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Abstract: Patient motion during positron emission tomography scanning can affect the accuracy of the data analysis in two ways: 1) movement occurring during emission data acquisition alters the time activity curves (TACs), measured at a voxel or region of interest (ROI), and hence introduces errors in the parameter estimates derived from kinetic modeling; 2) emission–transmission mismatches introduce errors during attenuation and scatter correction, and hence in the radioactivity distribution estimates for each time frame of the scan. With the aim of designing an algorithm-based frame realignment method, we first conducted investigations that aimed at optimizing the parameters of a coregistration method, such as the choice of the target volume and the similarity criterion. Based on these results we designed a novel frame realignment strategy in a multi-step algorithm using uncorrected reconstructed images, cross-correlation similarity criteria for the determination of inter-frame motion parameters and emission-transmission mismatch for each frame. Features and validation results are reported here based on a multi-subject simulated [11C]raclopride dynamic PET scan database incorporating intra-frame movements of various magnitudes and with various times of occurrence. Performances of the proposed algorithm were evaluated at regional and voxel-based level for binding potential parametric images. [Copyright &y& Elsevier]

Abstract: Research on dopamine (DA) transmission has emphasized the importance of increased phasic DA cell firing in the presence of unpredictable rewards. Using [11C]raclopride PET, we previously reported that DA transmission was both suppressed and enhanced in different regions of the striatum during an unpredictable reward task [Zald, D.H., Boileau, I., El Dearedy, W., Gunn, R., McGlone, F., Dichter, G.S. et al. (2004). Dopamine transmission in the human striatum during monetary reward tasks. J. Neurosci. 24, 4105–4112]. However, it was unclear if reductions in DA release during this task reflected a response to the high proportion of nonrewarding trials, and whether the behavioral demands of the task influenced the observed response. To test these issues, we presented 10 healthy subjects with an automated (passive) roulette wheel game in which the amount of reward and its timing were unpredictable and the rewarding trials greatly outnumbered the nonrewarding ones. As in the previous study, DA transmission in the putamen was significantly suppressed relative to a predictable control condition. A similar suppression occurred when subjects were presented with temporally unpredictable novel pictures and sounds. At present, models of DA functioning during reward do not account for this suppression, but given that it has been observed in two different studies using different reward paradigms, this phenomenon warrants attention. Neither the unpredictable reward nor the novelty conditions produced consistent increases in striatal DA transmission. These data suggest that active behavioral engagement may be necessary to observe robust statewise increases in DA release in the striatum. [Copyright &y& Elsevier]

Abstract: Multiple sclerosis (MS) is thought to predominantly affect white matter (WM). Recently, however, loss of cortical gray matter has also been described. Little is known about the cause of cortical atrophy in MS, whether it occurs early in the disease course, and whether it affects all cortical regions equally or if there is a preferential pattern of focal cortical atrophy. An automated method was used to compute the thickness at every vertex of the cortical surface of the brains of 425 early relapsing–remitting MS patients. We correlated cortical thickness with the WM lesion load and the Expanded Disability Status Scale score. Mean cortical thickness correlated with WM lesion load and disability. The correlations of cortical thickness with total lesion load and disability were most significant in cingulate gyrus, insula, and associative cortical regions. Conversely, primary sensory, visual, and motor areas showed a less significant relationship. The highest amount of atrophy per lesion volume or disability scale unit was in the anterior cingulate cortex. This study confirms the relation between cortical atrophy, WM lesion load, and disability in MS, and suggests that cortical atrophy occurs even in MS patients with only mild disability. Most interestingly, we show a specific regional pattern of focal atrophy in MS that is distinctively different from the one in normal aging. The predilection of the atrophic process for areas that are heavily inter-connected with other brain regions suggests that interruption of WM tracts by MS plaques contributes, at least in part, to the development of cortical atrophy. [Copyright &y& Elsevier]

Obesity and hypothalamic inflammation are causally related. It is unclear whether this neuroinflammation precedes or results from obesity. Animal studies show that an increase in food intake can lead to hypothalamic inflammation, but hypothalamic inflammation can create a feedback loop that further increases food intake. Internal and external factors mediate patterns of food intake and how it can affect the hypothalamus. Measures of water diffusivity in magnetic resonance imaging of the brain such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) are associated with grey matter inflammation. Here, we investigated how those measures are associated with obesity-related variables in groups of young and older adults. We found relationships between decreased diffusivity and obesity markers in young adults. In older adults, obesity and comorbidities were also related to significant changes in diffusivity. Here, diffusivity was strongly associated with body mass index (BMI) and blood levels of C-reactive protein (CRP) in multiple subcortical regions, rather than only the hypothalamus. Our results suggest that diffusivity measures can be used to investigate obesity-associated changes in the brain that can potentially reflect neuroinflammation. The connection seen between subcortical inflammation and obesity opens the conversation on preventative interventions needed to reduce the effects of obesity at all stages in life. [ABSTRACT FROM AUTHOR]

Abstract: Human brain imaging studies demonstrate distributed activation of limbic, paralimbic and sensory systems to food and food-associated cues. Activity in this circuit may be modulated by internal factors, such as hunger, and cognitive factors. Anticipation to eat is one such factor, which likely impacts consummatory behavior. Here, the neural substrates of food expectancy were identified in 10 healthy male participants who underwent two whole-brain functional Magnetic Resonance Imaging scans on separate days. Fasted subjects viewed images of food and scenery, in two counterbalanced states. During one condition, subjects were ‘expecting’ to eat right after the scan and during the other they were ‘not expecting’ to eat for 1h after the scan. Food pictures compared with scenery yielded bilateral activation in visual areas as well as in the left insula and amygdala in both conditions. The left dorsolateral prefrontal cortex, hippocampus and putamen were additionally activated in the ‘not expecting’ condition while right orbitofrontal cortex activity was enhanced in the ‘expecting’ condition. These data suggest that cognitive manipulations affect the response to food cues in the prefrontal cortex, in areas involved in the planning and control of motivated behaviors, while the amygdala and insula responded equally in both conditions, consistent with a more basic role in homeostatically driven appetitive behavior. [Copyright &y& Elsevier]

Seven healthy subjects underwent two [11C]raclopride positron emission tomography (PET) scans, one following a 16-h fast and the other after consumption of a favorite meal (following a 16-h fast) in counterbalanced fashion. Before and after each scan subjects gave ratings of hunger/fullness and desire to eat. In addition, meal pleasantness ratings were collected immediately after consumption of the favorite meal. PET data were analyzed using brain parametric maps to generate regions of statistically significant change, as well as regions of interest manually drawn on each individual''s coregistered anatomical image. [11C]Raclopride binding potential was compared across the two states (hungry and full). A significant reduction in binding potential was observed in the full compared to the hungry state in the dorsal putamen and caudate nucleus, indicative of dopamine release. There were no changes elsewhere in the striatum. A correlation was observed between the reduction in [11C]raclopride binding and meal pleasantness ratings, but not with desire to eat (hunger) or satiety after eating. These results suggest that feeding is associated with dopamine release in the dorsal, but not the ventral striatum, and that the amount of dopamine released correlates with the degree of experienced pleasure. [Copyright &y& Elsevier]

• Combined EEG-fMRI was used to derive fMRI-inspired EEG model of ventral striatum. • To model reward activity, EEG-fMRI data amassed during pleasurable music listening. • The resulting model (termed VS-EFP) predicted VS BOLD activity in a validation sample. • We provide evidence for the specificity and functional validity of the VS-EFP model. • VS-EFP may allow scalable probing of VS reward-related activation for diverse needs. Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music – a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation. [ABSTRACT FROM AUTHOR]

Abstract Parkinson's disease (PD) is a neurodegenerative disorder characterized by a wide array of motor and non-motor symptoms. It remains unclear whether neurodegeneration in discrete loci gives rise to discrete symptoms, or whether network-wide atrophy gives rise to the unique behavioural and clinical profile associated with PD. Here we apply a data-driven strategy to isolate large-scale, multivariate associations between distributed atrophy patterns and clinical phenotypes in PD. In a sample of N = 229 de novo PD patients, we estimate disease-related atrophy using deformation based morphometry (DBM) of T1 weighted MR images. Using partial least squares (PLS), we identify a network of subcortical and cortical regions whose collective atrophy is associated with a clinical phenotype encompassing motor and non-motor features. Despite the relatively early stage of the disease in the sample, the atrophy pattern encompassed lower brainstem, substantia nigra, basal ganglia and cortical areas, consistent with the Braak hypothesis. In addition, individual variation in this putative atrophy network predicted longitudinal clinical progression in both motor and non-motor symptoms. Altogether, these results demonstrate a pleiotropic mapping between neurodegeneration and the clinical manifestations of PD, and that this mapping can be detected even in de novo patients. Highlights • We apply deformation based morphometry to a large sample of MRI from Parkinson's Disease (PD) patients. • We use partial least squares (PLS) to identify a brain signature of PD disease severity. • The atrophy pattern in de novo patients predicts motor and cognitive disease progression. [ABSTRACT FROM AUTHOR]

Across age groups, differences in connectivity of the mesolimbic and the prefrontal cortex co-vary with trait impulsivity and sensation-seeking. Impulsivity and sensation-seeking are also known to increase during early adolescence as maturation of subcortical structures outpaces that of the prefrontal cortex. While an imbalance between the striatum and prefrontal cortex is considered a normal developmental process, higher levels of adolescent impulsivity and sensation-seeking are associated with an increased risk for diverse problems, including obesity. To determine how the relationship between sensation-seeking, impulsivity and body mass index (BMI) is related to shared neural correlates we measured their relationships with the connectivity of nuclei in the striatum and dopaminergic midbrain in young adolescents. Data were collected from 116 children between the ages of 12 and 14, and included resting state functional magnetic resonance imaging, personality measures from the Substance Use Risk Profile Scale, and BMI Z-score for age. The shared variance for the connectivity of regions of interest in the substantia nigra, ventral tegmental area, ventral striatum and sub-thalamic nucleus, personality measures and BMI Z-score for age, were analyzed using partial least squares correlation. This analysis identified a single significant striato-limbic network that was connected with the substantia nigra, ventral tegmental area and sub-thalamic nuclei (p = 0.002). Connectivity within this network which included the hippocampi, amygdalae, parahippocampal gyri and the regions of interest, correlated positively with impulsivity and BMI Z-score for age and negatively with sensation-seeking. Together, these findings emphasize that, in addition to the well-established role that frontostriatal circuits play in the development of adolescent personality traits, connectivity of limbic regions with the striatum and midbrain also impact impulsivity, sensation-seeking and BMI Z-score in adolescents. [ABSTRACT FROM AUTHOR]

Psychosocial stress is associated with an increased intake of palatable foods and weight gain in stress-reactive individuals. Personality traits have been shown to predict stress-reactivity. However, it is not known if personality traits influence brain activity in regions implicated in appetite control during psychosocial stress. The current study assessed whether Gray's Behavioural Inhibition System (BIS) scale, a measure of stress-reactivity, was related to the activity of brain regions implicated in appetite control during a stressful period. Twenty-two undergraduate students participated in a functional magnetic resonance imaging (fMRI) experiment once during a non-exam period and once during final exams in a counter-balanced order. In the scanner, they viewed food and scenery pictures. In the exam compared with the non-exam condition, BIS scores related to increased perceived stress and correlated with increased blood-oxygen-level dependent (BOLD) response to high-calorie food images in regions implicated in food reward and subjective value, such as the ventromedial prefrontal cortex, (vmPFC) and the amygdala. BIS scores negatively related to the functional connectivity between the vmPFC and the dorsolateral prefrontal cortex. The results demonstrate that the BIS trait influences stress reactivity. This is observed both as an increased activity in brain regions implicated in computing the value of food cues and decreased connectivity of these regions to prefrontal regions implicated in self-control. This suggests that the effects of real life stress on appetitive brain function and self-control is modulated by a personality trait. This may help to explain why stressful periods can lead to overeating in vulnerable individuals. [ABSTRACT FROM AUTHOR]

• We correlate gene expression and protein density for 27 receptors and transporters • Only 5HT1a, CB1, D2, and MOR show consistent expression-density correspondence • Expression-density associations are related to population variance • We replicate results using PET, autoradiography, microarray, and RNAseq data • We recommend being cautious when substituting gene expression for receptor density Neurotransmitter receptors modulate signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression measuring mRNA transcripts is often used as a proxy for receptor densities. In the present report, we comprehensively test the spatial correlation between gene expression and protein density for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography radioligand-based imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT 1 A , CB 1 , D 2 , and MOR). These expression-density associations are related to gene differential stability and can vary between cortical and subcortical structures. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function. [ABSTRACT FROM AUTHOR]

Individuals living with obesity tend to have increased brain age, reflecting poorer brain health likely due to grey and white matter atrophy related to obesity. However, it is unclear if older brain age associated with obesity can be reversed following weight loss and cardiometabolic health improvement. The aim of this study was to assess the impact of weight loss and cardiometabolic improvement following bariatric surgery on brain health, as measured by change in brain age estimated based on voxel-based morphometry (VBM) measurements. We used three distinct datasets to perform this study: 1) CamCAN dataset to train the brain age prediction model, 2) Human Connectome Project (HCP) dataset to investigate whether individuals with obesity have greater brain age than individuals with normal weight, and 3) pre-surgery, as well as 4, 12, and 24 month post-surgery data from participants (n = 87, age: 44.0 ± 9.2 years, BMI: 43.9 ± 4.2 kg/m2) who underwent a bariatric surgery to investigate whether weight loss and cardiometabolic improvement as a result of bariatric surgery lowers the brain age. As expected, our results from the HCP dataset showed a higher brain age for individuals with obesity compared to individuals with normal weight (T-value = 7.08, p-value < 0.0001). We also found significant improvement in brain health, indicated by a decrease of 2.9 and 5.6 years in adjusted delta age at 12 and 24 months following bariatric surgery compared to baseline (p-value < 0.0005 for both). While the overall effect seemed to be driven by a global change across all brain regions and not from a specific region, our exploratory analysis showed lower delta age in certain brain regions (mainly in somatomotor, visual, and ventral attention networks) at 24 months. This reduced age was also associated with post-surgery improvements in BMI, systolic/diastolic blood pressure, and HOMA-IR (T-value BMI =4.29, T-value SBP =4.67, T-value DBP =4.12, T-value HOMA-IR =3.16, all p-values < 0.05). In conclusion, these results suggest that obesity-related brain health abnormalities (as measured by delta age) might be reversed by bariatric surgery-induced weight loss and widespread improvements in cardiometabolic alterations. [ABSTRACT FROM AUTHOR]

Research on eating behaviour has identified several potentially relevant eating-related traits captured by different questionnaires. Often, these questionnaires predict Body Mass Index (BMI), but the relationship between them has not been explicitly studied. We studied the unity and diversity of questionnaires capturing five common eating-related traits: Power of Food, Eating Impulsivity, emotional eating, Disinhibition, and binge eating in women from Estonia (n = 740) and Canada (n = 456). Using bifactor analysis, we showed that a) these questionnaires are largely explained by a single factor, and b) relative to this shared factor, only some questionnaires offered additional variance in predicting BMI. Hence, these questionnaires seemed to characterise a common factor, which we label Uncontrolled Eating. Item Response Theory techniques were then applied to demonstrate that c) within this common factor, the questionnaires could be placed on a continuum of Uncontrolled Eating. That is, Eating Impulsivity focused on the milder degree, Power of Food Scale, emotional eating scales, and Disinhibition on intermediate degrees, and the Binge Eating Scale on the most severe degrees of Uncontrolled Eating. In sum, evidence from two samples showed that questionnaires capturing five common BMI-related traits largely reflected the same underlying latent trait – Uncontrolled Eating. In Estonia, some questionnaires focused on different severities of this common construct, supporting a continuum model of Uncontrolled Eating. These findings provide a starting point for developing better questionnaires of the neurobehavioural correlates of obesity, and provide a unifying perspective from which to view the existing literature. R scripts and data used for the analysis are provided. [ABSTRACT FROM AUTHOR]

The extent to which we learn from positive and negative outcomes of decisions is modulated by the neurotransmitter dopamine. Dopamine neurons burst fire in response to unexpected rewards and pause following negative outcomes. This dual signaling mechanism is hypothesized to drive both approach and avoidance behavior. Here we test a prediction deriving from a computational reinforcement learning model, in which approach is mediated via activation of the direct cortico-striatal pathway due to striatal D1 receptor stimulation, while avoidance occurs via disinhibition of indirect pathway striatal neurons secondary to a reduction of D2 receptor stimulation. Using positron emission tomography with two separate radioligands, we demonstrate that individual differences in human approach and avoidance learning are predicted by variability in striatal D1 and D2 receptor binding, respectively. Moreover, transient dopamine precursor depletion improved learning from negative outcomes. These findings support a bidirectional modulatory role for striatal dopamine in reward and avoidance learning via segregated D1 and D2 cortico-striatal pathways. [ABSTRACT FROM AUTHOR]

Metabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables. The study included 57 participants with severe obesity (mean BMI=43.1 ± 4.3 kg/m2) who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N = 36), 12 months (N = 29), and 24 months (N = 14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N = 46) or severe obesity (N = 46). We found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks. Bariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery. [ABSTRACT FROM AUTHOR]

Abstract: Smoking cues trigger craving for cigarettes and relapse. Nicotine metabolism, mediated by the enzyme CYP2A6, also influences smoking behavior. In this study, we investigated how nicotine metabolism and genetic variation in CYP2A6 influence the neural response to smoking cues in humans using functional magnetic resonance imaging (fMRI). We hypothesized that individuals with faster rates of nicotine metabolism would have stronger conditioned responses to smoking cues because of closer coupling in everyday life between exposure to cigarettes and surges in blood nicotine concentration. In contrast, individuals with reduced rates of metabolism, who have relatively constant nicotine blood levels throughout the day, should be less likely to develop conditioned responses to cues. We screened 169 smokers for their rate of nicotine metabolism and CYP2A6 genotype, and selected 31 smokers with the fastest and slowest rates for fMRI, matched for daily cigarette intake. We measured their neural response to visual smoking and non-smoking cues using fMRI. As predicted, fast metabolizers, by phenotype or genotype, had significantly greater responses to visual cigarette cues than slow metabolizers in the amygdala, hippocampus, striatum, insula, and cingulate cortex. These results support the theory that drug cues are conditioned stimuli, and explain why fast metabolizers who smoke have lower cessation rates. They also provide insight into how genetics can shape human vulnerability to addiction, and have implications for tailoring smoking cessation programs based on individual genetics. [Copyright &y& Elsevier]

In multiple sclerosis (MS), the correlation between disability and the volume of white matter lesions on magnetic resonance imaging (MRI) is usually weak. This may be because lesion location also influences the extent and type of functional disability. We applied an automatic lesion-detection algorithm to 452 MRI scans of patients with relapsing-remitting MS to identify the regions preferentially responsible for different types of clinical deficits. Statistical parametric maps were generated by performing voxel-wise linear regressions between lesion probability and different clinical disability scores. There was a clear distinction between lesion locations causing physical and cognitive disability. Lesion likelihood correlated with the Expanded Disability Status Scale (EDSS) in the left internal capsule and in periventricular white matter mostly in the left hemisphere. Pyramidal deficits correlated with only one area in the left internal capsule that was also present in the EDSS correlation. Cognitive dysfunction correlated with lesion location at the grey-white junction of associative, limbic, and prefrontal cortex. Coordination impairment correlated with areas in interhemispheric and pyramidal periventricular white matter tracts, and in the inferior and superior longitudinal fascicles. Bowel and bladder scores correlated with lesions in the medial frontal lobes, cerebellum, insula, dorsal midbrain, and pons, areas known to be involved in the control of micturition. This study demonstrates for the first time a relationship between the site of lesions and the type of disability in large scale MRI data set in MS. [Copyright &y& Elsevier]

MRI studies show that obese adults have reduced grey matter (GM) and white matter (WM) tissue density as well as altered WM integrity. Bariatric surgery can lead to substantial weight loss and improvements in metabolic parameters, but it remains to be examined if it induces structural brain changes. The aim of this study was to characterize GM and WM density changes measured with MRI in a longitudinal setting following sleeve gastrectomy, and to determine whether any changes are related to inflammation and cardiometabolic blood markers. 29 participants with obesity (age: 45.9 ​± ​7.8 years) scheduled to undergo sleeve gastrectomy were recruited. High-resolution T1-weighted anatomical images were acquired 1 month prior to as well as 4 and 12 months after surgery. GM and WM densities were quantified using voxel-based morphometry (VBM). Circulating lipid profile, glucose, insulin and inflammatory markers (interleukin-6, C-reactive protein and lipopolysaccharide-binding protein) were measured at each time point. A linear mixed effect model was used to compare brain changes before and after SG, controlling for age, sex, initial BMI and diabetic status. To assess the associations between changes in adiposity, metabolism and inflammation and changes in GM or WM density, the mean GM and WM densities were extracted across all the participants using atlas-derived regions of interest, and linear mixed-effect models were used. As expected, weight, BMI, waist circumference and neck circumference significantly decreased after SG compared with baseline (p ​< ​0.001 for all). A widespread increase in WM density was observed after surgery, particularly in the cerebellum, brain stem, cerebellar peduncle, cingulum, corpus callosum and corona radiata (p ​< ​0.05, after FDR correction). Significant increases in GM density were observed 4 months after SG compared to baseline in several brain regions such as the bilateral occipital cortex, temporal cortex, postcentral gyrus, cerebellum, hippocampus and insula as well as right fusiform gyrus, right parahippocampal gyrus, right lingual gyrus and right amygdala. These GM and WM increases were more pronounced and widespread after 12 months and were significantly associated with post-operative weight loss and the improvement of metabolic alterations. A linear mixed-effect model also showed associations between post-operative reductions in lipopolysaccharide-binding protein, a marker of inflammation, and increased WM density. To confirm our results, we tested whether the peak of each significant region showed BMI-related differences in an independent dataset (Human Connectome Project). We matched a group of individuals who were severely obese with a group of individuals who were lean for age, sex and ethnicity. Severe obesity was associated with reduced WM density in the brain stem and cerebellar peduncle as well as reduced GM density in cerebellum, regions that significantly changed after surgery (p ​< ​0.01 for all clusters). Bariatric surgery-induced weight loss and improvement in metabolic alterations is associated with widespread increases in WM and GM densities. These post-operative changes overlapped with baseline brain differences between participants who were severely obese and those who were normal-weight in a separate dataset, which may suggest a recovery of WM and GM alterations after bariatric surgery. • Bariatric surgery-induced weight loss was associated with increased WM and GM densities. • These WM and GM increases were related to post-operative metabolic improvements. • Post-operative brain changes lie in brain areas that are relevant for severe obesity. • These results may suggest a recovery of WM and GM alterations after SG. [ABSTRACT FROM AUTHOR]