Microstructures differences in AD between the BED and OBC groups were seen in fronto‐limbic pathways extending to temporoparietal pathways. The BED (vs. OBC) group had greater fractional anisotropy in the forceps minor and greater AD in the superior longitudinal fasciculus, cingulate gyrus, and corpus callosum, consistent with fronto‐tempoparietal pathways.
Conclusion
Women with BED show WM alterations in AD in fronto‐limbic and parietal pathways that are important in decision‐making processes. As BMI was a covariate in the analyses, alterations in BED may be part of the pathology, but whether they are a cause or effect of illness is unclear.
... These cognitive alterations often correspond to obesity-related variability in cortico-basal ganglia pathways that support decisionmaking and reward processing. For example, obesity is associated with reduced D2-receptor binding (Volkow et al., 2008b;de Weijer et al., 2011), altered reactivity to food cues in ventral and dorsal striatal regions (Stice et al., 2008(Stice et al., , 2010Burger and Stice, 2012), modified corticostriatal connectivity (García-García et al., 2012;Marqués-Iturria et al., 2015), and individual differences in genetic markers of dopamine availability (Noble et al., 1994;Nisoli et al., 2007;Stice et al., 2008). These observations have led to the hypothesis that risk for obesity may be engendered by a cluster of neurobiological phenotypes associated with addiction, mediated by hypersensitive mesolimbic dopaminergic pathway (Volkow et al., 2008a(Volkow et al., , 2012Tomasi and Volkow, 2013). ...
Unhealthy weight gain relates, in part, to how people make decisions based on prior experience. Here we conducted post hoc analysis on an archival data set to evaluate whether individual differences in adiposity, an anthropometric construct encompassing a spectrum of body types, from lean to obese, associate with signatures of asymmetric feedback learning during value-based decision-making. In a sample of neurologically healthy adults (N = 433), ventral striatal responses to rewards, measured using fMRI, were not directly associated with adiposity, but rather moderated its relationship with feedback-driven learning in the Iowa Gambling Task tested outside the scanner. Using a biologically-inspired model of basal ganglia-dependent decision processes, we found this moderating effect of reward reactivity to be explained by an asymmetrical use of feedback to drive learning; that is, with more plasticity for gains than for losses, stronger reward reactivity leads to decisions that minimize exploration for maximizing long-term outcomes. Follow-up analysis confirmed that individual differences in adiposity correlated with signatures of asymmetric use of feedback cues during learning, suggesting that reward reactivity may especially relate to adiposity, and possibly obesity risk, when gains impact future decisions more than losses.
... Brain reward circuitry plays a critical role in regulating food and drug reward, and alteration in this circuitry could contribute to pathological food and drug intake [49]. Importantly, disorganization in brain reward circuitry has been documented in obesity which may impair decision making and trigger food/drug-reinforced behavior [50][51][52][53][54][55]. In this context, bariatric surgeries (e.g., RYGB and VSG) have been shown to normalize obesity-induced alterations in the brain reward regions and overall brain functional connectivity, possibly contributing to beneficial or detrimental effects post-surgery [56][57][58][59][60][61][62][63][64][65]. ...
Purpose of Review
There is compelling evidence in the clinical population that long-term weight loss secondary to bariatric surgery is mitigated by the reemergence of maladaptive feeding behaviors and in some cases new onset substance abuse.
Recent Findings
A review of the current literature suggests that physical restructuring of the GI tract during WLS alters secretion of feeding peptides and nutrient-sensing mechanisms that directly target the brain’s endogenous reward system, the mesolimbic dopamine system.
Summary
Post-surgical changes in GI physiology augment activation of the mesolimbic system. In some patients, this process may contribute to a reduced appetite for palatable food whereas in others it may support maladaptive motivated behavior for food and chemical drugs. It is concluded that future studies are required to detail the timing and duration of surgical-induced changes in GI-mesolimbic communication to more fully understand this phenomenon.
... hunger) and initiating impulsive behaviors [36,37]. Thus, an attentional bias to food stimuli, coupled with impulsive traits, increases the likelihood of acting upon food cravings, irrespective of internal states of hunger or satiety [38,39]. This biased neural response towards high-calorie vs. low-calorie foods has been further explored in adolescents with obesity and has been linked to heightened activity in brain regions such as the striatum, insula, anterior cingulate cortex (ACC) and amygdala [33,38]. ...
Impulsivity and compulsivity are multidimensional constructs that are increasingly considered determinants of obesity. Studies using functional magnetic resonance imaging (fMRI) have provided insight on how differences in brain response during tasks exploring facets of impulsivity and compulsivity relate to the ingestive behaviors that support the etiology and maintenance of obesity. In this narrative review, we provide an overview of neuroimaging studies exploring impulsivity and compulsivity factors as they relate to weight status. Special focus will be placed on studies examining the impulsivity-related dimensions of attentional bias, delayed gratification and emotion regulation. Discussions of compulsivity within the context of obesity will be restricted to fMRI studies investigating habit formation and response flexibility under shifting contingencies. Further, we will highlight neuroimaging research demonstrating how alterations in neuroendocrine functioning are linked to excessive food intake and may serve as a driver of the impulsive and compulsive behaviors observed in obesity. Research on the associations between brain response with neuroendocrine factors, such as insulin, peptide YY (PYY), leptin, ghrelin and glucagon-like peptide 1 (GLP-1), will be reviewed.
... Specifically, in females with high BMI, we found a loss of prefrontal-orbitofrontal connectivity, coupled with abnormal orbitofrontal interconnections with nucleus accumbens (Figure 3). This finding further contributes to previous evidence in obesity [24], suggesting that a long-lasting enhanced responsiveness and motivation for food stimuli may lead to a dysregulation of the prefrontal and orbitofrontal inhibitory control towards subcortical reward structures, in particular the nucleus accumbens [15]. All these interconnected regions are involved in the regulation of food intake, through the integration of both internal signals (i.e. ...
There are reported gender differences in brain connectivity associated with obesity. In the elderlies, the neural endophenotypes of obesity are yet to be elucidated. We aim at exploring the brain metabolic and connectivity correlates to different BMI levels in elderly individuals, taking into account gender as variable of interest.
We evaluated the association between BMI, brain metabolism and connectivity, in elderly females and males, by retrospectively collecting a large cohort of healthy elderly subjects (N=222; age=74.03±5.88 [61.2-85.9] years; M/F=115/107; BMI=27.00±4.02 [19.21-38.79] kg/m²). Subjects underwent positron emission tomography with [18F]FDG. We found that, in females, high BMI was associated with increased brain metabolism in the orbitofrontal cortex (R=0.44; p<0.001). A significant BMI-by-gender interaction was present (F=7.024, p=0.009). We also revealed an altered connectivity seeding from these orbitofrontal regions, namely expressing as a decreased connectivity in crucial control/decision making circuits, and as an abnormally elevated connectivity in reward circuits, only in females. Our findings support a link between high BMI and altered brain metabolism and neural connectivity, only in elderly females. These findings indicate a strong gender effect of high BMI and obesity that brings to considerations for medical practice and health policy.
... doi: bioRxiv preprint first posted online Jun. 28,2019 . CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. ...
Life expectancy and obesity rates have drastically increased in recent years. An unhealthy weight is related to long-lasting biological deregulations that might compromise the normal course of development and jeopardize the so-called “successful aging”. The aim of the current study was to test whether an obesity status could mimic the functional organization of an otherwise healthy aged brain. Thus, the current study included adults with (N = 32, mean age 34.5 ± 6.49) and without obesity (N = 34, mean age 32.7 ± 6.79) as well as adolescents with obesity (N = 30, mean age 15.3 ± 2.64) and normal-weight (N = 31, mean age 15.6 ± 2.60). A sample of stroke-free non-obese and non-demented seniors was also entered (N = 32, mean age 66.1 ± 7.43). Participants underwent resting-state MRI acquisition and graph-based measurements of segregation, integration and robustness (i.e., mean degree and strength) were calculated. Obesity in adults was followed by a broad pattern of loses in robustness when compared to healthy-weight adults and seniors, as well as increases in network segregation relative to elders. Differences in adolescents followed the same direction yet they did not survive multiple comparison adjustment. No interaction emerged when exploring the transition from childhood to adulthood accounting for body-weight status. Altogether, and yet more research is needed, an obesity status could negatively render network resilience and compromise the normal course of aging.
... *P < 0.05, **P < 0.005, ***P < 0.0001 MH networks. Brain regions within the LH network, the putamen is a part of striatum which is a main input structure of the basal ganglia and receives afferent projections from the orbitofrontal cortex [35,36]. In function, the putamen is an important reward region whose dysfunction has been reported in subjects with obesity [37,38]. ...
Background
Lateral and medial hypothalamus (LH and MH) play important roles in energy balance. Changed hypothalamic function has been found in subjects with obesity. However, the effect of bariatric surgery on the function of the two sub-regions has been poorly investigated.
Methods
Thirty-eight subjects with obesity and 34 age- and sex-matched normal-weight controls were included. Seventeen of the 38 subjects underwent laparoscopic sleeve gastrectomy. Functional magnetic resonance imaging data and metabolic parameters were collected to investigate functional connectivity networks of the two hypothalamic sub-regions as well as the influence of sleeve gastrectomy on the two networks in subjects with obesity.
Results
Compared to normal-weight controls, pre-surgical subjects had increased functional connectivity (FC) in the reward region (putamen) within the LH network, and increased FC in somatosensory cortical area (insula), as well as decreased FC in the cognitive control regions (prefrontal regions) within the MH network. After the surgery, post-surgical FC of the putamen within the LH network changed towards the patterns found in the control group. Furthermore, the changes in fasting glucose before and after the surgery were associated with the changes in FC of the putamen within the LH network.
Conclusions
The FC within the LH and MH networks were changed in subjects with obesity. Part of these altered FC was rescued after the surgery.
... Using neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), a well-established literature has shown altered brain reward value responses and dopaminergic activities in obesity (Stice et al., 2008;Volkow et al., 2011;Frank et al., 2012;Babbs et al., 2013;Eisenstein et al., 2013;Guo et al., 2014). These alterations may further be coupled with structural and connectivity changes in the valuation system (Marques-Iturria et al., 2015;Shott et al., 2015). However, rather than an ultimate mechanistic answer to why obese individuals sometimes make suboptimal decisions, these findings should be more appropriately viewed as a step forward, which raises deeper and more challenging questions: If value for certain food items goes awry in obese individuals, why are they not able to get it right in the first place? ...
Obesity is associated with a diverse array of cognitive and affective deficits, among which impairments in food valuation and choices have received increasing attention. The neural underpinnings of such impairments, however, remain poorly understood, partly because a complete understanding of these processes under normal conditions has yet to be achieved. A rapidly growing literature on the interaction between memory and decision-making has begun to highlight the integral role of memory in decision making especially in the real world, as well as the role of the hippocampus in supporting flexible decision making. Perhaps not coincidentally, altered memory performances in obesity have been well documented, and the underlying neurobiological bases of these memory alterations have also started to be better described, involving pathologies at the biochemical, cellular, and circuit levels. Despite such correspondence, the link between memory impairments and food valuation/choice deficits in obesity has received little attention. In this article, we first summarize the growing empirical support for the relevance of memory for decision making, focusing on flexible value-based decisions. We then describe converging evidence on different forms of memory impairments accompanying obesity. Building on these findings, we formulate a general neuropsychological framework and discuss how dysfunctions in the formation and retrieval of memory may interfere with adaptive decision making for food. Finally, we stress the important practical implications of this framework, arguing that memory deficits are likely a significant contributor to suboptimal food purchase and eating behavior exhibited by obese individuals.
... Interestingly, the brain areas and networks that show functional responses to consumption of water and glucose in our study have also been implied to function differently in obesity 8,14,32,33,[37][38][39][40][41] and type 2 diabetes. 28,[42][43][44] This suggests that maintaining the functional responses found in our study could be important for maintaining energy and glucose homeostasis. ...
Objectives: The regulatory role of the brain in directing eating behavior becomes increasingly recognized. Although many areas in the brain have been found to respond to food cues, very little data is available after actual caloric intake. The aim of this study was to determine normal whole brain functional responses to ingestion of glucose after an overnight fast.
Methods: Twenty-five normal weight, adult males underwent functional MRI on two separate visits. In a single-blind randomized study setup, participants received either glucose solution (50 g/300 ml of water) or plain water. We studied changes in Blood Oxygen Level Dependent (BOLD) signal, voxel-based connectivity by Eigenvector Centrality Mapping, and functional network connectivity.
Results: Ingestion of glucose led to increased centrality in the thalamus and to decreases in BOLD signal in various brain areas. Decreases in connectivity in the sensory-motor and dorsal visual stream networks were found. Ingestion of water resulted in increased centrality across the brain, and increases in connectivity in the medial and lateral visual cortex network. Increased BOLD intensity was found in the intracalcarine and cingulate cortex.
Discussion: Our data show that ingestion of glucose leads to decreased activity and connectivity in brain areas and networks linked to energy seeking and satiation. In contrast, drinking plain water leads to increased connectivity probably associated with continued food seeking and unfulfilled reward.
Trail registration: This study combines data of two studies registered at clinicaltrails.gov under numbers NCT03202342 and NCT03247114.
... Especially, the consumption of high-sugar foods, just as in substance addiction, promotes higher consumption of these foods by affecting the reward system of the brain [18]. A study found that it is easier to reduce the amount of fat in biscuits than to reduce the amount of sugar, and it is more difficult for a consumer to notice the difference [19]. In another study with breakfast biscuits, liking of the biscuit with 33% reduced fat increased significantly in 4 weeks, while biscuits with 9% and 16% reduced sugar were liked more than the biscuit with 28% reduced sugar [20]. ...
PurposeThis study aimed to investigate the nutritional values of some low-nutrition packaged foods widely sold in supermarkets and encouraged for consumption. Methods
The study used 435 packaged foods from six hypermarkets with high sale capacities in Ankara to analyze their contents of energy/total fat/saturated fat/carbohydrate/sugar/salt based on label information. ResultsAmong the products in the scope of the study, the highest values were found in chocolates for fat (33.0 ± 4.28/100 g) and sugar (45.6 ± 5.95/100 g), wafers for saturated fat (19.2 ± 3.89/100 g), and crackers for sodium (0.9 ± 0.23/100 g). Among the 435 packaged foods investigated in the study, the products exceeded the limits designated in the health codes declared by the Turkish Food Codex Labeling Directive in 83.4% of the instances in terms of sugar, 93.7% of the instances in terms of total fat, 92.4% of the instances in terms of saturated fat, and 70.3% of the instances in terms of sodium. Conclusion
Energy/fat/sugar/salt contents were high in the packaged products that are especially targeted for children for higher consumption. Children’s frequent and excessive consumption of these products contribute to the prevalence of childhood obesity and increase in related health risks. Level of EvidenceLevel V, descriptive study.
... The literature search is summarized in Fig. 1. Eleven studies (Gupta et al., 2015;Mueller et al., 2015;Kullmann et al., 2016;Lou et al., 2014;Maayan et al., 2011;Marqués-Iturria et al., 2015;Mueller et al., 2011Mueller et al., , 2012Shott et al., 2015;Xu et al., 2013;Weise et al., 2013) met our inclusion criteria and were included in the present systematic review (more details are given in Supplementary material, Results). ...
... Consequently, although the sample varies in BMI status, rates of extreme obesity are relatively low. While BMI and BMI percentile are commonly used to reflect adiposity (e.g., Raji et al., 2010;Moreno-Lopez et al., 2012;Yokum et al., 2012;Alosco et al., 2013;Karlsson et al., 2013;Bobb et al., 2014;Marques-Iturria et al., 2015;Ou et al., 2015), they are poor in distinguishing whether variance in weight is due to excess fat or to excess muscle [although both measures correlate very highly using measurement techniques that reliably differentiate between the two (r = 0.85 in children and adolescents); Steinberger et al., 2005]. There is some evidence that increased non-adipose tissue accounts for BMI-related differences in brain structure (Weise et al., 2013). ...
Adolescent obesity is associated with an increased chance of developing serious health risks later in life. Identifying the neurobiological and personality factors related to increases in adiposity is important to understanding what drives maladaptive consummatory and exercise behaviors that result in obesity. Previous research has largely focused on adults with few findings published on interactions among adiposity, brain structure, and personality. In this study, Voxel Based Morphometry (VBM) was used to identify associations between gray and white matter volumes and increasing adiposity, as measured by Body Mass Index percentile (BMI%), in 137 adolescents (age range: 9–20 years, BMI% range: 5.16–99.56). Variations in gray and white matter volume and BMI% were then linked to individual differences in personality measures from the Multidimensional Personality Questionnaire (MPQ). After controlling for age and other covariates, BMI% correlated negatively with gray matter volume in the bilateral caudate (right: partial r = −0.338, left: r = −0.404), medial prefrontal cortex (partial r = −0.339), anterior cingulate (partial r = −0.312), bilateral frontal pole (right: partial r = −0.368, left: r = −0.316), and uncus (partial r = −0.475) as well as white matter volume bilaterally in the anterior limb of the internal capsule (right: partial r = −0.34, left: r = −0.386), extending to the left middle frontal subgyral white matter. Agentic Positive Emotionality (PEM-AG) was correlated negatively with BMI% (partial r = −0.384). PEM-AG was correlated positively with gray matter volume in the right uncus (partial r = 0.329). These results suggest that higher levels of adiposity in adolescents are associated with lower trait levels in reward-related personality domains, as well as structural variations in brain regions associated with reward processing, control, and sensory integration.
... Although network-based white matter analyses-i.e., from either anatomically-guided or fMRI-guided "connectome reconstructions" of white matter regions belonging to each network (as reported in the current study)-have enormous potential for investigating quantitative white matter differences, only one other study has very recently been published using similar methods to investigate white matter correlates of body composition (Marqués-Iturria et al., 2015). In their study, the authors investigated an ostensive white matter reward system (comprised of the anatomical connections between bilateral lateral orbitofrontal, medial orbitofrontal, caudate, putamen and nucleus accumbens regions), finding both reduced numbers of DTI tractography streamlines and lower FA values in obese subjects compared to healthy-weight controls. ...
It is well established that obesity decreases overall life expectancy and increases the risk of several adverse health conditions. Mounting evidence indicates that body fat is likely also associated with structural and functional brain changes, reduced cognitive function, and greater impulsivity. However, previously reported differences in brain structure and function have been variable across studies and difficult to reconcile due to sample population and methodological differences. To clarify these issues, we correlated two independent measures of body composition – i.e., body mass index (BMI) and body fat percent (BFP) – with structural and functional neuroimaging data obtained from a cohort of 32 neurologically healthy adults. Whole-brain voxel-wise analyses indicated that higher BMI and BFP were associated with widespread decreases in gray matter volume, white matter volume, and white matter microstructure (including several regions, such as the striatum and orbitofrontal cortex, which may influence value assessment, habit formation, and decision-making). Moreover, closer examination of resting state functional connectivity, white matter volume, and white matter microstructure throughout the default mode network (DMN), executive control network (ECN), and salience network (SN) revealed that higher BMI and BFP were associated with increased SN functional connectivity and decreased white matter volumes throughout all three networks (i.e., the DMN, ECN, and SN). Taken together, these findings: 1) offer a biologically plausible explanation for reduced cognitive performance, greater impulsivity, and altered reward processing among overweight individuals, and 2) suggest neurobiological mechanisms (i.e., altered functional and structural brain connectivity) that may affect overweight individuals’ ability to establish and maintain healthy lifestyle choices.
... It is perhaps worth noting that previous tract-based white matter atlases have implemented FA >0.15 and deviation angle thresholds above 40 • for similar reasons (e.g.,Wakana et al., 2004), while other deterministic tractography studies have used FA thresholds as low as 0.10 and deviation angle thresholds of 45 • (e.g.,Van den Heuvel and Sporns, 2011;Marqués-Iturria et al., 2015). Therefore, while the tractography parameters implemented in the current study are more liberal than the default values in DTIStudio, they are within previously established boundaries. ...
Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, “tractography”) approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template—using high-dimensional, non-linear warping methods—we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses.
... A dissociable pattern of structural connectivity was observed, using deterministic tractography, showing increased fiber tract density between reward network regions and decreased fiber tract density between prefrontal regions (Gupta et al., 2015). In addition, functional connectivity brain networks of the limbic and prefrontal system are especially vulnerable to increased body weight Kullmann et al., 2012Kullmann et al., , 2013Marques-Iturria et al., 2015). The prominent decrease in WM integrity of the MFB/ATR and SLF in obese adults could contribute to over-eating via the rich projections to and from the prefrontal cortex. ...
Obesity-related structural brain alterations point to a consistent reduction in gray matter with increasing body mass index (BMI) but changes in white matter have proven to be more complex and less conclusive. Hence, more recently diffusion tensor imaging (DTI) has been employed to investigate microstructural changes in white matter structure. Altogether, these studies have mostly shown a loss of white matter integrity with obesity-related factors in several brain regions. However, the variety of these obesity-related factors, including inflammation and dyslipidemia, resulted in competing influences on the DTI indices. To increase the specificity of DTI results, we explored specific brain tissue properties by combining DTI with quantitative multi-parameter mapping in lean, overweight and obese young adults. By means of multi-parameter mapping, white matter structures showed differences in MRI parameters consistent with reduced myelin, increased water and altered iron content with increasing BMI in the superior longitudinal fasciculus, anterior thalamic radiation, internal capsule and corpus callosum. BMI-related changes in DTI parameters revealed mainly alterations in mean and axial diffusivity with increasing BMI in the corticospinal tract, anterior thalamic radiation and superior longitudinal fasciculus. These alterations, including mainly fiber tracts linking limbic structures with prefrontal regions, could potentially promote accelerated aging in obese individuals leading to an increased risk for cognitive decline.
Background:
Metabolic syndrome score in children assesses the risk of developing cardiovascular disease in future. We aim to probe the role of the caudate in relation to the metabolic syndrome score. Furthermore, using both functional and structural neuroimaging, we aim to examine the interplay between functional and structural measures.
Methods:
A longitudinal birth cohort study with functional and structural neuroimaging data obtained at 4.5, 6.0 and 7.5 years and metabolic syndrome scores at 8.0 years was used. Pearson correlation and linear regression was used to test for correlation fractional anisotropy (FA) and fractional amplitude of low frequency fluctuations (fALFF) of the caudate with metabolic syndrome scores. Mediation analysis was used to test if later brain measures mediated the relation between earlier brain measures and metabolic syndrome scores. Inhibitory control was also tested as a mediator of the relation between caudate brain measures and metabolic syndrome scores.
Results:
FA at 4.5 years and fALFF at 7.5 years of the left caudate was significantly correlated with metabolic syndrome scores. Post-hoc mediation analysis showed that fALFF at 7.5 years fully mediated the relation between FA at 4.5 years and metabolic syndrome scores. Inhibitory control was significantly correlated with fALFF at 7.5 years, but did not mediate the relation between fALFF at 7.5 years and metabolic syndrome scores.
Conclusions:
We found that variations in caudate microstructure at 4.5 years predict later variation in functional activity at 7.5 years. This later variation in functional activity fully mediates the relation between microstructural changes in early childhood and metabolic syndrome scores at 8.0 years.
Eating behavior and food‐related decision making are among the most complex of the motivated behaviors, and understanding the neurobiology of eating behavior, and its developmental dynamics, is critical to advancing the nutritional sciences and public health. Recent advances from both human and animal studies are revealing that individual capacity to make health‐promoting food decisions varies based on biological and physiological variation in the signaling pathways that regulate the homeostatic, hedonic, and executive functions; past developmental exposures and current life‐stage; the food environment; and complications of chronic disease that reinforce the obese state. Eating rate drives increased calorie intake, and represents an important opportunity to lower rates of food consumption and energy intake through product reformulation. Understanding human eating behaviors and nutrition in the context of neuroscience can strengthen the evidence base from which dietary guidelines are derived and cam inform policies, practices, and educational programs in a way that increases the likelihood they are adopted and effective for reducing rates of obesity and other diet‐related chronic disease.
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Alzheimer disease (AD) and obesity are related to disruptions in the white matter (WM) connectome. We examined the link between the WM connectome and obesity and AD through edge-density imaging/index (EDI), a tractography-based method that characterizes the anatomical embedding of tractography connections. A total of 60 participants, 30 known to convert from normal cognition or mild-cognitive impairment to AD within a minimum of 24 months of follow up, were selected from the Alzheimer disease Neuroimaging Initiative (ADNI). Diffusion-weighted MR images from the baseline scans were used to extract fractional anisotropy (FA) and EDI maps that were subsequently averaged using deterministic WM tractography based on the Desikan-Killiany atlas. Multiple linear and logistic regression analysis were used to identify the weighted sum of tract-specific FA or EDI indices that maximized correlation to body-mass-index (BMI) or conversion to AD. Participants from the Open Access Series of Imaging Studies (OASIS) were used as an independent validation for the BMI findings. The edge-density rich, periventricular, commissural and projection fibers were among the most important WM tracts linking BMI to FA as well as to EDI. WM fibers that contributed significantly to the regression model related to BMI overlapped with those that predicted conversion; specifically in the frontopontine, corticostriatal, and optic radiation pathways. These results were replicated by testing the tract-specific coefficients found using ADNI in the OASIS-4 dataset. WM mapping with EDI enables identification of an abnormal connectome implicated in both obesity and conversion to AD.
Childhood obesity has become a global health problem. Previous studies showed that childhood obesity is associated with brain structural differences relative to controls. However, few studies have been performed with longitudinal evaluations of brain structural developmental trajectories in childhood obesity. We employed voxel-based morphometry (VBM) analysis to assess gray matter (GM) volume at baseline and 2-year follow-up in 258 obese children (OB) and 265 normal weight children (NW), recruited as part of the NIH Adolescent Brain and Cognitive Development (ABCD) study. Significant group × time effects on GM volume were observed in the prefrontal lobe, thalamus, right precentral gyrus, caudate, and parahippocampal gyrus/amygdala. OB compared to NW had greater reductions in GM volume in these regions over the 2-year period. BMI was negatively correlated with GM volume in prefrontal lobe and with matrix reasoning ability at baseline and 2-year follow-up. In OB, Picture Test was positively correlated with GM volume in the left orbital region of the inferior frontal gyrus (OFCinf_L) at baseline, and was negatively correlated with reductions in OFCinf_L volume (2-year follow-up vs. baseline). These findings indicate that childhood obesity is associated with GM volume reduction in regions involved with reward evaluation, executive function, and cognitive performance.
Obesity is related to overconsumption of high-calorie (HiCal) food, which is modulated by brain reward and inhibitory control circuitries. The basal ganglia (BG) are a key set of nuclei within the reward circuitry, but obesity-associated functional and structural abnormalities of BG have not been well studied. Resting-state functional MRI with independent component analysis (ICA) and probabilistic tractography were employed to investigate differences in BG-related functional-(FC) and structural connectivity (SC) between 32 patients with obesity (OB) and 35 normal-weight (NW) participants. Compared to NW, OB showed significantly lower FC strength in the caudate nucleus within the BG network, and seed-based FC analysis showed lower FC between caudate and dorsolateral prefrontal cortex (DLPFC), which was negatively correlated with craving for HiCal food cues. Further SC analysis revealed that OB showed lower SC than NW between left caudate and left DLPFC as measured with fractional anisotropy (FA). Alterations in FC and SC between caudate and DLPFC in obese patients, which highlights the role of BG network in modulating the balance between reward and inhibitory-control.
Introduction
N3 polyunsaturated fatty acids (n-3 PUFAs) exert anti-inflammatory effects for the hypothalamus, but their extra-hypothalamic outcome lack documentation. We evaluated the central consequences of the substitution of saturated fatty acids with n-3 or n-6 PUFA in obesogenic diets.
Methods
Twenty-one miniature pigs were fed ad libitum obesogenic diets enriched in fat provided either as lard, fish oil (source for n-3 PUFAs), or sunflower oil (source for n-6 PUFAs) for ten weeks. The blood–brain barrier (BBB) permeability was quantified by CT perfusion. Central autonomic network was evaluated using heart rate variability, and PET 18FDG was performed to assess brain metabolism.
Results
BBB permeability was higher in lard group, but heart rate variability changed only in fish oil group. Brain connectivity analysis and voxel-based comparisons show regional differences between groups except for the cingulate cortex in fish oil vs. sunflower oil groups.
Discussion
: The minute changes in brain metabolism in obese pigs feed with fish oil compared with saturated fatty acids were sufficient to induce detrimental changes in heart rate variability. On the contrary, the BBB's decreased permeability in n-3 and n-6 PUFAs groups was protective against an obesity-driven damaged BBB.
Background:
Prenatal development is a time when the brain is acutely vulnerable to insult and alteration by environmental factors (e.g., toxins, maternal health). One important risk factor is maternal obesity (Body Mass Index > 30). Recent research indicates that high maternal BMI during pregnancy is associated with increased risk for numerous physical health, cognitive, and mental health problems in offspring across the lifespan. It is possible that heightened maternal prenatal BMI influences the developing brain even before birth.
Methods:
The present study examines this possibility at the level of macrocircuitry in the human fetal brain. Using a data-driven strategy for parcellating the brain into subnetworks, we test whether MRI functional connectivity within or between fetal neural subnetworks varies with maternal prenatal BMI in 109 fetuses between the ages of 26 and 39weeks.
Results:
We discovered that strength of connectivity between two subnetworks, left anterior insula/inferior frontal gyrus (aIN/IFG) and bilateral prefrontal cortex (PFC), varied with maternal BMI. At the level of individual aIN/IFG-PFC connections, we observed both increased and decreased between-network connectivity with a tendency for increased within-hemisphere connectivity and reduced cross-hemisphere connectivity in higher BMI pregnancies. Maternal BMI was not associated with global differences in network topography based on network-based statistical analyses.
Conclusions:
Overall effects were localized in regions that will later support behavioral regulation and integrative processes, regions commonly associated with obesity-related deficits. By establishing onset in neural differences prior to birth, this study supports a model in which maternal BMI-related risk is associated with fetal connectome-level brain organization with implications for offspring long-term cognitive development and mental health.
Cognitive control and incentive sensitivity are related to overeating and obesity. Optimal white matter integrity is relevant for an efficient interaction among reward-related brain regions. However, its relationship with sensitivity to incentives remains controversial. The aim of this study was to assess the incentive sensitivity and its relationship to white matter integrity in normal-weight and overweight groups. Seventy-six young adults participated in this study: 31 were normal-weight (body mass index [BMI] 18.5 to < 25.0 kg/m², 14 females) and 45 were overweight (BMI ≥ 25.0 kg/m², 22 females). Incentive sensitivity was assessed using an antisaccade task that evaluates the effect of incentives (neutral, reward, and loss avoidance) on cognitive control performance. Diffusion tensor imaging studies were performed to assess white matter integrity. The relationship between white matter microstructure and incentive sensitivity was investigated through tract-based spatial statistics. Behavioral antisaccade results showed that normal-weight participants presented higher accuracy (78.0 vs. 66.7%, p = 0.01) for loss avoidance incentive compared to overweight participants. Diffusion tensor imaging analysis revealed a positive relationship between fractional anisotropy and loss avoidance accuracy in the normal-weight group (p < 0.05). No relationship reached significance in the overweight group. These results support the hypothesis that white matter integrity is relevant for performance in an incentivized antisaccade task.
Background: Obesity is of complex origin, involving genetic and neurobehavioral factors. Most consistently, polymorphisms in the fat-and-obesity associated gene (FTO) may increase the risk for developing obesity by modulating dopaminergic signaling in the brain. Dopamine-dependent behaviors, such as reward processing, are crucial for eating behavior and are altered in obesity. Yet, few studies have investigated the association of obesity, related genetic variants and structural connectivity of the dopaminergic reward network.
Methods: We analyzed 378 participants (age range: 20 - 59 years, BMI range: 17 - 38 kg/m2) of the LIFE-Adult Study. Genotyping for the single nucleotid polymorphisms rs1558902 (FTO) and rs1800497 (near dopamine D2 receptor) was performed on a micro-array. Structural connectivity of the reward network was derived from diffusion-weighted magnetic resonance imaging at 3 Tesla using deterministic tractography of Freesurfer-derived regions of interest. Using graph metrics, we extracted summary measures of clustering coefficient and connectivity strength between frontal and striatal brain regions, normalized for global connectivity. We applied linear regression models to test the association of BMI, risk alleles of both variants and reward network connectivity.
Results: Higher BMI was significantly associated with reduced connectivity strength for fractional anisotropy (β= -0.0011, 95%-C.I. [-0.0019, -0.0003], p= 0.0062) and number of streamlines (β = -0.0026, 95%-C.I.:[-0.004,-0.0009], p= 0.0024), but not clustering coefficient. Strongest associations were found for right accumbens, right lateral orbitofrontal cortex and left putamen. As expected, the polymorphism rs1558902 in FTO was associated with higher BMI (F=7.9, p<0.001). None of the genetic variants was associated with reward network structural connectivity.
Conclusions: Here, we provide evidence that higher BMI correlates with reduced reward network structural connectivity. This result is in line with previous findings of obesity-related decline in white matter microstructure. We did not find any association of variants in FTO or near DRD2 receptor and reward network structural connectivity, indicating that the genetic influence of these variants is small or non-existent. Future research should investigate the behavioral implications of structural connectivity differences in the fronto-striatal network and incorporate larger sample sizes with longitudinal designs in order to gain further insight into the genetic determinants of obesity in the brain.
Eating behaviors play an important role in individuals' development, and restrained eaters have a higher risk of obesity in the future. In the present study, we used the Three-Factor Eating Questionnaire to measure restrained eating, uncontrolled eating, and emotional eating in 158 young, normal-weight, Chinese women. We developed a multiple linear regression model to identify significant structural brain changes associated with the above-mentioned eating behaviors. Uncontrolled eating scores were positively associated with the gray matter volume (GMV) of the cerebellum, and negatively associated with the GMV on the left side of the anterior cingulate cortex, middle cingulate cortex, and supplementary motor areas, indicating that uncontrolled eating behaviors not only are less inhibitory but also appear to be associated with the low-level processing of appetite. Increased GMV on the right side of the precuneus was associated with a higher level of restrained eating, which might be thus related to a lower sensitivity to behavioral inhibition in young females who follow a diet. In addition, we did not find a relationship between emotional eating behavior and GMV. Our findings show that eating-behavior-related structural brain changes may lead to a decrease in inhibition and an increase in food sensitivity.
Macroscale white matter pathways are the infrastructure for large-scale communication in the human brain and a prerequisite for healthy brain function. Disruptions in the brain’s connectivity architecture play an important role in many psychiatric and neurological brain disorders. Here we show that connections important for global communication and network integration are particularly vulnerable to brain alterations across multiple brain disorders. We report on a cross-disorder connectome study comprising in total 1,033 patients and 1,154 matched controls across 8 psychiatric and 4 neurological disorders. We extracted disorder connectome fingerprints for each of these 12 disorders and combined them into a ‘cross-disorder disconnectivity involvement map’ describing the level of cross-disorder involvement of each white matter pathway of the human brain network. Network analysis revealed connections central to global network communication and integration to display high disturbance across disorders, suggesting a general cross-disorder involvement and the importance of these pathways in normal function.
Background/Objectives
Excessive body mass index (BMI) has been linked to a low-grade chronic inflammation state. Unhealthy BMI has also been related to neuroanatomical changes in adults. However, research in adolescents is relatively limited and has produced conflicting results. This study aims to address the relationship between BMI and adolescents’ brain structure as well as to test the role that inflammatory adipose-related agents might have over this putative link.
Methods
We studied structural MRI and serum levels of interleukin-6, tumor necrosis factor alpha (TNF-α), C-reactive protein and fibrinogen in 65 adolescents (aged 12-21 years). Relationships between BMI, cortical thickness and surface area were tested with a vertex-wise analysis. Subsequently, we used backward multiple linear regression models to explore the influence of inflammatory parameters in each brain-altered area.
Results
We found a negative association between cortical thickness and BMI in the left lateral occipital cortex (LOC), the left fusiform gyrus and the right precentral gyrus as well as a positive relationship between surface area and BMI in the left rostral middle frontal gyrus and the right superior frontal gyrus. In addition, we found that higher fibrinogen serum concentrations were related to thinning within the left LOC (β = −0.45, p < 0.001) and the left fusiform gyrus (β = - 0.33, p = 0.035), while higher serum levels of TNF-α were associated to a greater surface area in the right superior frontal gyrus (β = 0.32, p = 0.045).
Conclusions
These results suggest that adolescents’ body mass increases are related with brain abnormalities in areas that could play a relevant role in some aspects of feeding behavior. Likewise, we have evidenced that these cortical changes were partially driven by inflammatory agents such as fibrinogen and TNF-α.
Macroscale white matter pathways form the infrastructure for large-scale communication in the human brain, a prerequisite for healthy brain function. Conversely, disruptions in the brain's connectivity architecture are thought to play an important role in a wide range of psychiatric and neurological brain disorders. Here we show that especially connections important for global communication and network integration are involved in a wide range of brain disorders. We report on a meta-analytic connectome study comprising in total 895 patients and 1,016 controls across twelve neurological and psychiatric disorders. We extracted disorder connectome fingerprints for each of these twelve disorders, which were then combined into a cross-disorder disconnectivity involvement map, representing the involvement of each brain pathway across brain disorders. Our findings show connections central to the brain's infrastructure are disproportionally involved across a wide range of disorders. Connections critical for global network communication and integration display high disturbance across disorders, suggesting a general cross-disorder involvement and importance of these pathways in normal function. Taken together, our cross-disorder study suggests a convergence of disconnectivity across disorders to a partially shared disconnectivity substrate of central connections.
Background/objectives:
The brain has a central role in regulating ingestive behavior in obesity. Analogous to addiction behaviors, an imbalance in the processing of rewarding and salient stimuli results in maladaptive eating behaviors that override homeostatic needs. We performed network analysis based on graph theory to examine the association between body mass index (BMI) and network measures of integrity, information flow and global communication (centrality) in reward, salience and sensorimotor regions and to identify sex-related differences in these parameters.
Subjects/methods:
Structural and diffusion tensor imaging were obtained in a sample of 124 individuals (61 males and 63 females). Graph theory was applied to calculate anatomical network properties (centrality) for regions of the reward, salience and sensorimotor networks. General linear models with linear contrasts were performed to test for BMI and sex-related differences in measures of centrality, while controlling for age.
Results:
In both males and females, individuals with high BMI (obese and overweight) had greater anatomical centrality (greater connectivity) of reward (putamen) and salience (anterior insula) network regions. Sex differences were observed both in individuals with normal and elevated BMI. In individuals with high BMI, females compared to males showed greater centrality in reward (amygdala, hippocampus and nucleus accumbens) and salience (anterior mid-cingulate cortex) regions, while males compared to females had greater centrality in reward (putamen) and sensorimotor (posterior insula) regions.
Conclusions:
In individuals with increased BMI, reward, salience and sensorimotor network regions are susceptible to topological restructuring in a sex-related manner. These findings highlight the influence of these regions on integrative processing of food-related stimuli and increased ingestive behavior in obesity, or in the influence of hedonic ingestion on brain topological restructuring. The observed sex differences emphasize the importance of considering sex differences in obesity pathophysiology.
Evidence suggests that obesity and overweight may be associated with severe brain structural abnormalities and poor cognitive and functional outcomes in the general population. Despite these observations and the high prevalence of weight gain abnormalities in patients with psychosis spectrum disorders (PSDs), no studies have investigated the impact that these metabolic disturbances may have on brain structures and development in the earliest stages of PSDs. In the present review we shed light on the association between weight gain and brain structural abnormalities that may affect the course of illness in drug-na?ve FEPs. Given the lack of studies directly investigating this issue, we firstly identified and critically evaluated the literature assessing weight gain abnormalities and gray or white matter (GM, WM) volumes (either globally or in specific regions of interest) in otherwise healthy obese/overweight adolescents and young adults. We then compared the results of this systematic review with those of two recent meta-analysis investigating GM and WM abnormalities in drug-na?ve FEPs. Weight gain in otherwise healthy subjects was consistently associated with frontal and temporal GM atrophy and with reduced integrity of WM in the corpus callosum. Of relevance, all these brain regions are affected in drug-na?ve FEPs, and their integrity is associated with clinical, cognitive and functional outcomes. The underlying mechanisms that may explain the association between weight gain, adiposity, and brain damage in both healthy subjects and drug-na?ve FEPs are widely discussed. On the basis of this knowledge, we tried: a) to deduce an integrative model for the development of obesity in psychosis spectrum disorders; b) to identify the key vulnerability factors underlying the association between weight gain and psychosis; c) to provide information on new potential targets of intervention.
Global brain connectivity (GBC) identifies regions of the brain, termed “hubs,” which are densely connected and metabolically costly, and have a wide influence on brain function. Since obesity is associated with central and peripheral metabolic dysfunction we sought to determine if GBC is altered in obesity. Two independent fMRI data sets were subjected to GBC analyses. The first data set was acquired while participants (n = 15 healthy weight and 15 obese) tasted milkshake and the second with participants at rest (n = 33 healthy weight and 28 obese). In the resting state and during milkshake consumption GBC is consistently decreased in the ventromedial and ventrolateral prefrontal cortex, insula and caudate nucleus, and increased in brain regions belonging to the dorsal attention network including premotor areas, superior parietal lobule, and visual cortex. During milkshake consumption, but not at rest, additional decreases in GBC are observed in feeding-related circuitry including the insula, amygdala, anterior hippocampus, hypothalamus, midbrain, brainstem and somatomotor cortex. Additionally, GBC differences were not accounted for by age. These results demonstrate that obesity is associated with decreased GBC in prefrontal and feeding circuits and increased GBC in the dorsal attention network. We therefore conclude that global brain organization is altered in obesity to favor networks important for external orientation over those monitoring homeostatic state and guiding feeding decisions. Furthermore, since prefrontal decreases are also observed at rest in obese individuals future work should evaluate whether these changes are associated with neurocognitive impairments frequently observed in obesity and diabetes. Hum Brain Mapp, 2016.
In contrast to the task-based fMRI, the resting-state fMRI (rs-fMRI) doesn’t require a specific task, since
data are obtained during rest for a relatively short scan time (about 10 min). Therefore, rs-fMRI provides
advantages in studying individual differences not associated with the task, and in obtaining data from a
large population of various groups (clinical or normal healthy). In the current review, we introduced
several analyzing techniques for rs-fMRI. These techniques allow us to identify the functional connectivity
among specific regions (seed-based functional connectivity analysis, independent component analysis), a
network pattern composed of nodes (graph-based network analysis), or the spontaneous activity pattern
(regional homogeneity, analysis of low-frequency fluctuation) during rest. The individual differences found
during rest with these techniques have been shown to be related to individual differences (e.g., personality
traits) or clinical diseases, such as depression, Alzheimer’s diseases, and autism. Choosing an optimal
research technique for a specific study question would be possible only with a deep understanding of these
analysis techniques.
Anorexia nervosa is a severe psychiatric disorder associated with reduced drive to eat. Altered taste-reward circuit white matter fiber organization in anorexia nervosa after recovery could indicate a biological marker that alters the normal motivation to eat. Women recovered from restricting-type anorexia (Recovered AN, n=24, age=30.3±8.1 years) and healthy controls (n=24, age=27.4±6.3 years) underwent diffusion weighted imaging (DWI) of the brain. Probabilistic tractography analyses calculated brain white matter connectivity (streamlines) as an estimate of fiber connections in taste-reward related white matter tracts, and microstructural integrity (fractional anisotropy, FA) was assessed using tract-based spatial statistics (TBSS). Recovered AN showed significantly (range P<0.05-0.001) greater white matter connectivity between bilateral insula regions and ventral striatum, left insula and middle orbitofrontal cortex (OFC), and right insula projecting to gyrus rectus and medial OFC. Duration of illness predicted connectivity of tracts projecting from the insula to ventral striatum and OFC. Microstructural integrity was lower in Recovered AN in most insula white matter tracts, as was whole brain FA in parts of the anterior corona radiata, external capsule, and cerebellum (P<0.05, FWE-corrected). This study indicates higher structural white matter connectivity, an estimate of fibers connections, in anorexia after recovery in tracts that connect taste-reward processing regions. Greater connectivity together with less fiber integrity could indicate altered neural activity between those regions, which could interfere with normal food-reward circuit function. Correlations between connectivity and illness duration suggest that connectivity could be a marker for illness severity. Whether greater connectivity can predict prognosis of the disorder requires further study.Neuropsychopharmacology accepted article preview online, 16 June 2015. doi:10.1038/npp.2015.172.
This chapter discusses the anatomy and connectivity of the reward circuit. The reward circuit is a complex neural network that underlies the ability to effectively assess the likely outcomes from different choices. The cortico-basal ganglia network is at the center of the reward circuit that underlies the ability to make complex choices and accurately evaluate reward value, predictability, and risk. The key structures are the anterior cingulate cortex, the ventral striatum, the ventral pallidum, and the dopamine neurons of the ventral tegmental area and the substantia nigra, pars compacta. The amygdala, hippocampus, thalamus, lateral habenular nucleus, and specific brainstem structures, such as the pedunculopontine nucleus and the raphe nucleus, are key components in regulating the reward circuit. While pathways from the cortex through the striatum, pallidum, thalamus, and back to the cortex are generally topographically organized, there are key areas of convergence of between different functional regions, which provides an important substrate for integration between functional domains. Through these integrative networks, the reward circuit impacts on cognition and motor control, allowing information about reward to be channeled through cognitive and motor control circuits to mediate the development of appropriate action plans.
Many brain imaging studies have demonstrated reductions in gray and white matter volumes in alcoholism, with fewer investigators using diffusion tensor imaging (DTI) to examine the integrity of white matter pathways. Among various medical conditions, alcoholism and post-traumatic stress disorder (PTSD) are two comorbid diseases that have similar degenerative effects on the white matter integrity. Therefore, understanding and differentiating these effects would be very important in characterizing alcoholism and PTSD. Alcoholics are known to have neurocognitive deficits in decision-making, particularly in decisions related to emotionally-motivated behavior, while individuals with PTSD have deficits in emotional regulation and enhanced fear response. It is widely believed that these types of abnormalities in both alcoholism and PTSD are related to fronto-limbic dysfunction. In addition, previous studies have shown cortico-limbic fiber degradation through fiber tracking in alcoholism. DTI was used to measure white matter fractional anisotropy (FA), which provides information about tissue microstructure, possibly indicating white matter integrity. We quantitatively investigated the microstructure of white matter through whole brain DTI analysis in healthy volunteers (HV) and alcohol dependent subjects without PTSD (ALC) and with PTSD (ALC+PTSD). These data show significant differences in FA between alcoholics and non-alcoholic HVs, with no significant differences in FA between ALC and ALC+PTSD in any white matter structure. We performed a post-hoc region of interest analysis that allowed us to incorporate multiple covariates into the analysis and found similar results. HV had higher FA in several areas implicated in the reward circuit, emotion, and executive functioning, suggesting that there may be microstructural abnormalities in white matter pathways that contribute to neurocognitive and executive functioning deficits observed in alcoholics. Furthermore, our data do not reveal any differences between ALC and ALC+PTSD, suggesting that the effect of alcohol on white matter microstructure may be more significant than any effect caused by PTSD.
Ketamine is an N-methyl-D-aspartate (NMDA) receptor antagonist that has been found to induce schizophrenia-type symptoms in humans and is a potent and fast-acting anti-depressant. It is also a relatively widespread drug of abuse, particular in China and the UK. Acute administration has been well characterised, but the effect of extended periods of ketamine use-on brain structure in humans-remains poorly understood. We measured indices of white matter microstructural integrity and connectivity in the brain of 16 ketamine users and 16 poly-drug using controls, and used probabilistic tractography to quantify changes in cortico-subcortical connectivity associated with ketamine use. We found a reduction in the axial diffusivity profile of white matter in a right hemisphere network of white matter regions in ketamine users compared to controls. Within the ketamine user group, we found a significant positive association between the connectivity profile between caudate nucleus and lateral prefrontal cortex and dissociative experiences. These findings suggest that chronic ketamine use may be associated with widespread disruption of white matter integrity, and white matter pathways between subcortical and prefrontal cortical areas may in part predict individual differences in dissociative experiences due to ketamine use.Neuropsychopharmacology accepted article preview online, 9 August 2013. doi:10.1038/npp.2013.195.
The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges
Our brains are hardwired to respond and seek immediate rewards. Thus, it is not surprising that many people overeat, which in some can result in obesity, whereas others take drugs, which in some can result in addiction. Though food intake and body weight are under homeostatic regulation, when highly palatable food is available, the ability to resist the urge to eat hinges on self-control. There is no homeostatic regulator to check the intake of drugs (including alcohol); thus, regulation of drug consumption is mostly driven by self-control or unwanted effects (i.e., sedation for alcohol). Disruption in both the neurobiological processes that underlie sensitivity to reward and those that underlie inhibitory control can lead to compulsive food intake in some individuals and compulsive drug intake in others. There is increasing evidence that disruption of energy homeostasis can affect the reward circuitry and that overconsumption of rewarding food can lead to changes in the reward circuitry that result in compulsive food intake akin to the phenotype seen with addiction. Addiction research has produced new evidence that hints at significant commonalities between the neural substrates underlying the disease of addiction and at least some forms of obesity. This recognition has spurred a healthy debate to try and ascertain the extent to which these complex and dimensional disorders overlap and whether or not a deeper understanding of the crosstalk between the homeostatic and reward systems will usher in unique opportunities for prevention and treatment of both obesity and drug addiction.
Obesity is a health problem that has become a major focus of attention in recent years. There is growing evidence of an association between obesity and differences in reward processing. However, it is not known at present whether these differences are linked exclusively to food, or whether they can be detected in other rewarding stimuli. We compared responses to food, rewarding non-food and neutral pictures in 18 young adults with obesity and 19 normal-weight subjects using independent component analysis. Both groups modulated task-related activity in a plausible way. However, in response to both food and non-food rewarding stimuli, participants with obesity showed weaker connectivity in a network involving activation of frontal and occipital areas and deactivation of the posterior part of the default mode network. In addition, obesity was related with weaker activation of the default mode network and deactivation of frontal and occipital areas while viewing neutral stimuli. Together, our findings suggest that obesity is related to a different allocation of cognitive resources in a fronto-occipital network and in the default mode network.
Drug addiction and obesity appear to share several properties. Both can be defined as disorders in which the saliency of a specific type of reward (food or drug) becomes exaggerated relative to, and at the expense of others rewards. Both drugs and food have powerful reinforcing effects, which are in part mediated by abrupt dopamine increases in the brain reward centres. The abrupt dopamine increases, in vulnerable individuals, can override the brain's homeostatic control mechanisms. These parallels have generated interest in understanding the shared vulnerabilities between addiction and obesity. Predictably, they also engendered a heated debate. Specifically, brain imaging studies are beginning to uncover common features between these two conditions and delineate some of the overlapping brain circuits whose dysfunctions may underlie the observed deficits. The combined results suggest that both obese and drug-addicted individuals suffer from impairments in dopaminergic pathways that regulate neuronal systems associated not only with reward sensitivity and incentive motivation, but also with conditioning, self-control, stress reactivity and interoceptive awareness. In parallel, studies are also delineating differences between them that centre on the key role that peripheral signals involved with homeostatic control exert on food intake. Here, we focus on the shared neurobiological substrates of obesity and addiction.
Obesity is a multifactorial disease caused by the interaction between genotype and environment, and it is considered to be a type of addictive alteration. The A1 allele of the DRD2/ANKK1-TaqIA gene has been associated with addictive disorders, with obesity and with the performance in executive functions. The 7 repeat allele of the DRD4 gene has likewise been associated with the performance in executive functions, as well as with addictive behaviors and impulsivity. Participants were included in the obesity group (N = 42) if their body mass index (BMI) was equal to or above 30, and in the lean group (N = 42) if their BMI was below 25. The DRD2/ANKK1-TaqIA and DRD4 VNTR polymorphisms were obtained. All subjects underwent neuropsychological assessment. Eating behavior traits were evaluated. The 'DRD2/ANKK1-TaqIA A1-allele status' had a significant effect on almost all the executive variables, but no significant 'DRD4 7R-allele status' effects were observed for any of the executive variables analyzed. There was a significant 'group' x 'DRD2/ANKK1-TaqIA A1-allele status' interaction effect on LN and 'group' x 'DRD4 7R-allele status' interaction effect on TMT B-A score. Being obese and a carrier of the A1 allele of DRD2/ANKK1-TaqIA or the 7R allele of DRD4 VNTR polymorphisms could confer a weakness as regards the performance of executive functions.
Delay discounting, a measure of impulsive choice, has been associated with decreased control of the prefrontal cortex over striatum responses. The anatomical connectivity between both brain regions in delaying gratification remains unknown. Here, we investigate whether the quality of frontostriatal (FS) white matter tracts can predict individual differences in delay-discounting behavior. We use tract-based diffusion tensor imaging and magnetization transfer imaging to measure the microstructural properties of FS fiber tracts in 40 healthy young adults (from 18 to 25 years). We additionally explored whether internal sex hormone levels affect the integrity of FS tracts, based on the hypothesis that sex hormones modulate axonal density within prefrontal dopaminergic circuits. We calculated fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity, radial diffusivity (RD), and magnetization transfer ratio (MTR), a putative measure of myelination, for the FS tract. Results showed that lower integrity within the FS tract (higher MD and RD and lower FA), predicts faster discounting in both sexes. MTR was unrelated to delay-discounting performance. In addition, testosterone levels in males were associated with a lower integrity (higher RD) within the FS tract. Our study provides support for the hypothesis that enhanced structural integrity of white matter fiber bundles between prefrontal and striatal brain areas is associated with better impulse control.
Internet addiction disorder (IAD) is currently becoming a serious mental health issue around the globe. Previous studies regarding IAD were mainly focused on associated psychological examinations. However, there are few studies on brain structure and function about IAD. In this study, we used diffusion tensor imaging (DTI) to investigate white matter integrity in adolescents with IAD.
Seventeen IAD subjects and sixteen healthy controls without IAD participated in this study. Whole brain voxel-wise analysis of fractional anisotropy (FA) was performed by tract-based spatial statistics (TBSS) to localize abnormal white matter regions between groups. TBSS demonstrated that IAD had significantly lower FA than controls throughout the brain, including the orbito-frontal white matter, corpus callosum, cingulum, inferior fronto-occipital fasciculus, and corona radiation, internal and external capsules, while exhibiting no areas of higher FA. Volume-of-interest (VOI) analysis was used to detect changes of diffusivity indices in the regions showing FA abnormalities. In most VOIs, FA reductions were caused by an increase in radial diffusivity while no changes in axial diffusivity. Correlation analysis was performed to assess the relationship between FA and behavioral measures within the IAD group. Significantly negative correlations were found between FA values in the left genu of the corpus callosum and the Screen for Child Anxiety Related Emotional Disorders, and between FA values in the left external capsule and the Young's Internet addiction scale.
Our findings suggest that IAD demonstrated widespread reductions of FA in major white matter pathways and such abnormal white matter structure may be linked to some behavioral impairments. In addition, white matter integrity may serve as a potential new treatment target and FA may be as a qualified biomarker to understand the underlying neural mechanisms of injury or to assess the effectiveness of specific early interventions in IAD.
The human brain is a complex network of interlinked regions. Recent studies have demonstrated the existence of a number of highly connected and highly central neocortical hub regions, regions that play a key role in global information integration between different parts of the network. The potential functional importance of these "brain hubs" is underscored by recent studies showing that disturbances of their structural and functional connectivity profile are linked to neuropathology. This study aims to map out both the subcortical and neocortical hubs of the brain and examine their mutual relationship, particularly their structural linkages. Here, we demonstrate that brain hubs form a so-called "rich club," characterized by a tendency for high-degree nodes to be more densely connected among themselves than nodes of a lower degree, providing important information on the higher-level topology of the brain network. Whole-brain structural networks of 21 subjects were reconstructed using diffusion tensor imaging data. Examining the connectivity profile of these networks revealed a group of 12 strongly interconnected bihemispheric hub regions, comprising the precuneus, superior frontal and superior parietal cortex, as well as the subcortical hippocampus, putamen, and thalamus. Importantly, these hub regions were found to be more densely interconnected than would be expected based solely on their degree, together forming a rich club. We discuss the potential functional implications of the rich-club organization of the human connectome, particularly in light of its role in information integration and in conferring robustness to its structural core.
Neuroimaging is becoming increasingly common in obesity research as investigators try to understand the neurological underpinnings of appetite and body weight in humans. Positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and magnetic resonance imaging (MRI) studies examining responses to food intake and food cues, dopamine function and brain volume in lean vs. obese individuals are now beginning to coalesce in identifying irregularities in a range of regions implicated in reward (e.g. striatum, orbitofrontal cortex, insula), emotion and memory (e.g. amygdala, hippocampus), homeostatic regulation of intake (e.g. hypothalamus), sensory and motor processing (e.g. insula, precentral gyrus), and cognitive control and attention (e.g. prefrontal cortex, cingulate). Studies of weight change in children and adolescents, and those at high genetic risk for obesity, promise to illuminate causal processes. Studies examining specific eating behaviours (e.g. external eating, emotional eating, dietary restraint) are teaching us about the distinct neural networks that drive components of appetite, and contribute to the phenotype of body weight. Finally, innovative investigations of appetite-related hormones, including studies of abnormalities (e.g. leptin deficiency) and interventions (e.g. leptin replacement, bariatric surgery), are shedding light on the interactive relationship between gut and brain. The dynamic distributed vulnerability model of eating behaviour in obesity that we propose has scientific and practical implications.
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.
Decision neuroscience suggests that there exists a core network for the subjective valuation of rewards from a range of different domains, encompassing the ventral striatum and regions of the orbitofrontal cortex (OFC), in particular the ventromedial aspect of the OFC. Here we first review ways to measure subjective value experimentally in a cognitive neuroscience context, and provide a brief overview over different types of value (outcome, goal and decision value). We then compare results of functional neuroimaging studies of subjective value representations across these different types of value. Our analysis suggests that the same region of the mOFC represents the outcome values of primary reinforcers, but also more complex decision values in which multiple dimensions of the reward need to be integrated. The subjective (hedonic) experience of processing highly valued decision options (regardless of whether they refer to actually experienced rewards or merely potential future rewards) appears to be what is reflected in value-related mOFC activity.
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 relationship between brain structure and complex behavior is governed by large-scale neurocognitive networks. The availability of a noninvasive technique that can visualize the neuronal projections connecting the functional centers should therefore provide new keys to the understanding of brain function. By using high-resolution three-dimensional diffusion magnetic resonance imaging and a newly designed tracking approach, we show that neuronal pathways in the rat brain can be probed in situ. The results are validated through comparison with known anatomical locations of such fibers. Ann Neurol 1999;45:265–269
Background/objectives:
What drives overconsumption of food is poorly understood. Alterations in brain structure and function could contribute to increased food seeking. Recently, brain orbitofrontal cortex (OFC) volume has been implicated in dysregulated eating but little is known how brain structure relates to function.
Subjects/methods:
We examined obese (n=18, age=28.7±8.3 years) and healthy control women (n=24, age=27.4±6.3 years) using a multimodal brain imaging approach. We applied magnetic resonance and diffusion tensor imaging to study brain gray and white matter volume as well as white matter (WM) integrity, and tested whether orbitofrontal cortex volume predicts brain reward circuitry activation in a taste reinforcement-learning paradigm that has been associated with dopamine function.
Results:
Obese individuals displayed lower gray and associated white matter volumes (P<0.05 family-wise error (FWE)- small volume corrected) compared with controls in the orbitofrontal cortex, striatum and insula. White matter integrity was reduced in obese individuals in fiber tracts including the external capsule, corona radiata, sagittal stratum, and the uncinate, inferior fronto-occipital, and inferior longitudinal fasciculi. Gray matter volume of the gyrus rectus at the medial edge of the orbitofrontal cortex predicted functional taste reward-learning response in frontal cortex, insula, basal ganglia, amygdala, hypothalamus and anterior cingulate cortex in control but not obese individuals.
Conclusions:
This study indicates a strong association between medial orbitofrontal cortex volume and taste reinforcement-learning activation in the brain in control but not in obese women. Lower brain volumes in the orbitofrontal cortex and other brain regions associated with taste reward function as well as lower integrity of connecting pathways in obesity (OB) may support a more widespread disruption of reward pathways. The medial orbitofrontal cortex is an important structure in the termination of food intake and disturbances in this and related structures could contribute to overconsumption of food in obesity.
The prevalence of obesity is increasing worldwide. Previous research has shown a relationship between obesity and both executive functioning alterations and frontal cortex volume reductions. The Brain Derived Neurotrophic Factor val66met polymorphism, involved in eating behavior, has also been associated with executive functions and prefrontal cortex volume, but to date it has not been studied in relation to obesity. Our aim is to elucidate whether the interaction between the Brain Derived Neurotrophic Factor val66met polymorphism and obesity status influences executive performance and frontal-subcortical brain structure. Sixty-one volunteers, 34 obese and 27 controls, age range 12-40, participated in the study. Participants were assigned to one of two genotype groups (met allele carriers, n = 16, or non-carriers, n = 45). Neuropsychological assessment comprised the Trail Making Test, the Stroop Test and the Wisconsin Card Sorting Test, all tasks that require response inhibition and cognitive flexibility. Subjects underwent magnetic resonance imaging in a Siemens TIM TRIO 3T scanner and images were analyzed using the FreeSurfer software. Analyses of covariance controlling for age and intelligence showed an effect of the obesity-by-genotype interaction on perseverative responses on the Wisconsin Card Sorting Test as well as on precentral and caudal middle frontal cortical thickness: obese met allele carriers showed more perseverations on the Wisconsin Card Sorting Test and lower frontal thickness than obese non-carriers and controls. In conclusion, the Brain Derived Neurotrophic Factor may play an important role in executive functioning and frontal brain structure in obesity. © 2014 Wiley Periodicals, Inc.
Late-life major depression (LLD) is characterized by distinct epidemiologic and psychosocial factors, as well as medical comorbidities that are associated with specific neuroanatomical differences. The purpose of this study was to use interregional correlations of cortical and subcortical volumes to examine cortical-subcortical structural network properties in subjects with LLD compared with healthy comparison subjects.
This was a cross-sectional neuroimaging study conducted in the general community. We recruited 73 healthy elderly comparison subjects and 53 subjects with LLD who volunteered in response to advertisements. Brain network connectivity measures were generated by correlating regional volumes after controlling for age, gender, and intracranial volume by using the Brain Connectivity Toolbox.
Results for overall network strength revealed that LLD networks showed a greater magnitude of associations for both positive and negative correlation weights compared with healthy elderly networks. LLD networks also demonstrated alterations in brain network structure compared with healthy comparison subjects. LLD networks were also more vulnerable to targeted attacks compared with healthy elderly comparison subjects, and this vulnerability was attenuated when controlling for white matter alterations.
Overall, this study demonstrates that cortical-subcortical network properties are altered in LLD and may reflect the underlying neuroanatomical vulnerabilities of the disorder.
Objective:
Little is known about the mechanisms by which obesity influences brain structure. In this study, the obesity-related changes in brain white and gray matter integrity were examined.
Design and methods:
23 morbidly obese subjects and 22 nonobese volunteers were studied using voxel-based analysis of diffusion tensor imaging and of T1-weighted MRI images. Full-volume statistical parametric mapping analysis was used to compare fractional anisotropy (FA) and mean diffusivity (MD) values as well as gray (GM) and white matter (WM) density between these groups.
Results:
Obese subjects had lower FA and MD values and lower focal and global GM and WM volumes than control subjects did. The focal structural changes were observed in brain regions governing reward seeking, inhibitory control, and appetite. Regression analysis showed that FA and MD values as well as GM and WM density were negatively associated with body fat percentage. Moreover, the volume of abdominal subcutaneous fat was negatively associated with GM density in most regions.
Conclusion:
These findings imply that changes in GM and WM in obesity may be due to metabolic factors. Atrophy in regions involved in reward processing and appetite control may further promote abnormal reward seeking and eating behavior.