In this thesis we model two very different movement-related neuronal circuits, both of which produce oscillatory patterns of activity. In one case we study oscillatory activity in the basal ganglia under both normal and Parkinsonian conditions. First, we used a detailed Hodgkin-Huxley type spiking model to investigate the activity patterns that arise when oscillatory cortical input is transmitted to the globus pallidus via the subthalamic nucleus. Our model reproduced a result from rodent studies which shows that two anti-phase oscillatory groups of pallidal neurons appear under Parkinsonian conditions. Secondly, we used a population model of the basal ganglia to study whether oscillations could be locally generated. The basal ganglia are thought to be organised into multiple parallel channels. In our model, isolated channels could not generate oscillations, but if the lateral inhibition between channels is sufficiently strong then the network can act as a rhythm-generating ``pacemaker'' circuit. This was particularly true when we used a set of connection strength parameters that represent the basal ganglia under Parkinsonian conditions. Since many things are not known about the anatomy and electrophysiology of the basal ganglia, we also studied oscillatory activity in another, much simpler, movement-related neuronal system: the spinal cord of the Xenopus tadpole. We built a computational model of the spinal cord containing approximately 1,500 biologically realistic Hodgkin-Huxley neurons, with synaptic connectivity derived from a computational model of axon growth. The model produced physiological swimming behaviour and was used to investigate which aspects of axon growth and neuron dynamics are behaviourally important. We found that the oscillatory attractor associated with swimming was remarkably stable, which suggests that, surprisingly, many features of axonal growth and synapse formation are not necessary for swimming to emerge. We also studied how the same spinal cord network can generate a different oscillatory pattern in which neurons on both sides of the body fire synchronously. Our results here suggest that under normal conditions the synchronous state is unstable or weakly stable, but that even small increases in spike transmission delays act to stabilise it. Finally, we found that although the basal ganglia and the tadpole spinal cord are very different systems, the underlying mechanism by which they can produce oscillations may be remarkably similar. Insights from the tadpole model allow us to predict how the basal ganglia model may be capable of producing multiple patterns of oscillatory activity.

Schizophrenia remains an enigmatic disorder with unclear neuropathology. Recent advances in neuroimaging and genetic research suggest alterations in glutamate-dopamine interactions adversely affecting synaptic plasticity both intracortically and subcortically. Relating these changes to the manifestation of symptoms presents a great challenge, requiring a constrained framework to capture the most salient elements. Here, a biologically-grounded computational model of basal ganglia-mediated action selection was used to explore two pathological processes that hypothetically underpin schizophrenia. These were a drop in the efficiency of cortical transmission, reducing both the signal-to-noise ratio (SNR) and overall activity levels; and an excessive compensatory upregulation of subcortical dopamine release. It was proposed that reduced cortical efficiency was the primary process, which led to a secondary disinhibition of subcortical dopamine release within the striatum. This compensation was believed to partly recover lost function, but could then induce disorganised-type symptoms - summarised as selection ”Instability” - if it became too pronounced. This overcompensation was argued to be countered by antipsychotic medication. The model’s validity was tested during an fMRI (functional magnetic resonance imaging) study of 16 healthy volunteers, using a novel perceptual decision-making task, and was found to provide a good account for pallidal activation. Its account for striatum was developed and improved with a small number of principled model modifications: the inclusion of fast spiking interneurons within striatum, and their inhibition by the basal ganglia’s key regulatory nucleus, external globus pallidus. A key final addition was the explicit modelling of dopaminergic midbrain, which is dynamically regulated by both cortex and the basal ganglia. This enabled hypotheses concerning the effects of cortical inefficiency, compensatory dopamine release and medication to be directly tested. The new model was verified with a second set of 12 healthy controls. Its pathological predictions were compared to data from 12 patients with schizophrenia. Model simulations suggested that Instability went hand-in-hand with cortical inefficiency and secondary dopamine upregulation. Patients with high Instability scores showed a loss of SNR within decision-related cortex (consistent with cortical inefficiency); an exaggerated response to task demands within substantia nigra (consistent with dopaminergic upregulation); and had an improved fit to simulated data derived from increasingly cortically-inefficient models. Simulations representing the healthy state provided a good account for patients’ motor putamen, but only cortically-inefficient simulations representing the ill state provided a fit for ventral-anterior striatum. This fit improved as the simulated model became more medicated (increased D2 receptor blockade). The relative improvement of this account correlated with patients’ medication dosage. In summary, by distilling the hypothetical neuropathology of schizophrenia into two simplified umbrella processes, and using a computational model to consider their effects within action selection, this work has successfully related patients’ fMRI activation to particular symptomatology and antipsychotic medication. This approach has the potential to improve patient care by enabling a neurobiological appreciation of their current illness state, and tailoring their medication level appropriately.

Neuro-computational models allow to study the brain mechanisms involved in intelligent behavior and extract essential computational principles which can be implemented in cognitive systems. They are a promising solution to achieve a brain-like artificial intelligence that can compete with natural intelligence on realistic behaviors. A crucial property of intelligent behavior is motivation, defined as the incentive to interact with the world in order to achieve specific goals, either extrinsic (obtaining rewards such as food or money, or avoiding pain) or intrinsic (satisfying one’s curiosity, fun). In the human brain, motivated or goal-directed behavior depends on a network of different structures, including the prefrontal cortex, the basal ganglia and the limbic system. Dopamine, a neurotransmitter associated with reward processing, plays a central role in coordinating the activity of this network. It structures processing in high-level cognitive areas along a limbic-associative-motor gradient and impacts the learning capabilities of the whole system. In this habilitation thesis, I present biologically-constrained neuro-computational models which investigate the role of dopamine in visual object categorization and memory retrieval (Vitay and Hamker, 2008), reinforcement learning and action selection (Vitay and Hamker, 2010), the updating, learning and maintenance of working memory (Schroll et al., 2012) and timing processes (Vitay and Hamker, 2014). These models outline the many mechanisms by which the dopaminergic system regulates cognitive and emotional behavior: bistable processing modes in the cerebral cortex, modulation of synaptic transmission and plasticity, allocation of cognitive resources and signaling of relevant events. Finally, I present a neural simulator able to simulate a variety of neuro-computational models efficiently on parallel architectures (Vitay et al., 2015). / Neuronale Modelle nach dem Vorbild des Gehirns bieten die Möglichkeit intelligente, kognitive Prozesse nicht nur besser zu verstehen, sondern sie stellen auch eine vielversprechende Lösung dar, um eine Gehirn-ähnliche künstliche Intelligenz für Wahrnehmung und Verhaltensweisen zu erreichen, die mit natürlicher Intelligenz konkurrieren kann. Eine entscheidende Eigenschaft von intelligentem Verhalten ist Motivation, definiert als der Anreiz mit der Welt zu interagieren, um bestimmte Ziele zu erreichen, sei es extrinsisch (Belohnungen wie Nahrung oder Geld zu erhalten oder die Vermeidung von Schmerzen) oder intrinsisch (die Neugier zu befriedigen, Spaß zu haben). Im menschlichen Gehirn basiert motiviertes oder zielgerichtetes Verhalten auf einem Netzwerk von verschiedenen Strukturen, einschließlich des präfrontalen Cortex, der Basalganglien und des limbischen Systems. Dopamin, ein Neurotransmitter, welcher der Belohnungsverarbeitung zugeordnet wird, spielt eine zentrale Rolle bei der Koordination der Aktivität in diesem Netzwerk. Es strukturiert die Verarbeitung in High-Level-kognitiven Bereichen entlang eines limbischen-assoziativ-motor Gradienten und beinflusst die Lernfähigkeit des gesamten Systems. In dieser Habilitation, präsentiere ich biologisch motivierte neuronale Modelle, die die Rolle von Dopamin in der visuellen Objektkategorisierung und Gedächtnisabruf (Vitay and Hamker, 2008), Reinforcement Lernen und Aktionsauswahl (Vitay and Hamker, 2010), Aktualisierung, Lernen und Aufrechterhaltung von Arbeitsgedächtnis (Schroll et al., 2012) und Timing Prozessen (Vitay and Hamker, 2014) untersuchen. Diese Modelle beschreiben Mechanismen, durch die das dopaminerge System kognitives und emotionales Verhalten reguliert: bistabile Verarbeitungsmodi in der Hirnrinde, Plastizität und Modulation der synaptischen Übertragung, Zuweisung von kognitiven Ressourcen und Signalisierung von relevanten Ereignissen. Schließlich beschreibe ich einen neuronalen Simulator, der in in der Lage ist, eine Vielzahl von neuronalen Modellen effizient auf parallelen Architekturen zu simulieren (Vitay et al., 2015).

Parkinson's disease (PD) is characterized by debilitating impairments in motor control arising from pathophysiological alterations in basal ganglia circuitry and function. In this research thesis two main approaches, namely electrical recording and stimulation, are combined in order to better understand motor performance in Parkinson's disease and ways it might be improved. Three main types of motor behaviors are studied: discrete ballistic movement, repetitive movement, and motor adaptation. <ul><li>First, deep brain stimulation (DBS) of the subthalamic nucleus (STN) was shown to improve the velocity of discrete, ballistic movements in PD. The neural correlates of ballistic movements were then studied by recording from the STN of PD patients, revealing onset of beta-range desynchronization prior to, and gamma-range frequency synchronization during, performance of fast arm reaches. To determine a causal role for these oscillatory frequencies in motor behavior, the motor cortex of healthy humans was stimulated at either beta or gamma frequency during a 'go/no-go' grip force task. Beta stimulation resulted in slower force generation on 'go' trials but enhanced inhibition during 'no-go' trials, whereas gamma stimulation resulted in faster force generation on 'go' trials.</li> <li>Second, STN DBS resulted in improved repetitive tapping performance in PD patients through a reduction in variability. Recordings from the STN demonstrated that repetitive movement was accompanied by a substantial and persistent suppression of beta oscillatory activity.</li> <li>Third, Parkinson's patients were tested on a motor adaptation task, revealing intact learning but impaired retention of a visuomotor rotation. Application of direct current stimulation of the motor cortex resulted in enhanced adaptation during both learning and retention in PD patients and healthy controls.</li> <li>These results causally implicate the basal ganglia and oscillatory activity in motor control, provide insight into the neuronal mechanisms of motor performance and adaptation, and demonstrate promising new avenues for enhancing motor control in Parkinson's disease.</li></ul>

The basal ganglia (BG) is a complex set of heavily interconnected nuclei located in the central part of the brain that receives inputs from the several areas of the cortex and projects via the thalamus back to the prefrontal and motor cortical areas. Despite playing a significant part in multiple brain functions, the physiology of the BG and associated disorders like dystonia remain poorly understood. Dystonia is a devastating condition characterized by ineffective, twisting movements, prolonged co-contractions and contorted postures. Evidences suggest that it occurs due to abnormal discharge patterning in BG-thalamocortocal (BGTC) circuitry. The central purpose of this study was to understand the electrophysiology of BGTC circuitry and its role in motor control and dystonia. Toward this goal, an advanced multi-target multi-unit recording and analysis system was utilized, which allows simultaneous collection and analysis of multiple neuronal units from multiple brain nuclei. Over the cause of this work, neuronal data from the globus pallidus (GP), subthalamic nucleus (STN), entopenduncular nucleus (EP), pallidal receiving thalamus (VL) and motor cortex (MC) was collected from normal, lesioned and dystonic rats under awake, head restrained conditions. The results have shown that the neuronal population in BG nuclei (GP, STN and EP) were characterized by a dichotomy of firing patterns in normal rats which remains preserved in dystonic rats. Unlike normals, neurons in dystonic rat exhibit reduced mean firing rate, increased irregularity and burstiness at resting state. The chaotic changes that occurs in BG leads to inadequate hyperpolarization levels within the VL thalamic neurons resulting in a shift from the normal bursting mode to an abnormal tonic firing pattern. During movement, the dystonic EP generates abnormally synchronized and elongated burst duration which further corrupts the VL motor signals. It was finally concluded that the loss of specificity and temporal misalignment between motor neurons leads to corrupted signaling to the muscles resulting in dystonic behavior. Furthermore, this study reveals the importance of EP output in controlling firing modes occurring in the VL thalamus.

This thesis focuses on cognitive functions in patients after methanol poisoning. The theoretical part consists of a description of methanol, characteristics of methanol poisoning and its neurological sequelae. Methanol poisoning affects the basal ganglia, therefore we describe them and their role in cognitive processes. The theoretical part also describes a case of mass methanol poisoning in the Czech Republic in 2012-2013. The practical part compares results of a control group and a group of patients poisoned with methanol in cognitive assessment. Results show that the patients after methanol poisoning have significantly lower scores in tasks testing memory and executive functions than the control group.

Le Colliculus Supérieur (SC) est bien connu pour son rôle dans la génération des saccades oculaires. Sa connectivité réciproque avec les Ganglions de la Base (BG) a récemment été mise en évidence, ainsi que son implication active dans les processus de sélection saccadique. Indépendamment du rôle des BG dans la sélection en général, les hypothèses traditionnelles suggèrent que la sélection au sein du SC résulte d'inhibitions latérales réciproques. Notre modèle propose de développer une autre hypothèse, dans laquelle les BG jouent un rôle important pour la sélection des cibles des saccades par un circuit purement sous-cortical SC-BG. En partant du constat que les profils d'activités des populations neuronales du SC peuvent être assimilés à ceux des neurones accumulateurs stochastiques des modèles phénoménologiques de sélection par course, ce nouveau modèle propose que la sélection observée dans le SC résulte non pas d'interactions latérales dans le SC, mais d'un processus de course vers un seuil de sélection dans les couches colliculaires intermédiaires, seuil dynamiquement déterminé par une désinhibition sélective opérée par les BG dans le cadre d'une boucle de rétrocontrôle double des BG vers le SC. Ce modèle reproduit divers profils d'activité neuronaux observés in-vivo, ainsi que les profils de sélection de plusieurs tâches expérimentales relatives à la discrimination entre de nombreux stimuli similaires. Son neuromimétisme lui permet de proposer diverses prédictions sur les substrats neurologiques de ses composants, et les substrats neurologiques de divers phénomènes particuliers de sélection comme les saccades moyennes ou le remote distractor effect. / The Superior Colliculus (SC) is well-known for its role in the generation of ocular saccades. Its reciprocal connectivity with the Basal Ganglia (BG) has recently been highligted, as well as its active involvement in the saccadic selection processes. Yet, the most common hypothesis explaining its role in saccade target selection neglect the potential implication of the BG and focus on unproven networks of lateral reciprocal inhibitions within the SC. We propose a model based on a the SC-BG loop hypothesis, in the framework of a purely subcortical saccade selection process Since the activity profiles of specific SC neurons populations can be seen as equivalent to the stochastic accumulators of the phenomelogical race models, we propose that the selection operated bythe SC is based not on lateral inhibitions within its maps, but on a race to a selection threshold in the intermediate layers of the SC, the threshold being dynamically set by the selective disinhibition of the SC maps by a double closed loops with the BG. Our model is able to reproduce various in-vivo neuronal activity profiles, as well as the selection distributions observed in various experimental setups involving the discrimination between numerous identical stimuli. Our model's neuromimetism level allows us to propose predictions about the neuronal substrates of the model's components, as well as the substrates for various selection phenomenons such as average saccades and the remote distractor effect.

Notre cerveau prend en charge différentes formes d’apprentissage dans ses diverses parties. C’est par exemple le cas des ganglions de la base, un ensemble de noyaux sous-corticaux qui est impliqué dans la sélection de l’action et une forme spécifique de l’apprentissage / mémoire, la mémoire procédurale (mémoire des compétences ou d’expertise). A l’échelle du neurone unique, le support le plus plausible de l’apprentissage et de la mémoire est la plasticité synaptique, le processus par lequel l’efficacité de la communication entre deux neurones change en réponse à un pattern spécifique de conditions environnementales. Parmi les différentes formes de plasticité synaptique, la plasticité dépendante du timing des spikes (STDP) représente le fait que le poids synaptique (l’efficacité de la connexion) change en fonction du temps écoulé entre l’émission des deux potentiels d’action (spikes) présynaptiques et postsynaptiques consécutifs. Si la STDP est une forme de plasticité qui a récemment attiré beaucoup d’intérêt, on ne comprend pas encore comment elle émerge des voies de signalisation / biochimiques qui la sous-tendent. Pour répondre à cette question, nous combinons les approches expérimentales de nos collaborateurs (pharmacologie et électrophysiologie) avec la modélisation de la dynamique des réseaux de signalisation impliquées (décrite par des équations différentielles ordinaires). Après estimation des paramètres, le modèle reproduit la quasi-totalité des données expérimentales, y compris la dépendance de la STDP envers le nombre stimulations pré- et post-synaptiques appariées et son exploration pharmacologique intensive (perturbation des voies de signalisation par des produits chimiques). En outre, contrairement à ce qui était largement admis dans la communauté des neurosciences, notre modèle indique directement que le système endocannabinoïde contrôle les changements du poids synaptique de façon bi-directionnelle (augmentation et diminution). De plus, nous étudions comment une série de facteurs comme la recapture du glutamate régule la STDP. Notre modèle représente une première étape pour l’élucidation de la régulation de l’apprentissage et de la mémoire au niveau du neurone unique dans les ganglions de la base. / Our brains support various forms of learning in their various subparts. This is for instance the case of the basal ganglia, a set of subcortical nuclei that is involved in action selection and a specific form of learning / memory, procedural memory (memory of skills or expertise). At the scale of single neurons, the most plausible support of learning and memory is synaptic plasticity, the process by which the efficiency of interneuronal communication changes in response to a pattern of environmental conditions. A recent focus of research is on spike-timing dependent plasticity (STDP), whereby the relative timing of activations (spikes) of connected pre- and postsynaptic neurons, determines the synaptic weight (the efficiency of synaptic connection). Notwithstanding, the dependence of STDP on underlying signaling pathways is not yet fully understood. To address this issue, we combine experimental approaches by our collaborators (pharmacology and electrophysiology) with modeling of the implicated signaling network (described by Ordinary-Differential Equations). After parameter estimation, the model reproduces much of experimental data, including the dependence of STDP on the number of paired stimuli of pre- and postsynaptic neurons and intensive pharmacological exploration (where signaling molecules are perturbed by chemicals). Furthermore, in opposition to what was widely believed in the neuroscience community, our model directly indicates that the endocannabinoid system supports bidirectional changes of the synaptic weight (increase and decrease). Moreover, we study how a range of factors including glutamate uptake regulates STDP. We expect our model to be a starting point to the elucidation of the regulation of learning and memory in the basal-ganglia at the single neuron level.

La souris scrambler (Dab1scm) est un mutant ataxique cérébelleux qui présente une mutation naturelle du gène mdab1, codant pour une protéine intracellulaire nécessaire à la voie de signalisation de la rééline. Cette protéine joue un rôle crucial dans la mise place et la plasticité des structures laminées telles que le cortex cérébral, l’hippocampe ou le cervelet. Notre objectif a été de caractériser le phénotype comportemental et neurochimique de la souris scrambler au cours du développement post-natal et à l’âge adulte. Les premiers signes de l’ataxie cérébelleuse sont observables dès 8 jours et sont majorés au cours des 2ème et 3ème semaines de vie post-natale. A l’âge adulte, la souris se caractérise par un trouble important de la coordination motrice et une hyperactivité locomotrice exacerbée et stéréotypée (comportement de rotation) lorsque l’animal est placé en milieu aquatique. Les tests du labyrinthe aquatique de Morris et de l’alternance spontanée mettent en évidence des déficiences possiblement causées par un trouble du guidage visuo-moteur et la désinhibition comportementale. Chez ces souris, l’activité métabolique régionale évaluée par le marquage de la cytochrome oxydase est relativement préservée dans le cervelet ; elle est en revanche altérée dans diverses régions du tronc cérébral qui lui sont associées ainsi que dans l’hippocampe et certaines régions corticales. Le comportement de rotation stéréotypé et l’hyperactivité causés possiblement par un déséquilibre neurochimique acétylcholine/dopamine a été évalué dans un rotamètre avec ou sans injection préalable d’un antagoniste des récepteurs D2. Parallèlement, l’innervation cholinergique du système nerveux central, révélée par l’activité de l’acétylcholinestérase était diminuée dans la substance noire pour laquelle nous avons observé une désorganisation et une perte partielle des neurones dopaminergiques. Bien que les atteintes multiples compliquent l’étude structuro- fonctionnelle de ce mutant, nos résultats ont permis de préciser le phénotype scrambler en le comparant aux autres mutants de la voie de la rééline. Ces mutants font l’objet aujourd’hui d’un intérêt croissant pour la modélisation non seulement de l’ataxie mais également de certaines maladies neurologiques et neuro-psychiatriques comme l’autisme et la schizophrénie / The Dab1scm scrambler mice is a cerebellar ataxic mutant spontaneously mutated for a gene encoding a protein of the reelin signaling pathway involved in the development and the plasticity of laminated structures such as the neocortex, the hippocampus, and the cerebellum. Our objective was to characterize the behavioral and neurochemical phenotype of the scrambler mice during postnatal developmental and adult stages. The first signs of cerebellar ataxia are observable as early as 8 days and increase during the 2nd and 3rd weeks of postnatal life. Adult mouse is characterized by a significant disturbance of motor coordination and a locomotor hyperactivity which increases ans becomes stereotyped (circling) when the animal was placed in water. Morris water maze and spontaneous alternation highlight deficiencies possibly caused by disorder of visuomotor control and disinhibitory processes. Brain regional metabolic activity measured by cytochrome oxidase is relatively preserved in the mutant cerebellum. However, it is impaired in various connected regions of the brainstem as well as in the hippocampus and some cortical regions. Circling behavior and hyperactivity, possibly caused by a neurochemical imbalance between acetylcholine and dopamine, were evaluated in a rotameter with or whithout prior injection of D2 receptor antagonist. In parallel, cholinergic innervation of the central nervous system measured by acetylcholinesterase activity is lower in the substantia nigra for which a partial disruption and loss of dopaminergic neurons is observed. Although the multiple alterations complicate the structuro-fonctional study of this mutant, results have clarified the scrambler phenotype by comparison with others mutants of the reelin pathway. This mutants are now subject to a growing interest in not only ataxia modeling but also some neurological and neuropsychiatric diseases

Les dernières avancées dans le domaine de l’imagerie par résonance magnétique permettent aujourd’hui de mieux comprendre l’anatomie et le fonctionnement du cerveau humain. L’IRM s’avère d’ailleurs aujourd’hui un outil clé pour la recherche de biomarqueurs d’imagerie dans la plupart des pathologies cérébrales. Nous nous sommes intéressés dans le cadre de cette thèse à l’étude de la connectivité anatomique des noyaux gris centraux, structures impliquées dans de nombreuses boucles cortico-sous-cortico-corticales, et dont l’atteinte est à l’origine de troubles moteurs à l’instar de la maladie de Huntington, du syndrome Gilles de la Tourette et de la maladie de Parkinson. Nous avons pour cela effectué plusieurs développements méthodologiques qui permettent de segmenter les noyaux gris centraux et d’inférer leur connectivité anatomique. Tout d’abord, nous avons développé une méthode de segmentation des noyaux gris centraux à partir de différents contrastes et capable de s’adapter à des cas pathologiques présentant une forte modification de ces structures. Ensuite, nous avons développé des méthodes robustes d’analyse et de sélection des fibres reliant les différentes structures cérébrales, obtenues à l’aide de méthodes de tractographie par IRM du processus de diffusion cérébrale. Ces nouvelles méthodes de sélection présentent l’avantage de tenir compte d’a priori anatomiques, et fournissent ainsi des résultats plus proches de la réalité que les résultats obtenus dans la littérature. Nous avons également développé une méthodologie permettant de construire des cartes de connectivité surfaciques afin de projeter les connexions des noyaux gris centraux sur la surface corticale et de comparer le profil de connectivité corticale des noyaux gris au sein d’une population et entre populations. Enfin, nous avons utilisé ces outils pour étudier les modifications putatives de la connectivité anatomique des noyaux gris centraux dans la maladie de Huntington et dans le syndrome Gilles de la Tourette. / The recent advances in magnetic resonance imaging helped understanding brain anatomy and function. Today, MR imaging is a key tool for inferring imaging-based biomarkers for most neuropathologies. In this work, we focused on the anatomical connectivity of the basal ganglia which are involved in several cortico-subcortical loops and which dysfunction is the origin of motor disorders like Huntington and Parkinson diseases and Gilles de la Tourette syndrome. We developed several tools allowing the segmentation of the basal ganglia and inferring their anatomical connectivity. First, we developed a method for deep nuclei segmentation using several contrasts and that was adapted for pathological cases presenting high modifications in the morphology of these structures. Second, we developed robust methods for the analysis and the selection of the fiber tracts linking different brain structures and obtained using dMRI and tractography methods. These novel tools have the advantage of taking into account anatomical prior knowledge. Therefore the obtained results are closer to the real anatomy than those obtained using the tools available in the literature. We also developed surface connectivity maps that project the cortical connections of the deep nuclei directly on the cortical surface and that allow the comparison of the connectivity profile of the deep nuclei between different subjects and different groups. Finally, we used these tools to study the putative modifications of the anatomical connectivity of the deep nuclei in the Huntington disease and Gilles de la Tourette syndrome.