<p>Neuroimaging and neurophysiology techniques were used to study some aspects of cortical sensory and motor system reorganisation in patients in the chronic phase after stroke. Using Diffusion Tensor Imaging, we found that the degree of white matter integrity of the corticofugal tracts (CFT) was positively related to grip strength. Structural changes of the CFT were also associated with functional changes in the corticospinal pathways, measured using Transcranial Magnetic Stimulation. This suggests that structural and functional integrity of the CFT is essential for upper limb function after stroke.</p><p>Using functional magnetic resonance imaging (fMRI), to measure brain activity during slow and fast passive hand movements, we found that velocity-dependent brain activity correlated positively with neural contribution to passive movement resistance in the hand in ipsilateral primary sensory (S1) and motor (M1) cortex in both patients and controls. This suggests a cortical involvement in the hyperactive reflex response of flexor muscles upon fast passive stretch.</p><p>Effects of a four week passive-active movement training programme were evaluated in chronic stroke patients. The group improved in range of motion and upper limb function after the training. The patients also reported improvements in a variety of daily tasks requiring the use of the affected upper limb. </p><p>Finally, we used fMRI to explore if brain activity during passive hand movement is related to time after stroke, and if such activity can be affected with intense training. In patients, reduced activity over time was found in supplementary motor area (SMA), contralateral M1 and prefrontal and parietal association areas along with ipsilateral cerebellum. After training, brain activity increased in SMA, ipsilateral S1 and intraparietal sulcus, and contralateral cerebellum in parallel with functional improvements of the upper limb. The findings suggest a use-dependent modification of cortical activation patterns in the affected hand after stroke. </p>

Neuroimaging and neurophysiology techniques were used to study some aspects of cortical sensory and motor system reorganisation in patients in the chronic phase after stroke. Using Diffusion Tensor Imaging, we found that the degree of white matter integrity of the corticofugal tracts (CFT) was positively related to grip strength. Structural changes of the CFT were also associated with functional changes in the corticospinal pathways, measured using Transcranial Magnetic Stimulation. This suggests that structural and functional integrity of the CFT is essential for upper limb function after stroke. Using functional magnetic resonance imaging (fMRI), to measure brain activity during slow and fast passive hand movements, we found that velocity-dependent brain activity correlated positively with neural contribution to passive movement resistance in the hand in ipsilateral primary sensory (S1) and motor (M1) cortex in both patients and controls. This suggests a cortical involvement in the hyperactive reflex response of flexor muscles upon fast passive stretch. Effects of a four week passive-active movement training programme were evaluated in chronic stroke patients. The group improved in range of motion and upper limb function after the training. The patients also reported improvements in a variety of daily tasks requiring the use of the affected upper limb. Finally, we used fMRI to explore if brain activity during passive hand movement is related to time after stroke, and if such activity can be affected with intense training. In patients, reduced activity over time was found in supplementary motor area (SMA), contralateral M1 and prefrontal and parietal association areas along with ipsilateral cerebellum. After training, brain activity increased in SMA, ipsilateral S1 and intraparietal sulcus, and contralateral cerebellum in parallel with functional improvements of the upper limb. The findings suggest a use-dependent modification of cortical activation patterns in the affected hand after stroke.

There are competing theories in the literature regarding the extent to which the translation of print to speech involves single or multiple routes. Regardless of the number of routes in a model, all models of reading must account for both sight vocabulary (SV) processing, which specializes in mapping whole-word representations, and phonetic decoding (PD) processing, which specializes in mapping sub-word representations. The purpose of the present work was to examine two hypotheses regarding the relationship between SV and PD: independence versus redundancy. Both behavioural and functional Magnetic Resonance Imaging (fMRI) experiments were conducted and the results supported the hypothesis that SV and PD are behaviourally and neurobiologically independent processes. Furthermore, in the interest of advancing all models of basic word recognition, the neurobiological representations of some of the sub-systems within SV and PD routes were explored and the contribution that particular brain regions make to the completion of naming particular stimuli was evaluated. Finally, basic and applied areas of research were integrated to demonstrate how diagnostic stimuli developed from basic reading research can inform us about impaired reading performance following traumatic brain injury.

Traditional fMRI utilizes blood oxygenation level dependent (BOLD) contrast to map brain activity. BOLD signal is sensitive to the hemodynamic changes associated with brain activity, and gives an indirect measure of brain activity. Low frequency fluctuations (LFFs) have been observed in the BOLD signal even in the absence of any anesthetic agent, and the correlations between the fluctuations from different brain regions has been used to map functional connectivity in the brain. Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. The research presented in this document investigates the spatiotemporal dynamics of the BOLD fluctuations to identify common spatiotemporal patterns within a scan. First, the presence of a visually detectable spatiotemporal propagation pattern is demonstrated by utilizing single-slice data with high spatial and temporal resolution. The pattern consists of lateral-medial propagation of BOLD signal, demonstrating the presence of time-varying features in spontaneous BOLD fluctuations. Further, a novel pattern finding algorithm is developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm is applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consists of waves of high signal intensity, propagating in a lateral-medial direction across the cortex, replicating the results obtained using visual observation. In humans, the most common spatiotemporal pattern consisted of an alteration between activation of areas comprising the "default-mode" (e.g., posterior cingulate and anterior medial prefrontal cortices) and the "task-positive" (e.g., superior parietal and premotor cortices) networks. Signal propagation from focal starting points is also observed. The pattern finding algorithm is shown to be reasonably insensitive to the variation in user-defined parameters, and the results are consistent within and between subjects. This novel approach for probing the spontaneous network activity of the brain has implications for the interpretation of conventional functional connectivity studies, and may increase the amount of information that can be obtained from neuroimaging data.

Parkinson’s disease (PD) is next to Alzheimer’s disease (AD) the second most common neurodegenerative disease. PD has traditionally been characterised as a motor disorder, but more recent research has revealed that cognitive impairments are frequent. Cognitive impairments in executive functions, attention, and working memory with reliance on dopaminergic transmission, are often described as dominating the cognitive profile in early-phase PD. However, although knowledge about the neuropathology that underlies the cognitive impairments in PD has increased, its features are complex and knowledge remains insufficient. Therefore, the aim of the current thesis was to improve the understanding of how task-evoked brain responses relate to cognitive status in patients with PD, with and without mild cognitive impairment (MCI), and to evaluate the predictive value of PD-MCI in respect of prodromal Parkinson’s disease dementia (PDD). This was conducted within the “new Parkinsonism in Umeå” (NYPUM) project, which is a prospective cohort study. Patients with idiopathic PD were included in this thesis, and the patients were examined with a comprehensive neuropsychological battery and with a functional MRI (fMRI) working memory protocol. During scanning, patients conducted a verbal two-back task in which they needed to maintain and actively update relevant information, and the primary outcome measure was blood-oxygen-level-dependent (BOLD) signal. This thesis shows that patients with PD-MCI had significantly lower BOLD signal responses than patients without MCI in frontal (anterior cingulate cortex) and striatal (right caudate) regions (Study I). The altered BOLD response in the right caudate was associated with altered presynaptic dopamine binding. The fronto-striatal alterations persisted across time but without any additional change. However, decreased posterior cortical (right fusiform gyrus) BOLD signal responses were observed in patients with PD-MCI relative to patients without MCI across time (Study II). Finally, PD-MCI at baseline examination is highly predictive for prodromal PDD with a six-fold increased risk. Cognitive tests with a posterior cortical basis, to a greater extent, are predictive for prodromal PDD than tests with a fronto-striatal basis. The observed working memory related alterations in patients with PD-MCI suggest that early cognitive impairments in PD are linked to fronto-striatal dopaminergic dysfunction. The longitudinal development of cognitive impairment in PD reflects additional posterior cortical dysfunction. This might reflect a dual syndrome, with dopamine-depleted fronto-striatal alterations that characterise PD-MCI in general, whereas additional posterior cortical cognitive alterations with a non-dopaminergic basis to a greater extent characterise prodromal PDD. If, and how, the two potential syndromes interact, is still unclear. Thus, this thesis provides information on cognitive neuropathological changes in PD that might contribute to more relevant choices of pharmacotherapy and diagnostic accuracy in respect of PDD. However, additional large-scale longitudinal imaging studies are needed to further clarify the neuropatholgogical features of PD-MCI in respect of prodromal PDD.

Les modalités d'imagerie fonctionnelle et de perfusion sont étroitement liées car les deux mesurent, directement ou indirectement, le débit sanguin cérébral. D’une part, en utilisant le contraste BOLD (Blood-Oxygen-Level-Dependent), l'imagerie fonctionnelle par résonance magnétique (IRMf) exploite les propriétés magnétiques du sang (oxy et désoxyhémoglobine) pour y mesurer les changements locaux de concentration en oxygène: ce couplage neurovasculaire permet de déduire le fonctionnement du cerveau à partir des images IRMf. D’autre part, l'IRM de perfusion reflète le fonctionnement du système vasculaire cérébral en mesurant directement le débit sanguin cérébral. En particulier, l’IRM du marquage de l’eau artérielle (ASL) n'a pas besoin d'agents de contraste: le traceur est remplacé par des spins de protons endogènes d'eau. Habituellement l’ASL est utilisée pour mesurer la perfusion basale au repos. Toutefois, ces dernières années, il a également été utilisé comme une modalité d'imagerie fonctionnelle (comme fASL) en mesurant les variations de perfusion cérébrale induites par la réalisation de tâches cognitives. Contrairement à l'IRMf standard basée sur le contraste BOLD, les résultats sont quantitatifs, ce qui rend ce type de données intéressantes pour son utilisation dans la recherche clinique.Cette thèse porte sur l’étude de la modalité fASL et sur le développement de nouvelles méthodes pour l'analyser. Comme précédemment réalisé pour les données BOLD, un cadre bayésien est développé pour l'analyse des données fASL. Il fournit un moyen de modéliser les valeurs d'activation et les fonctions de réponse hémodynamique et de perfusion en tant que variables probabilistes dans l’approche de Détection-Estimation Conjointe. Les modèles bayésiens utilisent une connaissance a priori pour l'estimation des paramètres inconnus à travers la spécification de distributions de probabilité. Dans ce travail, nous exploitons cette fonction pour incorporer au modèle des informations physiologiques, afin de rendre l'estimation plus robuste. En particulier, nous utilisons des modèles physiologiques basés sur le modèle de ballon pour obtenir un lien entre les réponses hémodynamiques et de perfusion, puis nous utilisons ce lien dans une distribution a priori pour régulariser l'estimation des réponses. En utilisant information physiologique a priori, une solution de type Markov Chain Monte Carlo (MCMC) a été proposée pour l'estimation des quantités contenues dans le signal IRMf. Étant donné que le coût de calcul de cet algorithme est très élevé, nous reformulons le problème pour utiliser une approche variationnelle (VEM) qui fournit un algorithme beaucoup plus rapide avec des résultats similaires. Dans ce cadre, l'introduction d'information a priori et de contraintes est également plus simple.Ces méthodes ont été évaluées sur deux ensembles de données différentes en utilisant des paradigmes événementiels et du bloc, pour des tâches cognitives très simples. Nous montrons les bonnes performances des méthodes proposées par rapport aux méthodes standards, au niveau des sujets et du groupe. Les résultats expérimentaux montrent que les probabilités a priori physiologiques améliorent l'estimation d'une fonction de réponse de perfusion. Ces résultats démontrent également que le contraste BOLD a une meilleure sensibilité pour la détection de l'activité cérébrale évoquée que fASL, bien que la fASL donne une activation plus localisée, ce qui est conforme à la littérature existante. A partir de ces résultats, nous discutons l'impact de la modélisation de la corrélation spatiale, ainsi que l'impact de l'estimation des réponses temporelles.Ce travail propose de nouvelles contributions méthodologiques pour l'étude de la fASL, et les met en perspective avec les techniques existantes. Ainsi, nous proposons de nouveaux outils pour la communauté neuroscientifique, mis en œuvre en python dans le package PyHRF, pour étudier et comprendre le fonctionnement du cerveau. / Functional and perfusion imaging modalities are closely related since they both measure, directly or indirectly, blood flow in the brain. Functional Magnetic Resonance Imaging (fMRI) using the blood oxygen level dependent (BOLD) contrast exploits the magnetic properties of blood (oxy- and deoxyhemoglobin) to measure local changes in blood oxygen concentration in the brain. The neurovascular coupling allows us to infer brain function from fMRI images. Perfusion MRI images the cerebral vascular system by directly measuring blood flow. In particular, Arterial Spin Labeling (ASL) does not need contrast agents; it uses spins of endogenous water protons as a tracer instead. Usually ASL is used to probe the basal perfusion at rest. However, in the recent years, it has also been used as a functional imaging modality (as fASL) by tracking task-related perfusion changes. In contrast to the standard BOLD fMRI, results are quantitative, making this type of data attractive for use in clinical research.This thesis focuses on the investigation of the fASL modality and the development of new methods to analyze it. As previously done for BOLD data, a Bayesian framework is proposed for the analysis of fASL data. It provides a way of modeling activation values and both hemodynamic and perfusion response functions as probabilistic variables in the so-called joint detection estimation (JDE) framework. Bayesian models use a priori knowledge in the estimation of unknown parameters through the specification of probability distributions. In this work, we exploit this feature to incorporate physiological information to make the estimation more robust. In particular, we use physiological models based on the balloon model to derive a link between hemodynamic and perfusion responses and we turn this link into a prior distribution to regularize the estimation of the responses. A Markov Chain Monte Carlo solution with prior physiological knowledge has been first proposed for the estimation of the quantities contained in the fMRI signal. Since the computational cost of this algorithm is very high, we then reformulate the problem to use a variational expectation maximization approach that provides a much faster algorithm with similar results. The use of priors and constraints in this setting is also more straightforward.These methods have been evaluated on two different datasets using event-related and block designs with very simple experimental tasks. We show the performance of the methods investigated in comparison to standard methods at the subject and group levels. Experimental results show the utility of using physiological priors for improving the recovery of a perfusion response function. They also demonstrate that BOLD fMRI achieves better sensitivity to detect evoked brain activity as compared to fASL although fASL gives a more localized activation, which is in line with the existing literature. From the results, we discuss the impact of the modelling of spatial correlation, as well as the impact of the estimation of temporal responses.This work proposes new methodological contributions in the study of a relatively new fMRI modality that is functional ASL, and puts it into perspective with the existing techniques. Thus, we provide new tools for the neuroscientific community to study and understand brain function. These tools have been implemented in python in the PyHRF package.

Complex network models of functional connectivity have emerged as a paradigm shift in brain mapping over the past decade. Despite significant attention within the neuroimaging and cognitive neuroscience communities, these approaches have hitherto not been extensively explored in neurosurgery. The aim of this thesis is to investigate how the field of connectomics can contribute to understanding the effects of focal brain lesions and to functional brain mapping in neurosurgery. This datasets for this thesis include a clinical population with focal brain tumours and a cohort focused on healthy adolescent brain development. Multiple network analyses of increasing complexity are performed based upon resting state functional MRI. In patients with focal brain tumours, the full complement of resting state networks were apparent, while also suggesting putative patterns of network plasticity. Connectome analysis was able to identify potential signatures of node robustness and connections at risk that could be used to individually plan surgery. Focal lesions induced the formation of new hubs while down regulating previously established hubs. Overall these data are consistent with a dynamic rather than a static response to the presence of focal lesions. Adolescent brain development demonstrated discrete dynamics with distinct gender specific and age-gender interactions. Network architecture also became more robust, particularly to random removal of nodes and edges. Overall these data provide evidence for the early vulnerability rather than enhanced plasticity of brain networks. In summary, this thesis presents a combined analysis of pathological and healthy development datasets focused on understanding the functional effects of focal brain lesions at a network level. The coda serves as an introduction to a forthcoming study, known as Connectomics and Electrical Stimulation for Augmenting Resection (CAESAR), which is an evolution of the results and methods herein.

Les travaux présentés dans cette thèse portent sur l'effet d'apprentissages à court et long terme sur le système visuel. Nous avons d'abord montré grâce à des enregistrements Éléctroencéphalographiques que l'apprentissage d'une séquence de stimuli visuels induisait une activité cérébrale spontanée et sélective au prochain stimulus devant apparaitre et que cette activité sélective s'exprimait dans les bandes alpha et beta de l'activité électrique cérébrale. Par la suite nous avons montré grâce à de l'Imagerie par Résonance Magnétique fonctionnelle que lors d'apprentissages longs (trois semaines) les représentations neurales de catégories visuelles associées étaient modulées et devenaient plus similaires après l'apprentissage. Les travaux présentés dans cette thèse ont donc permis de mieux caractériser l'impact d'apprentissages à différentes échelles de temps sur les représentations neurales d'objets visuels. / The work presented in this thesis deals with the effect of short- and long-term learning on the visual system. We first demonstrated through electroencephalographic recordings that learning a sequence of visual stimuli induced spontaneous and selective cerebral activity to the next-to-appear stimulus and that this selective activity was expressed in the alpha and beta bands of cerebral electrical activity. Subsequently, we showed through functional magnetic resonance imaging that during long learning (three weeks) the neural representations of associated visual categories were modulated and became more similar due to learning. The work presented in this thesis has thus made it possible to better characterize the impact of learning at different time scales on the neural representations of visual objects.

Comment les agents anesthésiques induisent-ils une perte de conscience lors de l’anesthésie générale? La dissection des mécanismes neuronaux de l’anesthésie générale représente un défi important en neurosciences. L’émergence de l’IRM fonctionnelle (IRMf) chez le primate non-humain donne l’occasion d’étudier l’activité neuronale à l’état éveillé et sous anesthésie en s’affranchissant des contraintes cliniques. Le développement récent de paradigmes auditifs, tel que le paradigme ‘local-global’, qui explore spécifiquement les réseaux cérébraux impliqués dans l’état conscient, nous a permis d’émettre l’hypothèse que la combinaison de l’IRMf chez le primate, de paradigmes auditifs et de protocoles d’anesthésie contrôlés par l’électroencéphalogramme (EEG), pourraient aider à disséquer les mécanismes neuronaux de l’anesthésie générale.Dans une première étape, étant donnée l’utilisation extensive de l’IRM dans notre travail, il était important d’étudier systématiquement l’effet des agents anesthésiques sur l’oxygénation vasculaire cérébrale, paramètre critique pour le signal IRMf. Nous avons donc réalisé une expérience préliminaire, faisant appel à l’IRM à ultra-haut champ magnétique chez le rongeur, afin de détecter les éventuels modifications du signal T2* induits par chacun des agents anesthésiques. Nous avons pu démontrer que le propofol et la kétamine, deux agents anesthésiques utilisés en clinique, affectaient moins l’oxygénation sanguine cérébrale que les anesthésiques volatils.Dans une deuxième étape, nous avons développé une « boîte à outils » pour l’IRMf chez le primate éveillé et anesthésié, et avons validé notre dispositif expérimental avec un paradigme auditif basé sur des sons simples (basse et haute fréquence).Dans une troisième étape, nous avons testé le paradigme auditif ‘local-global’ chez le macaque éveillé et avons pu démontrer que le cerveau du macaque est capable d’un codage prédictif hiérarchique à travers un espace de travail global, composé d’un réseau fronto-pariéto-cingulaire, montrant une forte homologie avec celui de l’Homme.Dans une quatrième étape, nous avons testé le paradigme auditif ‘local-global’, chez le macaque anesthésié et avons pu démontrer une désorganisation progressive de l’espace de travail global neuronal sous anesthésie. Cette désorganisation a été proportionnelle au niveau de sédation sous propofol, et complète sous sédation profonde à la kétamine. Ces résultats sont compatibles avec l’hypothèse selon laquelle le mécanisme de la perte de conscience sous anesthésie, est lié à une désorganisation de l’organisation fonctionnelle hiérarchique de l’espace de travail neuronal. Le cortex pariétal apparaît comme une cible commune aux deux agents anesthésiques.Dans la dernière étape, nous avons étudié le réseau cérébral par défaut (« default mode network ») chez le macaque éveillé et anesthésié. Nous avons pu démontrer que sous anesthésie, le cerveau présentait encore des patrons de connectivité distincts et riches, mais que ces patrons étaient fortement liés à l’organisation anatomique sous-jacente, alors que, à l’état éveillé cette organisation se caractérisait par un haut degré de flexibilité temporelle ce qui permet une exploration non-stéréotypée d’une plus grande variété d’états cérébraux.En conclusion, les agents anesthésiques entraînent une désorganisation de l’espace de travail global neuronal, avec pour conséquence l’altération des dynamiques temporelles de l’activité cérébrale spontanée, induisant ainsi une suppression de la conscience. / How can anesthetics induce a loss of consciousness during general anesthesia? A major challenge in neuroscience is to dissect the mechanisms of general anesthesia, which is quite difficult to achieve in the clinical conditions. The dawning of monkey functional MRI (fMRI) in neuroscience is an important opportunity to investigate neuronal activity in awake and anesthetized conditions. The recent development of auditory paradigms, such as the ‘local-global’ paradigm, that specifically explore brain networks thought to be specific of the conscious state led us to hypothesize that the combination of primate fMRI, auditory paradigms and single-drug anesthetic protocols with electroencephalography (EEG) control would help dissect the neuronal mechanisms of general anesthesia. In a first step, because we planned an extensive use of fMRI in our work, it was key to screen anesthetic agents for their effects on brain vascular oxygenation, a critical parameter for fMRI signal. Thus we did a preliminary experiment using ultra-high field MRI in rodents to assess subtle changes of the T2* signal under different anesthetic conditions and could demonstrate that propofol and ketamine, both clinical anesthetics, affects less brain blood oxygenation than volatile agents. In a second step, we developed a toolbox for awake and anesthetized monkey fMRI and validated the experimental set-up with a simple sound paradigm (low and high frequency sounds). In the third step, we tested the ‘local-global’ auditory paradigm in awake monkeys and could demonstrate that the macaque brain was capable of hierarchical predictive coding through a hypothetical macaque Global Neuronal Workspace made of frontal, parietal and cingulate cortices, in a striking homology with humans. In the fourth step, we tested the ‘local-global’ auditory paradigm in anesthetized monkeys and could demonstrate a progressive disorganization of the macaque GNW under anesthesia when increasing the levels of propofol sedation, and a complete suppression of the macaque GNW under deep ketamine sedation. These results are compatible with the hypothesis that the mechanism of loss of consciousness under anesthesia is related to the disorganization of a hierarchical GNW, with the parietal cortex as a common target among anesthetics. In the final step we studied the default network by acquiring resting state in awake and anesthetized monkeys and could demonstrate that under anesthesia, the brain still exhibits distinct and rich connectivity patterns, but these patterns become strongly related to the underlying white-matter structural map in a monotonic manner, while the awake state is characterized by a high degree of temporal flexibility which allows for a non-stereotyped exploration of a greater variety of brain states. In conclusion, by disorganizing the GNW, anesthetics alter the temporal dynamics of spontaneous brain activity, and specifically its departure from mere random fluctuations along established anatomical routes, leading to consciousness suppression.

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