FreeSurfer cortical normative data for adults using Desikan-Killiany-Tourville and ex vivo protocols

We recently built normative data for FreeSurfer morphometric estimates of cortical regions using its default atlas parcellation (Desikan-Killiany or DK) according to individual and scanner characteristics. We aimed to produced similar normative values for Desikan-Killianny-Tourville (DKT) and ex vivo-based labeling protocols, as well as examine the differences between these three atlases. Surfaces, thicknesses, and volumes of cortical regions were produced using cross-sectional magnetic resonance scans from the same 2713 healthy individuals aged 18 to 94 years as used in the reported DK norms. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated intracranial volume (eTIV), scanner manufacturer and magnetic field strength (MFS) as predictors. The DKT and DK models generally included the same predictors and produced similar R2. Comparison between DK, DKT, ex vivo atlases normative cortical measures showed that the three protocols generally produced similar normative values

Measurement variability following MRI system upgrade

Major hardware/software changes to MRI platforms, either planned or unplanned, will almost invariably occur in longitudinal studies. Our objective was to assess the resulting variability on relevant imaging measurements in such context, specifically for three Siemens Healthcare Magnetom Trio upgrades to the Prismafit platform. We report data acquired on three healthy volunteers scanned before and after three different platform upgrades. We assessed differences in image signal (contrast-to-noise ratio (CNR)) on T1-weighted images (T1w) and fluid-attenuated inversion recovery images (FLAIR); brain morphometry on T1w image; and small vessel disease (white matter hyperintensities; WMH) on FLAIR image. Prismafit upgrade resulted in higher (30%) and more variable neocortical CNR and higher brain volume and thickness mainly in frontal areas. A significant relationship was observed between neocortical CNR and cortical volume. For FLAIR images, no significant CNR difference was observed, but WMH volumes were significantly smaller (-68%) after Prismafit upgrade, when compared to results on the Magnetom Trio. Together, these results indicate that Prismafit upgrade significantly influenced image signal, brain morphometry measures and small vessel diseases measures and that these effects need to be taken into account when analyzing results from any longitudinal study undergoing similar changes

Brain atrophy and patch-based grading in individuals from the CIMA-Q study : a progressive continuum from subjective cognitive decline to AD

It has been proposed that individuals developing Alzheimer’s disease (AD) first experience a phase expressing subjective complaints of cognitive decline (SCD) without objective cognitive impairment. Using magnetic resonance imaging (MRI), our objective was to verify whether SNIPE probability grading, a new MRI analysis technique, would distinguish between clinical dementia stage of AD: Cognitively healthy controls without complaint (CH), SCD, mild cognitive impairment, and AD. SNIPE score in the hippocampus and entorhinal cortex was applied to anatomical T1-weighted MRI of 143 participants from the Consortium pour l’identification précoce de la maladie Alzheimer - Québec (CIMA-Q) study and compared to standard atrophy measures (volumes and cortical thicknesses). Compared to standard atrophy measures, SNIPE score appeared more sensitive to differentiate clinical AD since differences between groups reached a higher level of significance and larger effect sizes. However, no significant difference was observed between SCD and CH groups. Combining both types of measures did not improve between-group differences. Further studies using a combination of biomarkers beyond anatomical MRI might be needed to identify individuals with SCD who are on the beginning of the clinical continuum of AD

Brain atrophy and patch-based grading in individuals from the CIMA-Q study : a progressive continuum from subjective cognitive decline to AD

It has been proposed that individuals developing Alzheimer's disease (AD) first experience a phase expressing subjective complaints of cognitive decline (SCD) without objective cognitive impairment. Using magnetic resonance imaging (MRI), our objective was to verify whether SNIPE probability grading, a new MRI analysis technique, would distinguish between clinical dementia stage of AD: Cognitively healthy controls without complaint (CH), SCD, mild cognitive impairment, and AD. SNIPE score in the hippocampus and entorhinal cortex was applied to anatomical T1-weighted MRI of 143 participants from the Consortium pour l’identification précoce de la maladie Alzheimer -Québec (CIMA-Q) study and compared to standard atrophy measures (volumes and cortical thicknesses). Compared to standard atrophy measures, SNIPE score appeared more sensitive to differentiate clinical AD since differences between groups reached a higher level of significance and larger effect sizes. However, no significant difference was observed between SCD and CH groups. Combining both types of measures did not improve between-group differences. Further studies using a combination of biomarkers beyond anatomical MRI might be needed to identify individuals with SCD who are on the beginning of the clinical continuum of AD

Morphometric analysis of structural MRI using schizophrenia meta-analytic priors distinguish patients from controls in two independent samples and in a sample of individuals with high polygenic risk

Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen’s d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (N(CASE) = 50; N(CONTROL) = 125), a replication sample (N(CASE) = 23; N(CONTROL) = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (N(HIGH-SCZ-PRS) = 95; N(LOW-SCZ-PRS) = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual’s patterns of structural brain-wide alterations

Alzheimer's genetic risk effects on cerebral blood flow are spatially consistent and proximal to gene expression across the lifespan

Cerebrovascular dysregulation is a hallmark feature of Alzheimer’s disease (AD), where alterations in cerebral blood flow (CBF) are observed decades prior to symptom onset. Genome-wide association studies (GWAS) show that AD has a polygenic aetiology, providing a tool for studying AD susceptibility across the lifespan. Here, we ascertain whether AD genetic risk effects on CBF previously observed (Chandler et al., 2019) remain consistent across the lifespan. We further provide a causal mechanism to AD genetic risk scores (AD-GRS) effects by establishing spatial convergence between AD-GRS associated regional reductions in CBF and mRNA expression of the proximal AD transcripts using independent data from the Allen Brain Atlas. We analysed grey matter (GM) CBF in a young cohort (N=75; aged 18-35) and an older cohort (N=90; aged 55-85). Critically, we observed that AD-GRS was negatively associated with whole brain GM CBF in the older cohort (standardised β −0.38 [−0.68 – −0.09], P = 0.012), consistent with our prior observation in younger healthy adults (Chandler et al., 2019). We then demonstrate that the regional impact of AD-GRS on GM CBF was spatially consistent across the younger and older samples (r = 0.233, P = 0.035). Finally, we show that CBF across the cortex was related to the regional expression of the genes proximal to SNP’s used to estimate AD-GRS in both younger and older cohorts (ZTWO-TAILED = −1.99, P= 0.047; ZTWO-TAILED = −2.153 P = 0.032, respectively). These observations collectively demonstrate that AD risk alleles have a negative influence on brain vascular function and likely contribute to cerebrovascular changes preceding the onset of clinical symptoms, potentially driven by regional expression of proximal AD risk genes across the brain. Our observations suggest that reduced CBF is an early antecedent of AD and a key modifiable target for therapeutic intervention in individuals with a higher cumulative genetic risk for AD. This study will further enable identification of key molecular processes that underpin AD genetic risk related reductions in CBF that could be targeted decades prior to the onset of neurodegeneration

Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks

Normative aging and Alzheimer’s disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56–65, 66–75, and 71–85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD

Towards a Unified Analysis of Brain Maturation and Aging across the Entire Lifespan: A MRI Analysis

"This is the peer reviewed version of the following article: Coupé, Pierrick, Gwenaelle Catheline, Enrique Lanuza, and José Vicente Manjón. 2017. Towards a Unified Analysis of Brain Maturation and Aging across the Entire Lifespan: A MRI Analysis. Human Brain Mapping 38 (11). Wiley: 5501 18. doi:10.1002/hbm.23743, which has been published in final form at https://doi.org/10.1002/hbm.23743. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] There is no consensus in literature about lifespan brain maturation and senescence, mainly because previous lifespan studies have been performed on restricted age periods and/or with a limited number of scans, making results instable and their comparison very difficult. Moreover, the use of nonharmonized tools and different volumetric measurements lead to a great discrepancy in reported results. Thanks to the new paradigm of BigData sharing in neuroimaging and the last advances in image processing enabling to process baby as well as elderly scans with the same tool, new insights on brain maturation and aging can be obtained. This study presents brain volume trajectory over the entire lifespan using the largest age range to date (from few months of life to elderly) and one of the largest number of subjects (N=2,944). First, we found that white matter trajectory based on absolute and normalized volumes follows an inverted U-shape with a maturation peak around middle life. Second, we found that from 1 to 8-10 y there is an absolute gray matter (GM) increase related to body growth followed by a GM decrease. However, when normalized volumes were considered, GM continuously decreases all along the life. Finally, we found that this observation holds for almost all the considered subcortical structures except for amygdala which is rather stable and hippocampus which exhibits an inverted U-shape with a longer maturation period. By revealing the entire brain trajectory picture, a consensus can be drawn since most of the previously discussed discrepancies can be explained. Hum Brain Mapp 38:5501-5518, 2017. (C) 2017 Wiley Periodicals, Inc.French State (French National Research Ageny in the frame of the Investments for the future Program IdEx Bordeaux); Contract grant number: ANR-10-IDEX-03-02, HL-MRI Project; Contract grant sponsor: Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57); Contract grant sponsor: CNRS ("Defi imag'In and the dedicated volBrain support); Contract grant sponsor: Ministerio de Economia y competitividad (Spanish); Contract grant number: TIN2013-43457-R; Contract grant sponsor: National Institute of Child Health and Human Development; Contract grant number: HHSN275200900018C; Contract grant sponsors: National Institute of Child Health and Human Development, the National Institute on Drug Abuse, the National Institute of Mental Health, and the National Institute of Neurological Disorders and Stroke; Contract grant numbers: N01- HD02-3343, N01-MH9-0002, and N01-NS-9-2314, -2315, -2316, -2317, -2319 and -2320; Contract grant sponsor: National Institutes of Health; Contract grant number: U01 AG024904; Contract grant sponsor: National Institute on Aging and the National Institute of Biomedical Imaging and Bioengineering (ADNI); Contract grant sponsor: NIH; Contract grant number: P30AG010129, K01 AG030514; Contract grant sponsor: Dana Foundation; Contract grant sponsor: OASIS project (OASIS data); Contract grant numbers: P50 AG05681, P01 AG03991, R01 AG021910, P50 MH071616, U24 RR021382, R01 MH56584; Contract grant sponsor: Common-wealth Scientific Industrial Research Organization (a publicly funded government research organization); Contract grant sponsor: Science Industry Endowment Fund, National Health and Medical Research Council of Australia; Contract grant number: 1011689; Contract grant sponsors: Alzheimer's Association, Alzheimer's Drug Discovery Foundation, and an anonymous foundation; Contract grant sponsor: Human Brain Project; Contract grant number: PO1MHO52176-11 (ICBM, P.I. Dr John Mazziotta); Contract grant sponsor: Canadian Institutes of Health Research; Contract grant number: MOP-34996; Contract grant sponsor: U.K. Engineering and Physical Sciences Research Council (EPSRC); Contract grant number: GR/S21533/02; Contract grant sponsor: ABIDE funding resources; Contract grant sponsor: NIMH; Contract grant number: K23MH087770; Contract grant sponsor: Leon Levy Foundation; Contract grant sponsor: NIMH award to MPM; Contract grant number: R03MH096321Coupé, P.; Catheline, G.; Lanuza, E.; Manjón Herrera, JV. (2017). Towards a Unified Analysis of Brain Maturation and Aging across the Entire Lifespan: A MRI Analysis. Human Brain Mapping. 38(11):5501-5518. https://doi.org/10.1002/hbm.23743S550155183811Ashburner, J., & Friston, K. J. (2005). Unified segmentation. NeuroImage, 26(3), 839-851. doi:10.1016/j.neuroimage.2005.02.018Aubert-Broche, B., Fonov, V. S., García-Lorenzo, D., Mouiha, A., Guizard, N., Coupé, P., … Collins, D. L. (2013). 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Neuromorphologische Korrelate dimensionaler schizotyper Persönlichkeitseigenschaften bei Gesunden

Schizotypie beschreibt ein mehrdimensionales Konstrukt, welches sich durch subklinische schizophrenieähnliche Verhaltens- und Denkweisen auszeichnet. Es konnten bisher Überschneidungen zwischen Schizotypie und Schizophrenie unter anderem in der genetischen Prädisposition und der Neuromorphologie detektiert werden. Schizotype Persönlichkeitseigenschaften kommen in unterschiedlichen Ausprägungen in der Bevölkerung vor und bilden ein Kontinuum zwischen einem niedrig-schizotypen und einem hoch-schizotypen bzw. klinischen Bereich. Obwohl sie per se keinen Krankheitswert besitzen, sind sie in ausgeprägter Form ein Risikofaktor für die Entwicklung einer Störung des Schizophrenie-Spektrums. Studien zur Schizotypie bieten die Möglichkeit innerhalb des Kontinuums Unterschiede zu detektieren, die bei vorhandener Disposition Hinweise auf protektive und kompensatorische Faktoren geben können. In dieser Studie wurde untersucht, inwieweit schizotype Persönlichkeitsmerkmale gesunder Probanden mit strukturellen Auffälligkeiten der Neuromorphologie korrelieren. Dazu wurden die schizotypen Eigenschaften von 250 klinisch unauffälligen Personen mit Hilfe des Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE) erhoben und die Korrelationen der einzelnen Unterskalen mit der Hirnstruktur jeweils mittels Voxel-Based Morphometry (VBM), Surface-Based Morphometry (SBM) und Diffusion-Tensor-Imaging (DTI) untersucht. Wir nutzen für die Gewinnung der Daten ein 3Tesla MRT. In allen drei Methoden zeigten sich Zusammenhänge zwischen den einzelnen Unterskalen und der Hirnstruktur. Im Rahmen der VBM-Analyse präsentierten sich Volumenreduktionen in temporalen und frontalen Bereichen, sowie Auffälligkeiten im Bereich der Insula, des Cerebellums und des Praecuneus. Insbesondere die Volumenreduktionen in temporalen Bereichen wurden für klinisch Betroffene vielfach vorbeschrieben, wobei vor allem Reduktionen des Gyrus temporalis superior mit der Positivsymptomatik korrelierten. In der hier untersuchten Kohorte konnten Zusammenhänge mit der positiven Dimension im Bereich des Gyrus temporalis inferior gefunden werden. Im Bereich des Praecuneus zeigten sich negative Volumenkorrelationen, die sich ebenfalls von zuvor publizierten Ergebnissen gesunder Probanden unterscheiden. Des Weiteren zeigte die SBM-Analyse eine verminderte Gyrifizierung in frontalen Bereichen, sowie eine vermehrte Gyrifizierung im Bereich der Insula. Innerhalb der DTI-Analyse präsentierten sich Assoziationen einzelner Dimensionen mit der Faserqualität in frontotemporalen und fronto-subkortikalen Faserzügen, sowie in Strukturen des limbischen Systems. Die Ergebnisse der Studie belegen damit multifokale Zusammenhänge schizotyper Persönlichkeitsmerkmale mit der Hirnstruktur auch bei Gesunden. Diese decken sich nur zum Teil mit bereits publizierten Daten. Ein Erklärungsansatz hierfür ist unter anderem die Verwendung verschiedener Fragebögen. Diese Studie erweitert so den Blick auf das schizotype Kontinuum aus einer klinisch unauffälligen Perspektive und ist ein wichtiger Baustein für das Verständnis neuromorphologischer Zusammenhänge schizotyper Persönlichkeitseigenschaften bei Gesunden

Investigating the neural substrates of gambling disorder using multiple neuromodulation and neuroimaging approaches

Introduction : Le trouble du jeu de hasard et d'argent (GD) est caractérisé par un comportement de jeu inadapté qui interfère avec les activités personnelles ou professionnelles. Ce trouble psychiatrique est difficile à traiter avec les thérapies actuelles et les rechutes sont fréquentes. Les symptômes dépressifs et cognitifs (e.g., l'impulsivité), ainsi que le "craving" (désir intense de jouer) sont des facteurs prédictifs de rechutes. Une meilleure compréhension des substrats neuronaux et leurs significations cliniques pourraient mener au développement de nouveaux traitements. La stimulation transcrânienne à courant direct (tDCS) pourrait être l'un de ceux-ci car elle permet de cibler des circuits neuronaux spécifiques. De plus, la tDCS ciblant le cortex dorsolatéral préfrontal (DLPFC) pourrait améliorer les symptômes dépressifs et cognitifs et réduire le craving. Cependant, les effets précis de la tDCS sur la fonction cérébrale, ainsi que leurs significations cliniques, demeurent à être élucidés. Par ailleurs, étant donné que les patients avec GD présentent souvent des différences morphométriques par rapport aux individus en santé, il est possible de faire l'hypothèse que la morphométrie cérébrale influence les effets de la tDCS. Objectifs : Ce travail avait trois objectifs principaux. Le premier objectif était d'explorer s'il y avait des associations entre les substrats neuronaux et les symptômes cliniques et cognitifs. Le deuxième objectif était d'examiner les effets de la tDCS sur la fonction cérébrale. Le troisième objectif était d'explorer si la morphométrie du site de stimulation (DLPFC) pouvait influencer les effets de la tDCS sur les substrats neuronaux. Méthode : Nous avons réalisé quatre études différentes. Dans la première étude, nous avons mesuré la morphométrie cérébrale en utilisant l'imagerie par résonance magnétique (IRM) structurelle. Nous avons mesuré les corrélations entre la morphométrie et les symptômes cliniques (dépression, sévérité et durée du GD) et cognitifs (impulsivité). De plus, nous avons comparé la morphométrie des patients à celui d'une base de données normative (individus en santé) en contrôlant pour plusieurs facteurs comme l'âge. Dans la deuxième étude, nous avons mesuré la fonction cérébrale (connectivité fonctionnelle) des patients avec l'IRM fonctionnelle. Nous avons examiné s'il y avait des liens entre la connectivité fonctionnelle et les symptômes cognitifs (impulsivité et prise de risque) et cliniques (sévérité et durée du GD). Dans la troisième étude, nous avons étudié les effets de la tDCS sur la connectivité fonctionnelle et si la morphométrie du DLPFC pouvait influencer ces effets. Dernièrement, dans la quatrième étude, nous avons examiné si la morphométrie du DLPFC pouvait influencer les effets de la tDCS sur la neurochimie (avec la spectroscopie par résonance magnétique). Résultats : Nous avons démontré deux corrélations positives entre la superficie du cortex occipital et les symptômes dépressifs (étude I). Nous avons également mis en évidence une corrélation positive entre la connectivité fonctionnelle d'un réseau occipital et l'impulsivité (étude II). De plus, il y avait une corrélation positive entre la connectivité fonctionnelle de ce réseau et la sévérité du GD. Par ailleurs, il y avait des corrélations positives entre la connectivité fonctionnelle de l'opercule frontal droit et la prise de risque (étude II). En outre, la connectivité fonctionnelle d'un réseau cérébelleux était corrélée avec les symptômes dépressifs (étude II). Les patients avaient aussi plusieurs différences morphométriques par rapport aux individus en santé (cortex occipital, préfrontal, etc.). Nous avons démontré également que la tDCS appliquée sur le DLPFC a augmenté la connectivité fonctionnelle d'un réseau fronto-pariétal (étude III). Finalement, cette thèse a montré que la morphométrie du DLPFC influence les augmentations induites par la tDCS sur la connectivité fonctionnelle du réseau fronto-pariétal (étude III) et le niveau de GABA frontal (étude IV). Conclusions : Cette thèse démontre une importance clinique potentielle pour les régions occipitales, frontales et cérébelleuses, particulièrement pour les patients ayant des symptômes dépressifs ou cognitifs. De plus, elle montre que la tDCS peut renforcer le fonctionnement d'un réseau fronto-pariétal connu pour son rôle dans les fonctions exécutives. Il reste à déterminer si un plus grand nombre de sessions pourrait apporter des bénéfices cliniques additionnels afin d'aider les patients à résister le jeu. Finalement, les résultats de cette thèse suggèrent que la morphométrie des régions sous les électrodes pourrait aider à identifier les meilleurs candidats pour la tDCS et pourrait être considéré pour la sélection des cibles de stimulation.Introduction: Gambling disorder (GD) is characterised by maladaptive gambling behaviour that interferes with personal or professional activities. This psychiatric disorder is difficult to treat with currently available treatments and relapse rates are high. Several factors can predict relapse, including depressive and cognitive (e.g., impulsivity, risk taking) symptoms, in addition to craving (strong desire to gamble). A better understanding of neural substrates and their clinical significance could help develop new treatments. Transcranial direct current stimulation (tDCS) might be one of these since it can target specific neural circuits. In addition, tDCS targeting the dorsolateral prefrontal cortex (DLPFC) could improve depressive and cognitive symptoms as well as reduce craving. However, the precise effects of tDCS on brain function, as well as their clinical significance, remain to be elucidated. Furthermore, considering that patients with GD often display morphometric differences as compared to healthy individuals, it may be worth investigating whether brain morphometry influences the effects of tDCS. Objectives: This work had three main objectives. The first objective was to explore whether there were associations between neural substrates and clinical and cognitive symptoms. The second objective was to examine the effects of tDCS on brain function. The third objective was to explore whether morphometry of the stimulation site (DLPFC) influenced the effects of tDCS on neural substrates. Methods: We carried out four different studies. In the first study, we investigated brain morphometry using structural magnetic resonance imaging (MRI). We tested for correlations between morphometry and clinical symptoms (depression, GD severity, GD duration) and cognitive symptoms (impulsivity). In addition, we compared the morphometry of patients with GD to that of a normative database (healthy individuals) while controlling for several factors such as age. In a second study, we assessed brain function (functional connectivity) in patients with functional MRI (fMRI). We examined whether there were associations between brain function and cognitive symptoms (impulsivity and risk taking) as well as clinical symptoms (GD severity and duration). In the third study, we examined tDCS-induced effects on brain function and whether morphometry of the DLPFC influenced these effects. Lastly, in the fourth study, we examined whether DLPFC morphometry influenced tDCS-induced effects on neurochemistry (using magnetic resonance spectroscopy imaging). Results: Firstly, we found two positive correlations between surface area of the occipital cortex and depressive symptoms (study I). We also showed a positive correlation between functional connectivity of an occipital network and impulsivity (study II). In addition, there was a positive correlation between functional connectivity of this network and GD severity (study II). In addition, there were positive correlations between functional connectivity of the right frontal operculum and risk-taking (study II). Also, functional connectivity of a cerebellar network was positively correlated with depressive symptoms (study II). Moreover, patients with GD had several morphometric differences as compared to healthy individuals (occipital and prefrontal cortices, etc.). Furthermore, we observed that tDCS over the DLPFC increased functional connectivity of a fronto-parietal circuit during stimulation (study III). Lastly, this thesis indicated that DLPFC morphometry influenced tDCS-induced elevations on fronto-parietal functional connectivity (study III) and frontal GABA levels (study IV). Conclusions: This thesis suggests the potential clinical relevance of occipital, frontal, and cerebellar regions, particularly for those with depressive and cognitive symptoms. It also indicates that tDCS can strengthen the functioning of a fronto-parietal network known to be implicated in executive functions. It remains to be seen whether a greater number of tDCS sessions could lead to clinical benefits to help patients resist gambling. Finally, the results of this thesis suggest that morphometry of the regions under the electrodes might help predict better candidates for tDCS and could be considered to select stimulation targets