Abstract: The default mode network of the brain is a set of functionally connected regions associated with introspection and daydreaming. Recent fMRI studies have discovered that the default mode network is often perturbed in the diseased brain. For example, the default mode network is known to be modulated in dementia, ADHD, depression, and schizophrenia, among others. This has led many into believing that this network could have a role in the physiopathology of nervous system disease, or could be a useful marker of brain function. However, very few studies have yet been done which investigate how surgical lesions such as brain tumours affect the default mode network. Consequently, the goal of this project was to characterise the effect of brain tumours on the default mode network based on their location, histological type, and other parameters. / Le mode de fonctionement par défaut du cerveau est un réseau cérébral associé à la rêverie et à l’introspection. Des études récentes sur ce réseau ont découvert qu’il est perturbé dans plusieurs pathologies cérébrales. Par example, le mode de fonctionnement par défaut est modulé en démence, TDAH, dépression, schizophrénie et plusieurs autres maladies liés au cerveau. Ceci a mené à l’hypothèse que le mode de fonctionnement par défaut pourrait avoir un rôle dans la physiopathologie des maladies du système nerveux, ou pourrait être un marqueur utile du fonctionnement cérébral. Par contre, très peu d’études ont investigué l’effet de lésions chirurgicaux comme les tumeurs cérébrales sur le mode de fonctionnement par défaut. Par conséquent, le but de ce projet était de caractériser l’importance de l’histologie, de la localisation et de plusieurs autres paramètres de l’effet d’une tumeur cérébrale sur le mode de fonctionnement par défaut.

Les mutations génétiques et les conditions pathologiques affectent la connectivité functionnelle du cerveau. Nous avons combiné la mutagénèse chez la souris et l’analyse de connectivité fonctionnelle (CF) par imagerie en Resonance Magnétique Nucléaire (IRM) pour déterminer l’impact de la délétion du gène codant pour le récepteur orphelin GPR88 sur la CF du cerveau entier. En utilisant une approche non biaisée, nous avons découvert que la délétion génétique chez la souris altère fortement le Default Mode Network, une caractéristique de nombreuses maladies psychiatriques. Nous avons aussi observé des modifications importantes de la connectivité des cortex moteurs et somatosensoriels,et du striatum en accord avec le pattern d’expression du récepteur. Enfin, une analyse par régions d’intérêt montre une perturbation importante du réseau mesocorticolimbic, qui pourrait expliquer la tendance de ces animaux à consommer de fortes quantités d’alcool. La concordance entre les altérations de CF et celles du comportement des animaux GPR88 knockout positionnent ce récepteur comme une cible prometteuse pour le traitement de maladies psychiatriques. / Pathological agitations of the brain and the expression or mutation of single gene affect overall brain connectivity. Here we combined mouse mutagenesis with functional and structural MRI and explored mouse whole brain connectivity maps non-invasively in response to the inactivation of Gpr88 gene. We perceived robust modifications in the default mode network which is considered a hallmark of many psychiatric conditions, followed by sensori-motor network allied to sensorimotor gating deficiency underlying hyperactivity phenotype in Gpr88-/- mice. In addition, hippocampal and dorsal striatum functional connectivity perturbations might underlie learning deficiency and weakened amygdala connectivity with cortex and striatum might suggest triggering of risk-taking behavior previously observed in these animals. Moreover, Gpr88 deletion strongly modifies the reward network leading Gpr88-/- mice vulnerable to alcohol intake. This is the first evidence of Gpr88 involvement in reshaping the mouse brain connectome. The concordance between connectivity alterations and behavior deficits posits Gpr88 as a potential target for psychiatric disorders.

This study investigated the effects of lesion presence within larger brain networks (e.g., default mode network (DMN), salience network (SN), and mentalizing network (MN)) in the chronic phase of a pediatric traumatic brain injury (TBI) and the effect on social function. We compared children with a TBI to children with an orthopedic injury (OI) with three different aims. The first aim was to determine whether network volume differed by group (e.g., TBI vs. OI). Second, investigate if lesion presence in a sub component region of the network resulted in total network volume loss for that network. Finally, learn whether network volume would predict outcome on the Behavior Assessment System for Children, Second Edition (BASC-2). Approximately 184 participants (65% male; 70% Caucasian) between the ages of 6-17 years completed testing and a structural MRI scan in the chronic stage (at least one-year post-injury) of the injury. Injury severity included complicated mild, moderate, and severe TBI. Radiological findings were analyzed using recommendations from the Common Data Elements' core (presence or absence of a lesion) and supplementary (lesion type and location) recommendations. Volumetrics for all participants were obtained with FreeSurfer to quantify total network volumes for the DMN, SN, and MN. The parent of each participant completed a behavioral measure for externalizing and internalizing behaviors. Three sets of statistical analyses were completed, including multivariate analysis of covariance, analysis of covariance, and multiple regression, for each of the three aims of the study, respectively. There were significant differences in total DMN volume between the two groups and participants with lesions solely in the MN had lower total MN volume. Moreover, lower total MN volume was associated with worse functioning on measures of externalizing and internalizing behaviors. The larger implications, including developmental and social implications, of these findings are discussed.

Psychiatry is in a crisis. Mental health disorders are on the rise worldwide and there are currently not enough efficient treatment methods that would meet the patients’ needs. Hence, the societal and economic costs of mental health problems are enormous, as well as the suffering of individuals afflicted by mental health problems. Lysergic acid diethylamide (LSD) and psilocybin are substances that create an altered state of consciousness characterized by altered sensory perception and on some occasions, ego-dissolution, and mystical experiences. In recent studies, LSD and psilocybin have been shown to carry significant therapeutic potential in the treatment of depression and anxiety disorders in conjunction with psychotherapy. The therapeutic effects of LSD and psilocybin have also been shown to persist for between 3-12 months post-treatment. LSD and psilocybin, like other classical hallucinogens, increase serotonin availability, which has been suggested to attenuate symptoms of anxiety and depression. In addition, LSD and psilocybin alter the activity of the default mode network, which has been suggested to be overly active in depressed and anxious patients. This essay is a literature review of the neural mechanisms of LSD and psilocybin, their potential therapeutic effects in the treatment of depressive and anxiety disorders, and how insights about said neural mechanisms may be useful in understanding the possible application of psychedelics in the treatment of depressive and anxiety disorders. In sum, recent studies have provided converging and convincing evidence on therapeutic potential of LSD and psilocybin. Yet, few conclusions on the exact neural mechanisms of how LSD and psilocybin alleviate depressive and anxiety symptoms can be made. Although the future of this research field looks promising, archaic national- and international regulations continue to be a hindrance to research into psychedelic drugs. Yet, due to the psychiatric crisis and the promising results so far, more studies in this field are warranted.

Background: Methamphetamine (MA) abuse is a global crisis that exacerbates sociopolitico-economic burdens in South Africa. MA use is associated with a myriad of neural abnormalities of structure and function, with associated neurocognitive deficits, particularly executive function (EF). Working memory (WM) training has been identified as a potential adjunct to treatment of substance use disorder (SUD) to improve EF in the hope of reducing relapse rates. Neuroimaging suggests MA alters intrinsic resting state functional connectivity (rsFC), and this may contribute to neuropsychological deficits observed in methamphetamine use disorder (MUD). Methods: This nested study analysed data described in Brooks et al. (2016), in which WM training was used as an adjunct to inpatient treatment of MUD. Healthy controls (HC, N = 25) were compared to two MUD groups, one receiving treatment as usual (TAU, N = 17), and one receiving additional cognitive training (CT, N = 24) in the form of a modified version of the ‘N-back' task (C-Ya). This task was also used to assess WMA in the neural scanner, using conditions of 0-back and 1-back across groups. The current research explored these data in a novel manner through examining rsFC. Hypotheses: It was predicted that: 1) HC and MUD participants would differ on measures of WMA, but WMA would improve in MA groups at follow-up compared to baseline and this would be augmented in the CT group; 2) rsFC networks of neural regions supporting WM would be predictive of ability to perform well and improve on WM tasks; and 3) MA groups would display heightened rsFC activity within and between resting state neural networks of the default mode network (DMN) and canonical cognitive control networks (CCNs). Results: Significant differences were observed between HC and MA groups in race and level of education, but not on WMA as tested in the scanner. The CT group, who completed WMA 3-back conditions, demonstrated significant improvement on this task post- intervention. Exploratory regression models showed the WM rsFC network did not demonstrate significant relationships with any clinical, demographic, or WM variables when controlling for multiple comparisons. Heightened connectivity within and between the DMN and CCNs was observed in the MUD compared to the HC group, which provided support for hypothesis 3. Exploratory multivariate regression models demonstrated race, age, education, duration of drug use, and an interaction of group and abstinence may impact rsFC in these networks. Post-hoc analyses identified pairwise network combinations affected by these variables. Conclusions: Despite limitations of this small study, it offers tentative preliminary insights into the largely unexplored field of rsFC in MA populations. This study supports limited research demonstrating hyperconnectivity within and between CCNs and DMN of MA users. This study also offers support for recent research suggesting that easier conditions of the Nback task may not reliably test all aspects of WM function. Exploratory analyses of covariates potentially affecting rsFC provide a platform for directions of future research.

京都大学 / 0048 / 新制・課程博士 / 博士(教育学) / 甲第20127号 / 教博第204号 / 新制||教||167(附属図書館) / 京都大学大学院教育学研究科教育科学専攻 / (主査)准教授 野村 理朗, 教授 齊藤 智, 教授 Emmanuel MANALO / 学位規則第4条第1項該当 / Doctor of Philosophy (Education) / Kyoto University / DGAM

The default mode network (DMN) is a highly cited neural network whose functional roles are not well understood. Until recently, event related fMRI experiments used to study the DMN could only be conducted in an open-loop format. The purpose of this study was to demonstrate the potential statistical advantages of real-time fMRI studies to conduct closed-loop experiments to directly test putative DMN functions. Using both fMRI simulations and large archival datasets, we demonstrate that open-loop designs are less statistically powerful than closed-loop experiments that can trigger stimuli at controlled levels of brain activity. When simulating event scheduling on resting state data, DMN levels were normally distributed, but the event timing proved to be ineffective in capturing the highest and lowest DMN values on average across subjects. Statistical differences in DMN levels collected by the Human Connectome Project-Aging (HCP-A) during a Go/NoGo task were also reported, along with the network's distributional effects across subjects. When examining DMN levels in 136 subjects more prone to commission errors the mean DMN levels were reported to be higher during and prior to incorrect NoGo responses. Exploring DMN levels in these same individuals reacting to a Go task also revealed differing measurement patterns when compared to all 711 subjects in the study. Additionally, the distribution of total DMN levels across all participants, as well as during a Go or NoGo trial, showed a shift in the mean towards deactivation. Furthermore, the peak at this location was greater and revealed that increased sampling occurred at the mean and under sampling at the tails. Overall, the cumulative findings in this study were successful in providing statistical arguments to support propositions for more powerful closed-loop experimentation in fMRI. / Master of Science / Activity in a neural network is observed through the use of functional MRI (fMRI) by tracking higher levels of oxygenated blood to that region when active and lower quantities when inactive. Neural networks vary in their responsibilities, thus fMRI tasks are designed to trigger a response based on the functional role of the network. This can be exemplified by studying the blood flow to default mode network (DMN), a network responsible for mind wandering, during a task that requires focus. Researchers can then correlate moments of high activity, which indicates a greater degree of mind wandering, or low activity to a correct or incorrect response to the task. Unfortunately, the timing in which a task is presented to the participant is predetermined prior to the subject entering the MRI making it difficult to capture a correct or incorrect response at the precise moment of activation or deactivation. This concept is known as open-loop and often collects data at moments of neutral activity, neither high nor low. In contrast, a closed-loop design allows a researcher to monitor the DMN's activation levels in real time and present the task at a desired time. This provides more useful data to the experimenter as all recorded responses to the task correlate with exact moments of high and low activation. This makes claims about the neural network's role statistically more powerful as there is a greater quantity of data at these moments rather than during a neutral activation state. The purpose of this thesis is to provide statistical arguments that support propositions for more powerful closed-loop experimentation in fMRI.

Le cerveau présente des fluctuations de son activité qui reflètent différents niveaux d’engagement avec le monde extérieur. Le traitement des stimuli externes n’est pas seulement associé avec une augmentation du métabolisme cérébrale, mais également avec une désactivation importante dans un ensemble des structures spécifiques connus sous le nom de ‘Default-Mode Network’ (DMN, réseau par défaut). Le rôle du DMN reste énigmatique en partie parce que ses corrélats électrophysiologiques et sa dynamique temporelle sont encore mal compris. En utilisant des enregistrements éléctrophysiologiques intracrânien chez le patient épileptique, nous démontrons que la population neuronale de ce réseau montre des suppressions de l’activité gamma (60-140 Hz). Plus important, nous montrons de quelle manière le profil temporale (en millisecondes) et l’amplitude de cette désactivation sont étroitement corrélés avec la difficulté de la tâche et la performance individuelle. Les résultats mettent également en évidence que pendant une tâche attentionnelle, une activation soutenue dans le temps de la bande gamma est présente dans un large réseau, alors que des activations transitoires sont spécifiques aux régions temporale et occipitale. Nos résultats révèlent ainsi un rôle essentiel des mécanismes d’activation et de désactivation des oscillations large bande gamma dans l’exécution d’un comportement orienté vers un but. / The brain displays moment-to-moment activity fluctuations that reflect various levels of engagement with the outside world. Processing external stimuli is not only associated with increased brain metabolism but also with prominent deactivation in specific structures, collectively known as the default-mode network (DMN). The role of the DMN remains enigmatic partly because its electrophysiological correlates and temporal dynamics are still poorly understood. Using unprecedented wide-spread depth recordings in epileptic patients, undergoing intracranial EEG during pre-surgical evaluation, we reveal that DMN neural populations display task-related suppressions of gamma (60-140 Hz) power and, critically, we show how millisecond temporal profile and amplitude of gamma deactivation tightly correlate with task demands and subject performance. The results show also that during an attentional task, sustained activations in the gamma band power are presented across large cortical networks, while transient activations are mostly specific to occipital and temporal regions. Our findings reveal a pivotal role for broadband gamma modulations in the interplay between activation and deactivation networks mediating efficient goal-directed behavior

Attention is a key mental function in everyday life, but unfortunately we easily get distracted. The brain correlates underlying sustained attention, the so-called sustained attention network (SAN), have been well identified, as have the brain correlates underlying mind-wandering, the so-called default mode network (DMN). Nevertheless, even though we know about the underlying brain processes, this knowledge has not yet been translated in advanced brain-based attention training protocols. Here we proposed to use a novel brain imaging technique based on real-time functional magnetic resonance imaging (fMRI) to provide individuals with information about ongoing levels of activity in the attention and the default mode networks. To the best of our knowledge, this is the first study to show that, with the help of that fMRI-neurofeedback, individuals can learn how to improve controlling of, at the same time, SAN activation and DMN deactivation. This learning process was explained mainly in terms of DMN deactivation. Behavioral effects were observed when separating a group with the best learners in an overall measure of attention and specifically in the task-switching ability, controlled by a test-retest group performing the same behavioral tests battery. Neurofeedback-induced functional connectivity changes were also observed in multiple brain regions positively and negatively related to attention. Although the behavioral effects were no longer present two months after training, participants still held the learned ability of controlling self-regulation of the concerned networks. This approach potentially provides a non-invasive and non-pharmacological tool to deliver general enhancements in the attention ability for healthy subjects and it can be potentially beneficial to many neurological and psychiatric patients. We also show in this thesis compelling evidence that brain regions definition and other experimental parameters are crucial for inducing learning of self-regulation via fMRI-neurofeedback, in a similar study also considering differential signal of attention-related competitive networks. We finally present Personode, a useful, easy to use, and open access toolbox to neuroimaging researchers, for independent component analysis maps classification into canonical resting-state networks and regions-of--interest definition in individual and group levels. We also show that the toolbox leads to better results for task-induced activation and functional connectivity analyses. / A atenção é uma função mental crucial na vida cotidiana, mas infelizmente distrai-se facilmente. Os fundamentos cerebrais que sustentam a atenção, a chamada rede de atenção, foram satisfatoriamente identificados, assim como os fundamentos cerebrais que sustentam a divagação, a chamada rede de modo padrão. Entretanto, embora tais processos sejam conhecidos, este conhecimento ainda não foi transformado em protocolos avançados de treinamento de atenção baseado na atividade cerebral. Portanto, é proposto o uso de uma nova técnica baseada em imageamento por ressonância funcional (fMRI) em tempo real para proporcionar aos indivíduos informação sobre os níveis de atividade cerebral atuais nas redes de atenção e de modo padrão. Segundo nosso conhecimento atual, esse é o primeiro estudo a mostrar que, com o auxílio do neurofeedback baseado em fMRI, indivíduos podem aprender como melhorar o controle da ativação da rede de atenção e da desativação da rede de modo padrão ao mesmo tempo. Este processo de treinamento poderia ser explicado principalmente em termos da desativação da rede de modo padrão. Efeitos comportamentais foram observados, ao separar um grupo com os melhores aprendizes, em uma medida de atenção geral e, especificamente, na habilidade de alternação de tarefas, controlado por um grupo teste-reteste realizando a mesma bateria de testes comportamentais. Alterações em conectividade funcional induzidas por neurofeedback foram também reveladas em múltiplas regiões cerebrais positiva e negativamente relacionadas à atenção. Embora os efeitos comportamentais não puderam ser constatados depois de dois meses após o treinamento, os participantes ainda mantiveram a habilidade de controlar a autorregulação das redes em questão. Esse método provê uma ferramenta não-invasiva e não-farmacológica para proporcionar melhorias gerais na habilidade de atenção para sujeitos saudáveis, o que pode ser potencialmente benéfico para muitos pacientes de desordens neurológicas e psiquiátricas. Nesta tese, são mostradas evidências convincentes de que a definição de redes cerebrais e outros parâmetros experimentais de neurofeedback baseado em fMRI são decisivos para a indução do aprendizado de autorregulação, em um estudo similar, também considerando o sinal diferencial de redes competitivas relacionadas à atenção. Finalmente, é apresentado Personode, uma ferramenta útil, de fácil utilização e de livre acesso direcionado a pesquisadores em neuroimagem, para classificação de mapas produzidos por uma análise de componentes independentes em redes de repouso canônicas e definições de regiões de interesse em níveis individuais e de grupo. É também mostrado que a ferramenta conduz a melhores resultados para análises de ativação induzida à tarefa e conectividade funcional.

The brain displays moment-to-moment activity fluctuations that reflect various levels of engagement with the outside world. Processing external stimuli is not only associated with increased brain metabolism but also with prominent deactivation in specific structures, collectively known as the default-mode network (DMN). The role of the DMN remains enigmatic partly because its electrophysiological correlates and temporal dynamics are still poorly understood. Using unprecedented wide-spread depth recordings in epileptic patients, undergoing intracranial EEG during pre-surgical evaluation, we reveal that DMN neural populations display task-related suppressions of gamma (60-140 Hz) power and, critically, we show how millisecond temporal profile and amplitude of gamma deactivation tightly correlate with task demands and subject performance. The results show also that during an attentional task, sustained activations in the gamma band power are presented across large cortical networks, while transient activations are mostly specific to occipital and temporal regions. Our findings reveal a pivotal role for broadband gamma modulations in the interplay between activation and deactivation networks mediating efficient goal-directed behavior