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Deep brain stimulation (DBS) is an established neuromodulatory intervention against otherwise treatment-refractory obsessive-compulsive disorder (OCD). Several DBS targets, all of which are part of brain networks connecting basal ganglia and prefrontal cortex, alleviate OCD symptoms. Stimulation of these targets is thought to unfold its therapeutic effect by modulation of network activity through internal capsule (IC) connections. Research into DBS-induced network changes and the nature of IC-related effects of DBS in OCD is needed to further improve DBS. Here, we studied the effects of DBS at the ventral medial striatum (VMS) and IC on blood-oxygen level dependent (BOLD) responses in awake rats using functional magnetic resonance imaging (fMRI). BOLD-signal intensity was measured in five regions of interest (ROIs): medial and orbital prefrontal cortex, nucleus accumbens (NAc), IC area, and mediodorsal thalamus. In previous rodent studies, stimulation at both target locations resulted in a reduction of OCD-like behavior and activation of prefrontal cortical areas. Therefore, we hypothesized that stimulation at both targets would result in partially overlapping BOLD responses. Both differential and overlapping activity between VMS and IC stimulation was found. Stimulating the caudal part of the IC resulted in activation around the electrode, while stimulating the rostral part of the IC resulted in increased cross-correlations between the IC area, orbitofrontal cortex, and NAc. Stimulation of the dorsal part of the VMS resulted in increased activity in the IC area, suggesting this area is activated during both VMS and IC stimulation. This activation is also indicative of VMS-DBS impacting corticofugal fibers running through the medial caudate into the anterior IC, and both VMS and IC DBS might act on these fibers to induce OCD-reducing effects. These results show that rodent fMRI with simultaneous electrode stimulation is a promising approach to study the neural mechanisms of DBS. Comparing the effects of DBS in different target areas has the potential to improve our understanding of the neuromodulatory changes that take place across various networks and connections in the brain. Performing this research in animal disease models will lead to translational insights in the mechanisms underlying DBS, and can aid improvement and optimization of DBS in patient populations.

Understanding the neural mechanisms of emotional reactivity in Attention-Deficit/Hyperactivity Disorder (ADHD) may help develop more effective treatments that target emotion dysregulation. In adult ADHD, emotion regulation problems cover a range of dimensions, including emotional reactivity (ER). One important process that could underlie an impaired ER in ADHD might be impaired working memory (WM) processing. We recently demonstrated that taxing WM prior to the exposure of emotionally salient stimuli reduced physiological and subjective reactivity to such cues in heavy drinkers, suggesting lasting effects of WM activation on ER. Here, we investigated neural mechanisms that could underlie the interaction between WM and ER in adult ADHD participants. We included 30 male ADHD participants and 30 matched controls. Participants performed a novel functional magnetic resonance imaging paradigm in which active WM-blocks were alternated with passive blocks of negative and neutral images. We demonstrated group-independent significant main effects of negative emotional images on amygdala activation, and WM-load on paracingulate gyrus and dorsolateral prefrontal cortex activation. Contrary to earlier reports in adolescent ADHD, no impairments were found in neural correlates of WM or ER. Moreover, taxing WM did not alter the neural correlates of ER in either ADHD or control participants. While we did find effects on the amygdala, paCG, and dlPFC activation, we did not find interactions between WM and ER, possibly due to the relatively unimpaired ADHD population and a well-matched control group. Whether targeting WM might be effective in participants with ADHD with severe ER impairments remains to be investigated.

Human brain mapping 43(1), 37-55 (2022). doi:10.1002/hbm.25029 special issue: "Special Issue: The ENIGMA Consortium: the first 10 years / Issue Edited by: P.M. Thompson, N. Jahanshad, L. Schmaal, J.A. Turner, A. Winkler, S.I. Thomopoulos, G.F. Egan, P. Kochunov", Published by Wiley-Liss, New York, NY

Prior studies suggest that methylphenidate, the primary pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD), alters functional brain connectivity. As the neurotransmitter systems targeted by methylphenidate undergo significant alterations throughout development, the effects of methylphenidate on functional connectivity may also be modulated by age. Therefore, we assessed the effects of a single methylphenidate challenge on brain network connectivity in stimulant-treatment naïve children and adults with ADHD. We obtained resting-state functional MRI from 50 boys (10-12 years of age) and 49 men (23-40 years of age) with ADHD (DSM IV, all subtypes), before and after an oral challenge with 0.5 mg/kg methylphenidate; and from 11 boys and 12 men as typically-developing controls. Connectivity strength (CS), eigenvector centrality (EC), and betweenness centrality (BC) were calculated for the striatum, thalamus, dorsal anterior cingulate cortex (dACC), and prefrontal cortex (PFC). In line with our hypotheses, we found that methylphenidate decreased measures of connectivity and centrality in the striatum and thalamus in children with ADHD, but increased the same metrics in adults with ADHD. Surprisingly, we found no major effects of methylphenidate in the dACC and PFC in either children or adults. Interestingly, pre-methylphenidate, participants with ADHD showed aberrant connectivity and centrality compared to controls predominantly in frontal regions. Our findings demonstrate that methylphenidate’s effects on connectivity of subcortical regions are age-dependent in stimulant-treatment naïve ADHD patients, likely due to ongoing maturation of dopamine and noradrenaline systems. These findings highlight the importance for future studies to take a developmental perspective when studying the effects of methylphenidate treatment.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Chemotherapy for non-central nervous system cancers is associated with abnormalities in brain structure and function. Diffusion tensor imaging (DTI) allows for studying in vivo microstructural changes in brain white matter. Tract-based spatial statistics (TBSS) is a widely used processing pipeline in which DTI data are typically normalized to a generic DTI template and then ‘skeletonized’ to compensate for misregistration effects. However, this approach greatly reduces the overall white matter volume that is subjected to statistical analysis, leading to information loss. Here, we present a re-analysis of longitudinal data previously analyzed with standard TBSS (Menning et al., BIB 2018, 324–334). For our current approach, we constructed a pipeline with an optimized registration method in Advanced Normalization Tools (ANTs) where DTI data are registered to a study-specific, high-resolution T1 template and the skeletonization step is omitted. In a head to head comparison, we show that with our novel approach breast cancer survivors who had received chemotherapy plus or minus endocrine therapy (BC + SYST, n = 26) showed a global decline in overall FA that was not present in breast cancer survivors who did not receive systemic therapy (BC-SYST, n = 23) or women without a cancer diagnosis (no cancer controls, NC, n = 30). With the standard TBSS approach we did not find any group differences. Moreover, voxel-based analysis for our novel pipeline showed a widespread decline in FA in the BC + SYST compared to the NC group. Interestingly, the BC-SYST group also showed a decline in FA compared to the NC group, although in much less voxels. These results were not found with the standard TBSS approach. We demonstrate that a modified processing pipeline makes DTI data more sensitive to detecting changes in white matter integrity in non-CNS cancer patients after treatment, particularly chemotherapy.

Methylphenidate (MPH) is the first-choice pharmacological treatment for treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) across the lifespan. However, it is unclear whether MPH affects cognitive development, while recent (pre-) clinical studies suggest effects on the developing brain. The present randomized, placebo-controlled trial aims to determine whether MPH has short-term, age-dependent effects on cognitive performance in ADHD after a 1-week washout. Effects of 16 weeks MPH treatment were assessed after a one-week washout on cognitive functioning. Boys (age=10-12) and men (age=23-40) with ADHD were assigned to MPH treatment (boys n=25, men n=24) or placebo (boys n=25, men n=24). Outcome measures were working memory, response inhibition, response speed, episodic memory, and delay aversion. Differences in task performances over time (pre-, mid-, and post-treatment, following a 1-week wash-out) were compared between age and treatment conditions with mixed ANOVAs. MPH improved working memory and response speed, but only during treatment. No lasting age*treatment effects were observed post intervention. Overall, the results from the present randomized, placebo-controlled trial show that the effects of MPH on cognition do not extend past treatment in children or adults. While treatment with MPH improves cognition during treatment, these effects appear transient after 16-weeks of treatment. (Title trial: "Effects of methylphenidate on the developing brain"; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3103).

BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset.MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain predicted age difference (brain-PAD).FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohen’s d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004).InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates.FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.

Contains fulltext : 219494.pdf (Publisher’s version ) (Closed access) While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics - the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD) - that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures. 15 p.

Background: Radiomics in neuroimaging uses fully automatic segmentation to delineate the anatomical areas for which radiomic features are computed. However, differences among these segmentation methods affect radiomic features to an unknown extent.Method: A scan-rescan dataset (n=46) of T1-weighted and diffusion tensor images was used. Subjects were split into a sleep-deprivation and a control group. Scans were segmented using four segmentation methods from which radiomic features were computed. First, we measured segmentation agreement using the Dice-coefficient. Second, robustness and reproducibility of radiomic features were measured using the intraclass correlation coefficient (ICC). Last, difference in predictive power was assessed using the Friedman-test on performance in a radiomics-based sleep deprivation classification application.Results: Segmentation agreement was generally high (interquartile range=0.77-0.90) and median feature robustness to segmentation method variation was higher (ICC>0.7) than scan-rescan reproducibility (ICC 0.3-0.8). However, classification performance differed significantly among segmentation methods (pConclusion: Despite high agreement among segmentation methods, subtle differences significantly affected radiomic features and their predictive power. Consequently, the effect of differences in segmentation methods should be taken into account when designing and evaluating radiomics-based research methods.

Background and ObjectivesDespite effective combination antiretroviral therapy (cART), adolescents with perinatally acquired HIV (PHIV) exhibit cognitive impairment, of which structural changes could be the underlying pathophysiologic mechanism. Prior MRI studies found lower brain volumes, higher white matter (WM) hyperintensity (WMH) volume, lower WM integrity, and differences in cerebral blood flow (CBF). However, these findings may be confounded by adoption status, as a large portion of adolescents with PHIV have been adopted. Adoption has been associated with malnutrition and neglect, which, in turn, may have affected brain development. We investigated the long-term effects of PHIV on the brain, while minimizing the confounding effect of adoption status.MethodsWe determined whole-brain gray matter (GM) and WM volume with 3D T1-weighted scans; total WMH volume with fluid-attenuated inversion recovery; CBF in the following regions of interest (ROIs): WM, GM, and subcortical GM with arterial spin labeling; and whole-brain WM microstructural markers: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) with diffusion tensor imaging in cART-treated adolescents with PHIV visiting our outpatient clinic in Amsterdam and controls matched for age, sex, ethnic origin, socioeconomic status, and adoption status. We assessed differences in neuroimaging parameters between adolescents with PHIV and controls using linear regression models adjusted for age and sex and applied multiple comparison correction.ResultsThirty-five adolescents with PHIV and 38 controls were included with a median age of 14.9 (interquartile range [IQR]: 10.7–18.5) and 15.6 (IQR: 11.1–17.6) years, respectively, with a similar rate of adoption. We found a lower overall FA (beta = −0.012; p < 0.014, −2.4%), a higher MD (beta = 0.014, p = 0.014, 1.3%), and a higher RD (beta = 0.02, p = 0.014, 3.3%) in adolescents with PHIV vs adoption-matched controls, but no differences in AD. We found comparable GM, WM, and WMH volume and CBF in ROIs between adolescents with PHIV and controls. We did not find an association between cognitive profiles and WM microstructural markers in adolescents with PHIV.DiscussionIrrespective of adoption status, adolescents with PHIV exhibited subtle lower WM integrity. Our findings may point toward early-acquired WM microstructural alterations associated with HIV.

BACKGROUND AND PURPOSE: Although methylphenidate is frequently used to treat children with attention-deficit/hyperactivity disorder, it is currently unknown how methylphenidate affects brain development. In a randomized controlled trial, we investigated whether the cortical effects of methylphenidate are modulated by age. MATERIALS AND METHODS: Between June 1, 2011, and June 15, 2015, we conducted a randomized, double-blind, placebo-controlled trial (Effects of Psychotropic Drugs on Developing Brain-Methylphenidate) in 99 males with attention-deficit/hyperactivity disorder (according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, criteria) from referral centers in the greater Amsterdam area in the Netherlands. The trial was registered on March 24, 2011 (identifier NL34509.000.10) and subsequently at the Netherlands National Trial Register (identifier NTR3103). Participants (first enrolled October 13, 2011) were 10–12 years or 23–40 years of age and randomized to treatment with either methylphenidate or a placebo for 16 weeks. Our main outcome was a change in cortical thickness in predefined ROIs as measured by MR imaging pre- and posttreatment. RESULTS: We observed a time × medication × age interaction (F[1,88.825] = 4.316, P

BackgroundMethylphenidate (MPH) is highly effective in treating attention-deficit/hyperactivity disorder (ADHD). However, not much is known about its effect on the development of human brain white matter (WM).PurposeTo determine whether MPH modulates WM microstructure in an age-dependent fashion in a randomized double-blind placebo-controlled trial (Effects of Psychotropic Medication on Brain Development-Methylphenidate, or ePOD-MPH) among ADHD referral centers between October 13, 2011, and June 15, 2015, by using diffusion-tensor imaging (DTI).Materials and MethodsIn this prospective study (NTR3103 and NL34509.000.10), 50 stimulant treatment-naive boys and 49 young adult men diagnosed with ADHD (all types) according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition criteria were randomized to undergo treatment with MPH or placebo for 16 weeks. Before and 1 week after treatment cessation, study participants underwent MRI, including DTI. The outcome measure was change in fractional anisotropy (FA), which was assessed in three regions of interest (ROIs), as well as in a voxel-based analysis in brain WM. Data were analyzed by using intention-to-treat linear mixed models for ROI analysis and a permutation-based method for voxel-based analysis with family-wise error correction.ResultsFifty boys (n = 25 MPH group, n = 25 placebo group; age range, 10-12 years) and 48 men (n = 24 MPH group, n = 24 placebo group; age range, 23-40 years) were included. ROI analysis of FA yielded no main effect of time in any of the conditions. However, voxel-based analysis revealed significant (P < .05) time-by-medication-by-age interaction effects in several association tracts of the left hemisphere, as well as in the lateral aspect of the truncus of the corpus callosum, due to greater increase in FA (standardized effect size, 5.25) in MPH-treated boys. Similar changes were not present in boys receiving a placebo, nor in adult men.ConclusionFour months of treatment with methylphenidate affects specific tracts in brain white matter in boys with attention-deficit/hyperactivity disorder. These effects seem to be age dependent, because they were not observed in adults treated with methylphenidate.© RSNA, 2019Online supplemental material is available for this article.

PURPOSE Cognitive decline is frequently observed after chemotherapy. As chemotherapy is associated with changes in brain white matter microstructure, we investigated whether white matter microstructure before chemotherapy is a risk factor for cognitive decline after chemotherapy. METHODS Neuropsychologic tests were administered before and 6 months (n = 49), 2 years (n = 32), and 3 years (n = 32) after chemotherapy in patients with breast cancer receiving anthracycline-based chemotherapy (BC + CT group), at matched intervals to patients with BC who did not receive systemic therapy (BC – CT group: n = 39, 23, and 19, respectively) and to no-cancer controls (NC group: n = 37, 29, and 28, respectively). Using multivariate normative comparison, we evaluated to what extent the cognitive profiles of patients deviated from those of controls. Fractional anisotropy (FA), derived from magnetic resonance diffusion tensor imaging, was used to measure white matter microstructure before treatment. FA was evaluated as a risk factor for cognitive decline, in addition to baseline age, fatigue, cognitive complaints, and premorbid intelligence quotient. We subsequently ran voxel-wise diffusion tensor imaging analyses to investigate white matter microstructure in specific nerve tracts. RESULTS Low FA independently predicted cognitive decline early (6 months, P = .013) and late (3 years, P < .001) after chemotherapy. FA did not predict cognitive decline in the BC – CT and NC groups. Voxel-wise analysis indicated involvement of white matter tracts essential for cognitive functioning. CONCLUSION Low FA may reflect low white matter reserve. This may be a risk factor for cognitive decline after chemotherapy for BC. If validated in future trials, identification of patients with low white matter reserve could improve patient care, for example, by facilitating targeted, early interventions or even by influencing choices of patients and doctors for receiving chemotherapy.

Objective Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. Methods We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. Results There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from −0.18 to 0.18) and would not survive study-wide correction for multiple testing. Conclusion Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait., Journal of Child Psychology and Psychiatry, 62 (10), ISSN:0021-9630, ISSN:1469-7610

Understanding the neural mechanisms of emotional reactivity in Attention-Deficit/Hyperactivity Disorder (ADHD) may help develop more effective treatments that target emotion dysregulation. In adult ADHD, emotion regulation problems cover a range of dimensions, including emotional reactivity (ER). One important process that could underlie an impaired ER in ADHD might be impaired working memory (WM) processing. We recently demonstrated that taxing WM prior to the exposure of emotionally salient stimuli reduced physiological and subjective reactivity to such cues in heavy drinkers, suggesting lasting effects of WM activation on ER. Here, we investigated neural mechanisms that could underlie the interaction between WM and ER in adult ADHD participants. We included 30 male ADHD participants and 30 matched controls. Participants performed a novel functional magnetic resonance imaging paradigm in which active WM-blocks were alternated with passive blocks of negative and neutral images. We demonstrated group-independent significant main effects of negative emotional images on amygdala activation, and WM-load on paracingulate gyrus and dorsolateral prefrontal cortex activation. Contrary to earlier reports in adolescent ADHD, no impairments were found in neural correlates of WM or ER. Moreover, taxing WM did not alter the neural correlates of ER in either ADHD or control participants. While we did find effects on the amygdala, paCG, and dlPFC activation, we did not find interactions between WM and ER, possibly due to the relatively unimpaired ADHD population and a well-matched control group. Whether targeting WM might be effective in participants with ADHD with severe ER impairments remains to be investigated.

The dopamine system in the brain is involved in a variety of neurologic and psychiatric disorders, such as Parkinson's disease, attention-deficit/hyperactivity disorder and psychosis. Different aspects of the dopamine system can be visualized and measured with positron emission tomography (PET) and single photon emission computed tomography (SPECT), including dopamine receptors, dopamine transporters, and dopamine release. New developments in MR imaging also provide proxy measures of the dopamine system in the brain, offering alternatives with the advantages MR imaging, i.e. no radiation, lower costs, usually less invasive and time consuming. This review will give an overview of these developments with a focus on the most developed techniques: pharmacological MRI (phMRI) and neuromelanin sensitive MRI (NM-MRI). PhMRI is a collective term for functional MRI techniques that administer a pharmacological challenge to assess its effects on brain hemodynamics. By doing so, it indirectly assesses brain neurotransmitter function such as dopamine function. NM-MRI is an upcoming MRI technique that enables in vivo visualization and semi-quantification of neuromelanin in the substantia nigra. Neuromelanin is located in the cell bodies of dopaminergic neurons of the nigrostriatal pathway and can be used as a proxy measure for long term dopamine function or degeneration of dopaminergic neurons. Both techniques are still primarily used in clinical research, but there is promise for clinical application, in particular for NM-MRI in dopaminergic neurodegenerative diseases like Parkinson's disease.

Executive functioning is a higher-order cognitive process that is thought to depend on a brain network organization facilitating network integration across specialized subnetworks. The frontoparietal network (FPN), a subnetwork that has diverse connections to other brain modules, seems pivotal to this integration, and a more central role of regions in the FPN has been related to better executive functioning. Brain networks can be constructed using different modalities: diffusion MRI (dMRI) can be used to reconstruct structural networks, while resting-state fMRI (rsfMRI) and magnetoencephalography (MEG) yield functional networks. These networks are often studied in a unimodal way, which cannot capture potential complementary or synergistic modal information. The multilayer framework is a relatively new approach that allows for the integration of different modalities into one ‘network of networks’. It has already yielded promising results in the field of neuroscience, having been related to e.g. cognitive dysfunction in Alzheimer’s disease. Multilayer analyses thus have the potential to help us better understand the relation between brain network organization and executive functioning. Here, we hypothesized a positive association between centrality of the FPN and executive functioning, and we expected that multimodal multilayer centrality would supersede unilayer centrality in explaining executive functioning. We used dMRI, rsfMRI, MEG, and neuropsychological data obtained from 33 healthy adults (age range 22-70 years) to construct eight modality-specific unilayer networks (dMRI, fMRI, and six MEG frequency bands), as well as a multilayer network comprising all unilayer networks. Interlayer links in the multilayer network were present only between a node’s counterpart across layers. We then computed and averaged eigenvector centrality of the nodes within the FPN for every uni- and multilayer network and used multiple regression models to examine the relation between uni- or multilayer centrality and executive functioning. We found that higher multilayer FPN centrality, but not unilayer FPN centrality, was related to better executive functioning. To further validate multilayer FPN centrality as a relevant measure, we assessed its relation with age. Network organization has been shown to change across the life span, becoming increasingly efficient up to middle age and regressing to a more segregated topology at higher age. Indeed, the relation between age and multilayer centrality followed an inverted-U shape. These results show the importance of FPN integration for executive functioning as well as the value of a multilayer framework in network analyses of the brain. Multilayer network analysis may particularly advance our understanding of the interplay between different brain network aspects in clinical populations, where network alterations differ across modalities.Highlights:Multimodal neuroimaging and neurophysiology data were collected in healthy adultsMultilayer frontoparietal centrality was positively associated with executive functioningUnilayer (unimodal) centralities were not associated with executive functioningThere was an inverted-U relationship between multilayer centrality and age

Background Pontocerebellar hypoplasia (PCH) is a rare group of disorders mainly affecting the cerebellum and pons. Supratentorial structures are variably involved. We assessed brain growth patterns in patients with the most frequent forms of PCH, namely PCH1B (OMIM#614678) and PCH2A (OMIM#277470), since in these types of PCH, pre- and postnatal neurodegeneration is established by neuropathological profiling. To assess the influence of the different pathomechanisms on postnatal growth patterns, we included CASK-associated microcephaly and PCH (MICPCH, OMIM#300749) patients in our analyses, as MICPH mimics PCH on magnetic resonance imaging (MRI) but represents a developmental disorder including abnormal neuronal migration. Methods A total of 66 patients were included: 9 patients with PCH1B, 18 patients with PCH2A, 6 patients with MICPCH, and 33 age- and gender-matched hospital-based controls. Segmentation of the vermis and cerebellum was performed manually, as were measurements of the thickness of the head of the caudate nucleus, the width of the anterior horn, and lateral ventricle size. Results The cerebellum was severely hypoplastic at birth in all patients, and postnatal growth was nearly absent. In patients with PCH1B/2A, we found relative sparing of the vermis compared with the cerebellar hemispheres. In addition, PCH1B and PCH2A cases demonstrated thinning of the head of the caudate nucleus, an associated increase in anterior horn width, and an increase in lateral ventricle size. None of these features were seen in the MICPCH group. Conclusions Our findings confirm the progressive nature including caudate nucleus atrophy in PCH1B and PCH2A. In MICPCH, the relative sparing of supratentorial structures confirms its different pathomechanism.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Contains fulltext : 243961.pdf (Publisher’s version ) (Closed access) Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice.ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.