<div><div><div><p>Head injuries in collision sports have been linked to long-term neurological disorders. High school collision sport athletes, a population vulnerable to head injuries, are at a greater risk of chronic damage. Various studies have indicated significant deviations in brain function due to the accumulation of repetitive low-level subconcussive impacts to the head without externally observable cognitive symptoms. The aim of this study was to investigate metabolic changes in asymptomatic collision sport athletes across time within their competition season and as a function of mechanical force to their head. For this purpose, Proton Magnetic Resonance Spectroscopy (MRS) was used as a tool to detect altered brain metabolism in high school collision sport athletes (football and soccer) without diagnosed concussion. Also, sensors were attached to each athletes head to collect the count and magnitude of head impacts during their games and practices. Transient neurometabolic alterations along with prolonged recovery were observed in collision sport athletes.</p><div><div><div><p><br></p><p>Multi-site studies are becoming important to increase statistical power, enhance generalizability, and to improve the likelihood of pooling relevant subgroups together activities which are otherwise limited by the availability of patients or funds at a single site. Even with harmonized imaging sequences, site-dependent variability can mask the advantages of these multi-site studies. The aim of this study was to assess multi-site reproducibility in resting-state functional connectivity fingerprints, and to improve identifiability of obtained functional connectomes. We evaluated individual fingerprints in test- retest visit pairs within and across two sites and present a generalized framework based on principal component analysis (PCA) to improve identifiability. The optimally reconstructed functional connectomes using PCA showed a substantial improvement in individual fingerprinting of the subjects within and across the two sites and test-retest visit pairs relative to the original data. Results demonstrate that the data-driven method presented in the study can improve identifiability in resting-state functional connectomes in multi-site studies.</p></div></div></div></div></div></div>

INTRODUÇÃO: Transtornos psiquiátricos com sintomas psicóticos trazem prejuízos ocupacionais e sociais significativos aos seus portadores, com aumento da mortalidade e morbidade. Estes transtornos têm sido estudados como alterações do padrão de conectividade funcional nas redes cerebrais do estado de repouso. Entretanto, tais relatos são mais frequentes em pacientes crônicos, com literatura escassa sobre pacientes em primeiro episódio psicótico, principalmente não realizando comparações entre as redes. OBJETIVO: Este foi um estudo exploratório com objetivo de caracterizar a conectividade funcional cerebral das redes do estado de repouso em pacientes de primeiro episódio psicótico através da ressonância nuclear magnética funcional comparando-os a irmãos e a controles de base populacional. MÉTODOS: A amostra foi composta por por 38 pacientes em primeiro episódio psicótico, 13 irmãos e 41 controles de base populacional. Foram coletadas imagens por ressonância magnética funcional e a conectividade funcional foi obtida através do coeficiente de correlação de Pearson da série temporal do sinal BOLD de 264 regiões de interesse. A comparação da conectividade funcional entre os grupos de participantes foi feita pelo método Partial Least Square. Também foi utilizado o método Behavior Partial Least Square para buscar um padrão de conexões alteradas que estivesse associado a gravidade dos sintomas psicóticos, ao tempo de tratamento e a duração da psicose não tratada. A análise estatística contou com 10.000 permutações e um método de reamostragem e foram considerados significativos valores de p<0.05. RESULTADOS: As alterações nas redes, em sua maioria, foram devido à mudança de correlação positiva para correlação negativa nos pacientes em relação aos controles. As redes com maior número de conexões alteradas entre pacientes e controles foram a rede sensóriomotor mão, Default Mode Network (DMN) e rede visual. As conexões estiveram mais alteradas no lobo frontal direito. Não foi encontrada associação entre o padrão de conectividade funcional dos pacientes e a duração de psicose não tratada, o tempo de tratamento farmacológico e a gravidade da psicose. Na comparação entre pacientes e irmãos, foi encontrada uma tendência à significância de um padrão de conexões alteradas. Não foi encontrada diferença significativa entre o grupo de irmãos e o grupo controle. DISCUSSÃO: Pacientes em primeiro episódio psicótico apresentaram maior segregação das redes do estado de repouso comparados a controles de base populacional, corroborando a hipótese etiológica da Esquizofrenia de uma desconectividade funcional do cérebro. A rede sensório-motor mão surpreendentemente foi a rede com maior número de alterações, apontando a necessidade de mais estudos sobre a mesma. Os irmãos não apresentaram um padrão de conexões do repouso diferente dos controles, não corroborando as hipóteses de que tal grupo apresentaria um padrão intermediário entre pacientes e controles. CONCLUSÃO: Os achados apontam para um uma topologia cerebral amplamente prejudicada já no início da psicose, com uma maior segregação entre as redes do estado de repouso em pacientes de primeiro episódio psicótico. / INTRODUCTION: Psychiatric disorders with psychotic symptoms bring significant occupational and social harm to their patients, with increased mortality and morbidity. These disorders have been studies as changes in the functional connectivity patterns in resting state brain networks. However, reports are more frequently made in chronic patients, with a scarce literature from first episode psychosis patients, mostly not making intra-networks comparison. OBJECTIVE: This was an exploratory study that had the objective of characterize the brain functional connectivity of resting networks in first episode psychosis patients through functional magnetic resonance imaging compared to siblings and to population based controls. METHODS: Final sample consisted of 38 first episode psychosis, 13 siblings and 41 population-based controls. Functional magnetic resonance images were collected in first episode psychosis, siblings and population based controls. Functional connectivity was obtained through the Pearson Correlation Coefficient of 264 regions of interest BOLD signal time series´. Comparison of functional connectivity among groups of participants was made using Partial Least Square method. Behavior Partial Least Square was performed to seek for a pattern associated with illness severity, pharmacological treatment time and duration of untreated psychosis. The statistical analysis was conducted with 10,000 permutations and bootstrap considering significant values of p<0.05. RESULTS: Aberrant network connections were mostrly due to changes of positive correlation to negative correlation in patients compared to controle. The majority of altered connections were found in sensory-motor network, DMN and visual network. The areas most affected were right frontal lobe. It was not found a functional connectivity pattern associated with illness severity, treatment time and duration of untreated psychosis. A tendency difference was found in the connectivity pattern between siblings and patients. No different connectivity pattern was found between siblings and controls. DISCUSSION: First episode psychosis presented more segregated resting state networks than controls, reinforcing the disconnectivity etiology hypothesis for schizophrenia. An unexpected result was sensory-motor hand network being the network with more altered connections, pointing to the need of more studies to comprehend it. The sibling group did not differ from the control group, not corroborating the hypotheses that such a group would present an intermediate pattern between patients and controls. CONCLUSION: The findings point to a largely impaired brain topology already at the beginning of the psychosis, with greater segregation between resting state networks in patients with first episode psychosis.

La neuromodulation apporte une extraordinaire richesse à la dynamique des réseaux de neurones. Parmi les neuromodulateurs du système nerveux central, la noradrénaline permettrait de faciliter l'adaptation du comportement face aux variations des contraintes environnementales en modulant l'attention, cette fonction au coeur de la cognition qui nous permet de sélectionner l'information la plus pertinente en fonction de notre but. Ce processus complexe qui opère à chaque instant à la fois dans l'espace et le temps, constitue une étape essentielle dans cette adaptation comportementale. Cependant, à ce jour, les mécanismes par lesquels ce neuromodulateur exerce ses effets sur le cerveau sain demeurent mal connus. Mon travail de thèse a pour objectif d'examiner les déterminants comportementaux et les marqueurs neuronaux de l'effet stimulant des agonistes noradrénergiques. La question posée était : "Comment la noradrénaline agit-elle pour optimiser l'attention?" Pour répondre à cette question, j'ai choisi de combiner la pharmacologie, l'analyse du comportement, et l'imagerie par résonnance magnétique fonctionnelle chez le singe. Un des principaux résultats de mes travaux est que l'administration d'agents noradrénergiques induit une large réorganisation des réseaux cérébraux, qui pourrait être à l'origine de l'optimisation des réponses comportementales observées parallèlement / Neuromodulation provides an extraordinary wealth to the dynamics of neural networks. Among the neuromodulators of the central nervous system, noradrenaline would facilitate behavioral adaptation facing variations of environmental constraints by modulating attention, this function at the heart of cognition that allows us to select the most relevant information based our goal. This complex process that operates at every moment both in space and time, is an essential step in this behavioral adaptation. However, to date, the mechanisms by which this neuromodulator exerts its effects on healthy brain remain unknown. My thesis aims to examine the behavioral and neural markers of the boosting effect of noradrenergic agonists. The question asked was: "How does noradrenaline optimize attention?" To answer this question, I chose to combine pharmacology, behavior analysis, and functional Magnetic Resonance Imaging in monkeys. One of the main results of my work is that the administration of noradrenergic agents induced a large-scale brain networks reorganization, which could be responsible for optimizing behavioral responses observed in parallel

Esta dissertação desenvolve e aplica métodos para caracterizar regiões cerebrais durante o estado de repouso. Utilizam-se grafos para representar a inter-dependência temporal de sinais de ressonância magnética funcional provenientes de regiões cerebrais distintas. Vértices representam regiões cerebrais e arestas representam a conectividade funcional. Buscando superar os problemas de visualização e interpretação desta forma de representação, elaboram-se métodos quantitativos para caracterizar padrões de conectividade entre regiões cerebrais. Para cada sujeito analisado: 1) Faz-se a redução da dimensionalidade espacial das imagens de ressonância magnética funcional respeitando os limites anatômicos das regiões cerebrais. 2) Estima-se a rede de conectividade funcional pela coerência direcionada entre pares de regiões distintas. 3) Constrói-se um grafo direcionado e pesado pela medida de conectividade. 4) Quantificam-se os vértices por índices e faz-se o registro destes valores no espaço comum MNI. 5) Avalia-se a consistência de cada índice pelo teste não paramétrico de Friedman seguido de análises de múltiplas comparações. A análise de 198 imagens de sujeitos sadios produziu resultados consistentes e biologicamente plausíveis. Em sua maioria, revelou regiões associadas a conceitos anatômicos de conectividade e integração cerebral. Embora de implementação simples, o método proporciona informações de natureza dinâmica sobre as relações entre diferentes regiões cerebrais e pode ser utilizado futuramente para estudar e entender desordens psiquiátricas/neurológicas. / This dissertation develops and applies methods to characterize brain regions during resting state. Graphs are used to represent functional MRI connectivity from different brain regions. Vertices represent brain regions and edges represent connectivity. To overcome the visualization and interpretation problems of this form of representation, we developed quantitative methods to characterize its patterns. Methods: For each subject: 1) The reduction of spatial dimensionality of functional magnetic resonance imaging is carried out taking into account the anatomic limits of the brain regions. 2) The network is estimated by directed coherence between pairs of separate regions. 3) A directed graph with weights on its edges is constructed using the later connectivity measure. 4) The vertices are quantified by indexes that are registered in the MNI common space. 5) The consistency of each index is evaluated by the nonparametric Friedman followed by Post-Hoc analysis. Results: The analysis of 198 images of healthy subjects produced consistent and biologically plausible results. They revealed anatomical regions involved in brain integration. Conclusion: The method provides information about the dynamic nature of the relationships between different brain regions and can be used in future clinical studies to understand psychiatric and neurological disorders.

Large scale functional brain networks, defined by synchronized spontaneous oscillations between spatially distinct anatomical regions, are essential to brain function and have been implicated in disease states, cognitive capacity, and many sensing and motor processes. In this work, we sever the corpus callosum in the rodent model to determine if structural connectivity (specifically the primary interhemispheric pathway) organizes and influences bilateral functional connectivity and brain-wide spatiotemporal dynamic activity patterns. Prior to the callosotomy work, resting state brain networks were evaluated using blood oxygen level dependent (BOLD) and cerebral blood volume (CBV) magnetic resonance imaging contrast mechanisms, and revealed that BOLD and CBV provide highly similar spatial maps of functional connectivity; however, the amplitude of BOLD connectivity was generally stronger. The effects of extended anesthetic durations on functional connectivity were also evaluated revealing extended isoflurane anesthetic periods prior to the switch to dexmedetomidine attenuates functional activity for a longer duration as compared to a shorter isoflurane paradigm. We also observed a secondary significant evolution of functional metrics occurring during long durations of dexmedetomidine use under the currently accepted and refined dexmedetomidine sedation paradigm. Taking these previous findings into account, we moved forward with the callosotomy study. Functional network integrity was evaluated in sham and full callosotomy groups using BOLD and electrophysiology. Functional connectivity analysis indicated a similar significant reduction in bilateral connectivity in the full callosotomy group as compared to the sham group across both recording modalities. Spatiotemporal dynamic analysis revealed bilaterally symmetric propagating waves of activity in the sham data, but none were present in the full callosotomy data; however, the emergence of unilateral spatiotemporal patterns became prominent following the callosotomy. This finding suggests that the corpus callosum could be largely responsible for maintaining bilateral network integrity, but non-bilaterally symmetric propagating waves occur in the absence of the corpus callosum, suggesting a possible subcortical driver of the dynamic cascading event. This work represents a robust finding indicating the corpus callosum's influence on maintaining integrity in bilateral functional networks.

Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast has become a widespread technique in brain research. The central challenge in fMRI is the detection of relatively small activity-induced signal changes in the presence of various other signal fluctuations. Physiological fluctuations due to respiration and cardiac pulsation are dominant sources of confounding variability in BOLD fMRI. This dissertation seeks to characterize and compensate for non-neural physiological fluctuations in fMRI. First, the dissertation presents an improved and generalized technique for correcting T1 effect in cardiac-gated fMRI data incorporating flip angle estimated from fMRI dataset itself. Using an unscented Kalman filter, spatial maps of flip angle and T1 relaxation are estimated simultaneously from the cardiac-gated time series. Accounting for spatial variation in flip angle, the new method is able to remove the T1 effects robustly, in the presence of significant B1 inhomogeneity. The technique is demonstrated with simulations and experimental data. Secondly, this dissertation describes a generalized retrospective technique to precisely model and remove physiological fluctuations from fMRI signal: Physiological Impulse Response Function Estimation and Correction (PIRFECT). It is found that the modeled long-term physiological fluctuations explained significant variance in grey matter, even after removing short-term physiological effects. Finally, application of the proposed technique is observed to substantially increase the intra-session reproducibility of resting-state networks.

La actividad cerebral exhibe complejos fenómenos oscilatorios similares a los que se observan en modelos de redes artificiales con osciladores acoplados. Por un lado, estudios sobre la actividad cerebral durante el reposo han demostrado la presencia de fluctuaciones lentas estructuradas y modulaciones de potencia a distintas frecuencias. Simultáneamente, estudios teóricos en el ámbito de la física muestran dinámicas similares usando osciladores acoplados. En este trabajo, por primera vez, se usan modelos de osciladores de fase en redes inspiradas en la arquitectura real del cerebro. Los resultados muestran la aparición espontánea de una dinámica similar a la observada experimentalmente. Además, esta correspondencia es comparable cuantitativamente con datos de neuroimagen, lo que sugiere procesos generales de integración subyacentes a la cognición. Por otra parte, se propone que la actividad cerebral alterada observada en algunas enfermedades psiquiátricas podría tener su origen en desconexiones estructurales que afectarían el comportamiento cooperativo de regiones corticales. / Neural activity in the brain exhibits complex oscillatory phenomena that can be compared with the ones observed in artificial network models of coupled oscillators. In particular, neuroimaging studies of brain activity during rest have reported slow spatiotemporally organized fluctuations and correlated band-limited power modulations. Simultaneously, theoretical works on the area of physics have reported similar dynamic behaviours using simple models of coupled oscillators with intermittent modular synchronization. In this work, for the first time, we use models of phase oscillators in networks inspired in the brain’s wiring architecture. Results show the spontaneous emergence of a dynamics similar to the one observed experimentally. In addition, this correspondence is quantitatively comparable to neuroimaging data, which is suggestive of general integrative processes underlying cognition. Furthermore, we propose that altered brain activity observed in some psychiatric diseases might originate from structural disconnections, which affect the cooperative behaviour of coupled cortical regions.

L'auteur n'a pas fourni de résumé en français / L'auteur n'a pas fourni de résumé en anglais

Around the world Alzheimer’s Disease (AD) is on the rise. Previous studies have shown the default mode network (DMN) sees changes with AD progression as the disease erodes away cortical areas. Aerobic exercise with significant increases to cardiorespiratory fitness could show neuro-protective changes to delay AD. This study will explore if functional connectivity changes in the DMN can be seen in a young adult sample by using group independent component analysis through FSL MELODIC. The young adult sample of 19 were selected from a larger study at the Brain Plasticity and Neuroimaging Laboratory at Boston University. The participants engaged in a twelve-week exercise intervention in either a strength training or aerobic training group. They also completed pre-intervention and post-intervention resting-state fMRI scans to evaluate change in functional connectivity in the default mode network. Cardiorespiratory fitness was assessed using a modified Balke protocol with pre-intervention and post-intervention VO2 max percentiles being used. Through two repeated-measure ANOVA analyses, this study found no significant increase in mean functional connectivity or cardiorespiratory fitness in the young adult sample. While improvements in mean VO2 max percentile and functional connectivity would have been seen with a larger sample size, this study adds to the literature by suggesting if fitness does not improve significantly, neither will functional connectivity in the default mode network.

The current study explored how hot and cool executive functions (EF) could predict resting-state connectivity of the Default Mode Network (DMN) and Central Executive Network (CEN) in a mixed clinical and typically developing sample of adolescents. It was hypothesized that hot EF would predict a quadratic, inverted U-shaped, relationship between connectivity of the major regions of the DMN: the Posterior Cingulate Cortex (PCC) and the Medial Prefrontal Cortex (MPFC). It also was hypothesized that cool EF would predict a quadratic, inverted U-shaped, relationship between the connectivity of the major regions of the CEN: the right Posterior Parietal Cortex (right PPC) and the right Dorsal Lateral Prefrontal Cortex (right DLPFC). The results suggested that hot EF, specifically emotional regulation, predicted a quadratic relationship in DMN connectivity. However, this relationship was U-shaped instead of an inverted U-shaped. Thus, participants who scored well or poorly in emotional regulation generally had higher connectivity than those with average scores in emotional regulation. There were no significant results between cool EF and the CEN. Additional exploratory analysis suggested that the main hypotheses were not driven or suppressed by group differences. Further exploration observed other brain regions involved in resting-state activity that may play a role in hot or cool EF. Overall, findings support the Internal Mentation Hypothesis of DMN activity and are indicative of a relationship between emotional regulation and DMN resting-state connectivity.