No description available.

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.

Human infants have been shown to have an innate capacity to acquire their mother tongue. In recent decades, the advent of the functional magnetic resonance imaging (fMRI) technique has made it feasible to explore the neural basis underlying language acquisition and processing in children, even in newborn infants (for reviews, see Kuhl & Rivera-Gaxiola, 2008; Kuhl, 2010) . Spontaneous low-frequency (< 0.1 Hz) fluctuations (LFFs) in the resting brain have been shown to be physiologically meaningful in the seminal study (Biswal et al., 1995) . Compared to task-based fMRI, resting-state fMRI (rs-fMRI) has some unique advantages in neuroimaging research, especially in obtaining data from pediatric and clinical populations. Moreover, it enables us to characterize the functional organization of the brain in a systematic manner in the absence of explicit tasks. Among brain systems, the language network has been well investigated by analyzing LFFs in the resting brain. This thesis attempts to investigate the functional connectivity within the language network in typically developing preschool children and the covariation of this connectivity with children’s language development by using the rs-fMRI technique. The first study (see Chapter 2.1; Xiao et al., 2016a) revealed connectivity differences in language-related regions between 5-year-olds and adults, and demonstrated distinct correlation patterns between functional connections within the language network and sentence comprehension performance in children. The results showed a left fronto-temporal connection for processing syntactically more complex sentences, suggesting that this connection is already in place at age 5 when it is needed for complex sentence comprehension, even though the whole functional network is still immature. In the second study (see Chapter 2.2; Xiao et al., 2016b), sentence comprehension performance and rs-fMRI data were obtained from a cohort of children at age 5 and a one-year follow-up. This study examined the changes in functional connectivity in the developing brain and their relation to the development of language abilities. The findings showed that the development of intrinsic functional connectivity in preschool children over the course of one year is clearly observable and individual differences in this development are related to the advancement in sentence comprehension ability with age. In summary, the present thesis provides new insights into the relationship between intrinsic functional connectivity in the brain and language processing, as well as between the changes in intrinsic functional connectivity and concurrent language development in preschool children. Moreover, it allows for a better understanding of the neural mechanisms underlying language processing and the advancement of language abilities in the developing brain.

Extracting structure from initially incomprehensible streams of events is fundamental to a range of human abilities: from navigating in a new environment to learning a language. These skills rely on our ability to extract spatial and temporal regularities, often with minimal explicit feedback, that is known as statistical learning. Despite the importance of statistical learning for making perceptual decisions, we know surprisingly little about the brain circuits and how they change when learning temporal regularities. In my thesis, I combine behavioural measurements, Diffusion Tensor Imaging (DTI) and resting-state fMRI (rs-fMRI) to investigate the structural and functional circuits that are involved in statistical learning of temporal structures. In particular, I compare structural connectivity as measured by DTI and functional connectivity as measured by rs-fMRI before vs. after training to investigate learning-dependent changes in human brain pathways. Further, I combine the two imaging modalities using graph theory and regression analyses to identify key predictors of individual learning performance. Using a prediction task in the context of sequence learning without explicit feedback, I demonstrate that individuals adapt to the environment’s statistics as they change over time from simple repetition to probabilistic combinations. Importantly, I show that learning of temporal structures relates to decision strategy that varies among individuals between two prototypical distributions: matching the exact sequence statistics or selecting the most probable outcome in a given context (i.e. maximising). Further, combining DTI and rs-fMRI, I show that learning-dependent plasticity in dissociable cortico-striatal circuits relates to decision strategy. In particular, matching relates to connectivity between visual cortex, hippocampus and caudate, while maximisation relates to connectivity between frontal and motor cortices and striatum. These findings have potential translational applications, as alternate brain routes may be re-trained to support learning ability when specific pathways (e.g. memory-related circuits) are compromised by age or disease.

Près de 30% des patients ayant survécus à un AVC, développent une dépression (DPAVC) dont le retentissement sur la qualité de vie peut être majeur. Sa physiopathologie est encore méconnue et les critères diagnostiques ne sont pas clairement définis. Notre objectif est d'identifier des facteurs précoces neuropsychologiques et de neuroimagerie prédictifs d'une dépression 3 mois après l’AVC.Cinquante-cinq patients présentant un premier AVC, sans antécédent neurologique ou psychiatrique ont été inclus. Dix jours après l’AVC, la sévérité des symptômes dépressifs et anxieux a été évaluée d’une part, par les échelles standard d’Hamilton et d’autre part, en vie quotidienne durant 7 jours, par la méthode d’échantillonnage des expériences (ESM). Au même temps, un examen d’IRM multimodale a été réalisé (IRM fonctionnelle de repos, DTI et 3D T1) afin d'évaluer les modifications anatomo-fonctionnelles de l’organisation cérébrale. Trois mois après l’AVC, une mesure standard de la sévérité des symptômes dépressifs et anxieux est à nouveau effectuée. A partir de ces données nous avons exploré la relation existant entre 1/ la sévérité des symptômes dépressifs et les données IRM 2/ la sévérité des symptômes dépressifs et les données ESM 3/ la sévérité des symptômes dépressifs mesurée par ESM et les modifications anatomo-fonctionnelles cérébrales. Nous avons mis en évidence une modification de la connectivité fonctionnelle entre les régions postérieures du réseau en "default mode", de la même façon que dans les dépressions majeure et vasculaire ; et entre le cortex temporal moyen et ce réseau. A la phase aigue de l’AVC, 2 profils symptomatologiques se distinguent : le premier est caractérisé par une grande fatigue et une forte anhédonie, le deuxième est définit par de la tristesse, une forte anxiété, des pensées négatives et une forte réactivité émotionnelle. Ce dernier est associé au risque de DPAVC à 3 mois. Enfin, nous avons montré que les modifications fonctionnelles du DMN prédictives de l’AVC étaient associées à la réactivité émotionnelle, alors que le volume de substance grise du cervelet était corrélé à la fréquence des pensées positives et négatives.En conclusion, la physiopathologie de la DPAVC présenterait des similitudes avec celle de la dépression majeure et de la dépression vasculaire, mais aussi des différences comme l’engagement du cortex temporal moyen au sein du réseau en « default mode ». De plus, cette étude suggère qu'à côté de l'implication de la lésion cérébro-vasculaire, des critères de vulnérabilité psychobiologiques antérieurs à l’AVC influenceraient la survenue d’une dépression. / 30% of stroke survivors will experience Post-Stroke Depression (PSD) that is associated to a poor quality of life. PSD is still under-diagnosed due to the absence of clear diagnostic criteria and its pathophysiology remains unknown. The aim of this study was to identify early imaging and psychiatric risk factors of depression 3 months after stroke. Patients with a first ischemic stroke, without any neurologic and psychiatric history were included. Daily-life symptoms were evaluated using ESM 10 days after stroke. Brain MRI acquisition was performed at 10 days after stroke including DWI, FLAIR/T2, resting state fMRI and anatomical sequences. We explored the association between 1/ the severity of depressive symptoms and MRI data 2/ the severity of depressive symptoms and ESM data 3/ the severity of depressive symptoms measured by ESM and MRI data.Results revealed a modification of the functional connectivity between posterior structures of the DMN (Default Mode Network) and between the middle temporal cortex and the DMN. In the acute phase, depressed patients presented either high fatigue and anhedonia or another profile including high anxiety, negative thoughts and emotional reactivity which is associated to the risk of depression 3 months after stroke. Moreover, we demonstrated that functional connectivity modifications within the DMN and the cerebellum grey matter were respectively associated to emotional reactivity and the frequency of positive and negative thoughts.In conclusion, modifications of the DMN were implicated in the physiopathology of PSD in the same way that major or vascular depression, with a specificity represented by the new contribution of the middle temporal cortex within the DMN. Furthermore, this study suggests that more than a stroke lesion, anterior psychobiological vulnerabilities of an individual patient could mediate PSD occurrence.

Human infants have been shown to have an innate capacity to acquire their mother tongue. In recent decades, the advent of the functional magnetic resonance imaging (fMRI) technique has made it feasible to explore the neural basis underlying language acquisition and processing in children, even in newborn infants (for reviews, see Kuhl & Rivera-Gaxiola, 2008; Kuhl, 2010) . Spontaneous low-frequency (< 0.1 Hz) fluctuations (LFFs) in the resting brain have been shown to be physiologically meaningful in the seminal study (Biswal et al., 1995) . Compared to task-based fMRI, resting-state fMRI (rs-fMRI) has some unique advantages in neuroimaging research, especially in obtaining data from pediatric and clinical populations. Moreover, it enables us to characterize the functional organization of the brain in a systematic manner in the absence of explicit tasks. Among brain systems, the language network has been well investigated by analyzing LFFs in the resting brain. This thesis attempts to investigate the functional connectivity within the language network in typically developing preschool children and the covariation of this connectivity with children’s language development by using the rs-fMRI technique. The first study (see Chapter 2.1; Xiao et al., 2016a) revealed connectivity differences in language-related regions between 5-year-olds and adults, and demonstrated distinct correlation patterns between functional connections within the language network and sentence comprehension performance in children. The results showed a left fronto-temporal connection for processing syntactically more complex sentences, suggesting that this connection is already in place at age 5 when it is needed for complex sentence comprehension, even though the whole functional network is still immature. In the second study (see Chapter 2.2; Xiao et al., 2016b), sentence comprehension performance and rs-fMRI data were obtained from a cohort of children at age 5 and a one-year follow-up. This study examined the changes in functional connectivity in the developing brain and their relation to the development of language abilities. The findings showed that the development of intrinsic functional connectivity in preschool children over the course of one year is clearly observable and individual differences in this development are related to the advancement in sentence comprehension ability with age. In summary, the present thesis provides new insights into the relationship between intrinsic functional connectivity in the brain and language processing, as well as between the changes in intrinsic functional connectivity and concurrent language development in preschool children. Moreover, it allows for a better understanding of the neural mechanisms underlying language processing and the advancement of language abilities in the developing brain.

No description available.

L'activité neuronale partagée entre les différentes régions cérébrales permet d'estimer les patrons d'activation fonctionnelle à l'échelle de réseaux distribués, même en l'absence de paradigme. Constamment rapportés dans la population saine, les réseaux fonctionnels au repos (RSNs) peuvent être utilisés comme objet d'étude pour comprendre la contribution du développement sensoriel atypique sur la communication globale inter-réseau. À ce jour, peu d'études ont exploré l'organisation cérébrale au repos dans le contexte de la surdité. Pourtant, de multiples évidences soutiennent l'importance des entrées sensorielles en début de vie dans la consolidation de l'architecture fonctionnelle du cerveau. L'étude présentée dans ce mémoire a été développée et conceptualisée pour rendre compte de la relation entre la privation sensorielle et l'activité cérébrale spontanée entre les RSNs. À cette fin, 17 personnes avec une surdité congénitale de degré sévère à profond et 18 personnes entendantes non signeurs ont été recrutées et ont effectué 10 minutes d'enregistrement par imagerie magnétique fonctionnelle (IRMf) à l'état de repos. Les estimations de connectivité fonctionnelle de 17 RSNs extraites par une méthode de parcellisation fonctionnelle du cerveau ont été comparées entre les groupes. Le couplage entre les réseaux d'attention dorsale (DAN) et d'attention ventrale (VAN) était significativement plus élevé chez les participants qui présentent une surdité. Ces deux systèmes sont impliqués dans les tâches attentionnelles descendantes (« top-down ») et ascendantes (« bottom-up »), respectivement. Les résultats démontrent une réorganisation du cerveau au sein des réseaux associatifs et proposent une preuve potentielle des substrats neuronaux qui sous-tendraient les performances attentionnelles supérieures des personnes avec une surdité. / Neural activity shared between different brain regions allows estimation of functional activation patterns at the scale of distributed networks, even in the absence of a paradigm. Consistently reported in the healthy population, resting-state functional networks (RSNs) can be studied to understand the contribution of atypical sensory development on global inter-network communication. To date, few studies have explored brain organization at rest in the context of deafness. Yet, numerous evidence supports the importance of early sensory input in the consolidation of the brain's functional architecture. The study presented in this thesis was developed and conceptualized to report on the relationship between sensory deprivation and spontaneous brain activity between RSNs. To this end, 17 individuals with severe to profound congenital hearing loss and 18 non-signer hearing individuals were recruited and performed 10 minutes of functional magnetic imaging (fMRI) recording at rest. Functional connectivity estimates of 17 RSNs extracted by a functional brain parcellation method were compared between groups. The coupling between dorsal attention (DAN) and ventral attention (VAN) networks was significantly higher in deaf participants. These two systems are involved in topdown and bottom-up attentional tasks, respectively. The results demonstrate brain plasticity within associative networks and offer potential evidence of neural substrates that may underlie superior attentional performances observed in individuals with deafness.

Malgré le développement de nouvelles générations d’antipsychotiques, certains symptômes schizophréniques ne répondent pas à ces traitements. S’appuyant sur des hypothèses physiopathologiques sous tendant ces symptômes, de nouvelles thérapeutiques comme la thérapie de remédiation cognitive et les techniques de neurostimulation externe ont été développées. Cette approche était restée essentiellement clinique. Dans ce travail, l’étude en imagerie des mécanismes biologiques sous tendant les effets bénéfiques de ces thérapeutiques non pharmacologiques nous a permis de tester des hypothèses physiopathologiques. L’IRM fonctionnelle (IRMf) et la spectroscopie par résonance magnétique (SRM) ont été utilisées pour rechercher les effets d’une thérapie de remédiation cognitive (TRC), de la stimulation magnétique transcrânienne (TMS) et de la stimulation électrique transcrânienne en courant continu (tDCS). Nous avons mis en évidence (1) que la TRC modifie les activations cérébrales durant une tâche de mémoire de travail chez des patients schizophrènes (2) que la TMS modifie la biochimie cérébrale de la zone stimulée et de régions cérébrales profondes chez un patient schizophrène, (3) que la tDCS modifie les réseaux de connectivité fonctionnelle d’une tâche de repos chez des volontaires sains / Despite the development of new generation antipsychotic drugs, some symptoms of schizophrenia do not respond to these treatments. Based on the pathophysiological hypothesis underlying these symptoms, new therapies such as cognitive remediation therapy and neurostimulation techniques have been developed. This approach remained essentially clinical. In this work, the study of biological mechanisms tending benefits of these non-pharmacological treatment has allowed us to test these pathophysiological hypotheses. Functional MRI (fMRI) and magnetic resonance spectroscopy (MRS) were used to investigate the effects of cognitive remediation therapy (CRT), transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). We demonstrated (1) that CRT modifies cerebral activations during a working memory task in patients with schizophrenia, (2) that TMS modifies brain biochemistry of the stimulated area and of deep brain regions in a patient with schizophrenia and (3) that tDCS modifies the functional connectivity in resting state networks of healthy volunteers

Hintergrund. Exzessives Sorgen ist durch anhaltende, sich wiederholende negative Gedanken gekennzeichnet, die als aufdringlich und unkontrollierbar empfunden werden. Chronisches Sorgen kann zu einer schwer beeinträchtigenden mentalen Aktivität werden und es wird angenommen, dass es zur Entstehung, Aufrechterhaltung und Verschlechterung einer Reihe von somatischen Gesundheitsproblemen und psychischen Störungen beiträgt. Theoretische Modelle und empirische Befunde deuten darauf hin, dass exzessives Sorgen mit einer gestörten Bottom-up-Salienzverarbeitung, einer unzureichenden Top-down-Aufmerksamkeitssteuerung, Defiziten in der Emotionsregulation und abnormalen selbstreferenziellen mentalen Funktionen verbunden sind. Neuroimaging-Studien zu exzessivem Sorgen zeigen Veränderungen funktioneller Aktivierung und Konnektivität in limbischen und paralimbischen Hirnstrukturen, welche die Reaktivität auf emotionale Stimuli unterstützen, in präfrontalen Strukturen, die in Top-down-Prozesse involviert sind, welche der Aufmerksamkeitssteuerung und Emotionsregulation zugrunde liegen, und in medialen kortikalen Mittellinienstrukturen, die an selbstreferenziellen mentalen Aktivitäten beteiligt sind. Im Hinblick auf das Vorhandensein, die genaue Lokalisation der beteiligten Hirnareale und die Richtung der Effekte präsentieren diese Studien jedoch weitgehend heterogene Ergebnisse. Die hohe Variabilität der Befunde erschwert es, ein kohärentes Verständnis der neurobiologischen Mechanismen exzessiven Sorgens zu erlangen. Um dieses Verständnis zu erweitern und künftige Richtungen für die weitere Forschung auf diesem Gebiet aufzuzeigen, verfolgte die vorliegende Dissertationsschrift drei Ziele: (i) die emotionsbezogene, aufgabenbasierte fMRT-Literatur zu exzessivem Sorgen auf quantitative, datengesteuerte Weise zusammenzufassen, um konsistente funktionelle Störungen über Studien hinweg zu identifizieren; (ii) zu bestimmen, mit welchen psychologischen Prozessen die identifizierten Hirnregionen assoziiert sind, und in welchen funktionellen Hirnnetzwerken sie wirken; und (iii) Anomalien in der grundlegenden Hirnorganisation zu untersuchen, die mit exzessivem Sorgen assoziiert sind. Methoden. Eine State-of-the-Art koordinatenbasierte Meta-Analyse wurde unter Anwendung des Activation Likelihood Estimation (ALE) Algorithmus durchgeführt, um die Übereinstimmung zwischen 16 Neuroimaging-Experimenten zu bestimmen, die Veränderungen in der funktionellen Aktivität des Gehirns während der Verarbeitung emotionaler Inhalte zwischen Personen mit hoher und normaler Sorgenneigung berichten. Die identifizierten Regionen wurden mithilfe von Metadaten der funktionellen Magnetresonanztomographie (fMRT) hinsichtlich ihrer psychologischen Funktionen charakterisiert (Verhaltens-Charakterisierung). Zusätzlich wurde meta-analytic-connectivity modeling (MACM) verwendet, um ihre globalen funktionellen Konnektivitätsmuster zu bestimmen und so zugehörige Gehirnnetzwerke zu identifizieren. Schließlich wurde fMRT im Ruhezustand (resting-state) verwendet, um die funktionellen Konnektivitätsmuster zwischen 21 Personen mit hoher und 21 Personen mit normaler Sorgenneigung ohne einer aufgabenbezogenen Gehirnaktivierung zu vergleichen. Dispositionelle Sorgen wurden mit dem Penn State Worry Questionnaire als verlässliches Selbstauskunftsmaß für schwere Sorgen erhoben. Saatregion-basierte Analysen mit den meta-analytisch abgeleiteten Hirnregionen als Saatregionen und eine datengesteuerte Multi-Voxel-Pattern-Analyse (MVPA) wurden durchgeführt, um funktionelle Konnektivitätsunterschiede zwischen den beiden Gruppen zu detektieren. Darüber hinaus wurden gruppenüber-greifende Korrelationen zwischen dem aktuellen Sorgenausmaß (State-Sorgen) und den funktionellen Konnektivitätsmustern der Saat-Regionen sowie den aus der MVPA abgeleiteten Komponenten-Werten analysiert. Ergebnisse. Die Meta-Analyse ergab konvergente Anomalien bei Individuen mit hoher im Vergleich mit normaler Sorgenneigung, hauptsächlich in einem linkshemisphärischen Cluster, welcher Teile des mittleren frontalen Gyrus, des inferioren frontalen Gyrus und der anterioren Insula umfasst. Die Verhaltens-Charakterisierung zeigte, dass der identifizierte Cluster mit der Sprachverarbeitung und dem Gedächtnis assoziiert ist. Darüber hinaus ergaben die meta-analytischen Konnektivitätskartierungen starke funktionelle Verbindungen zwischen den beobachteten konvergenten Regionen und frontalen, temporalen und parietalen Hirnregionen, die sich mit Teilen von zwei verhaltensrelevanten Hirnnetzwerken überschneiden, nämlich dem Salienznetzwerk (SN) und dem Default-Netzwerk (DN). Die resting-state funktionellen Konnektivitätsanalysen zeigten keine Unterschiede zwischen Individuen mit hoher und normaler Sorgenneigung und auch keine Korrelationen zwischen den resting-state funktionellen Konnektivitätsmustern und State-Sorgen, weder mit dem auf Saatregionen basierenden Ansatz noch mit dem MVPA-Ansatz. Schlussfolgerungen. Die Ergebnisse dieser Dissertationsschrift deuten darauf hin, dass exzessives Sorgen mit einer gestörten Funktion in Hirnarealen zusammenhängt, die mit bottom-up und top-down Aufmerksamkeitssteuerung sowie Emotionserzeugung und Emotionsregulation in Verbindung gebracht werden. Die Verhaltensanalyse deckte Assoziationen zwischen dem identifizierten Cluster und der Sprachverarbeitung auf, die mit dem übermäßigen inneren Sprechen bei zu Sorgen neigenden Personen zusammenhängen könnten. Diese Assoziation ist bisher eher unbeachtet geblieben und sollte weiter erforscht werden. Darüber hinaus stellen die identifizierten Hirnregionen Schlüsselknoten in interagierenden neuronalen Netzwerken dar, die endogen und exogen orientierte Kognition unterstützen und das dynamische Zusammenspiel zwischen diesen Prozessen steuern. Ihre veränderte netzwerkübergreifende Dynamik könnte die Ursache für die Unfähigkeit von zu schweren Sorgen neigen-den Personen sein, sich von intern orientierten Kognitionen zu lösen, wenn adaptives Reagieren einen externen Fokus der Aufmerksamkeit erfordern würde. Die Nullergebnisse der Ruhezustandsanalysen könnten auf das Studiendesign zurückzuführen sein oder durch Charakteristika des Sorgens selbst verursacht werden, werden aber nicht als Beleg dafür interpretiert, dass Anomalien in der intrinsischen Konnektivität des Gehirns in Verbindung mit exzessivem Sorgen nicht vorhanden sind. Die Ergebnisse dieser Arbeit können zukünftige Forschungen anleiten, die z.B. untersuchen könnten, ob und wie sich die dynamischen zeitlichen Interaktionen innerhalb und zwischen den hier identifizierten Netzwerken in Abhängigkeit vom Schweregrad des Sorgens unterscheiden. Die ALE-Ergebnisse liefern eine A-priori-Auswahl von Hirnregionen für solche Studien. Ein besseres Verständnis der Veränderungen in den Gehirnnetzwerken, die exzessivem Sorgen zugrunde liegen, und der psychologischen Funktionen, die dadurch beeinträchtigt werden, wird Ansatzpunkte für die Verbesserung therapeutischer Interventionen liefern.:Contents TABLES VIII FIGURES IX ABBREVIATIONS X ABSTRACT 1 1 THEORETICAL BACKGROUND 6 1.1 WORRY 6 1.1.1 DEFINITION, NATURE AND FUNCTION OF WORRY 6 1.1.2 THE WORRY CONTINUUM – NORMAL VERSUS MALADAPTIVE WORRY 7 1.1.3 THE DELETERIOUS EFFECTS OF EXCESSIVE WORRY 8 1.1.4 THEORETICAL MODELS OF EXCESSIVE WORRY 11 1.2 FUNCTIONAL BRAIN NETWORKS AND EXCESSIVE WORRY 18 1.2.1 A SYSTEMS NEUROSCIENCE VIEW OF EXCESSIVE WORRY 18 1.2.2 EMPIRICAL EVIDENCE: FMRI STUDIES ON EXCESSIVE WORRY 20 1.3 RESEARCH QUESTION 32 2 STUDY I: A QUANTITATIVE META-ANALYSIS OF FMRI STUDIES INVESTIGATING EMOTIONAL PROCESSING IN EXCESSIVE WORRIERS: APPLICATION OF ACTIVATION LIKELIHOOD ESTIMATION ANALYSIS 35 2.1 ABSTRACT 36 2.2 INTRODUCTION 37 2.3 METHODS 40 2.3.1 LITERATURE SEARCH AND STUDY SELECTION 40 2.3.2 ACTIVATION LIKELIHOOD ESTIMATION 46 2.3.3 META-ANALYTIC CONNECTIVITY MODELING 47 2.3.4 ANALYSIS OF BEHAVIORAL DOMAIN PROFILES 47 2.4 RESULTS 48 2.4.1 SIGNIFICANT ALE CLUSTERS 48 2.4.2 FUNCTIONAL CONNECTIVITY OF THE DERIVED ALE-CLUSTER – MACM-ANALYSIS 51 2.4.3 FUNCTIONAL CHARACTERIZATION OF THE DERIVED ALE-CLUSTER – BEHAVIORAL ANALYSIS 54 2.5 DISCUSSION 55 2.6 CONCLUSION 59 2.7 SUPPLEMENTARY MATERIAL STUDY I: LISTING OF ALE CLUSTERS SIGNIFICANT AT P < 0.001 UNCORRECTED, CLUSTER SIZE > 100MM3 60 3 STUDY II: HIGH AND LOW WORRIERS DO NOT DIFFER IN UNSTIMULATED RESTING-STATE BRAIN CONNECTIVITY 61 3.1 ABSTRACT 62 3.2 INTRODUCTION 63 3.3 MATERIALS AND METHODS 65 3.3.1 PARTICIPANTS AND PROCEDURE 65 3.3.2 FMRI DATA ACQUISITION 66 3.3.3 SELF-REPORT ASSESSMENTS AND STATE WORRY ASSESSMENT 66 3.3.4 STATISTICAL ANALYSES 67 3.4 RESULTS 69 3.4.1 SELF-REPORT MEASURES 69 3.4.2 FMRI RESULTS 72 3.5 DISCUSSION 72 3.6 CONCLUSION 75 3.7 SUPPLEMENTARY MATERIAL STUDY II: STATE WORRY ASSESSMENT 75 4 GENERAL DISCUSSION 76 4.1 CONVERGENT ABERRANT FUNCTION IN THE MFG-IFG-INSULA-CLUSTER 76 4.2 META-ANALYTIC FUNCTIONAL CHARACTERIZATION AND CONNECTIVITY MAPPING OF THE MFG-IFG-INSULA CLUSTER 82 4.3 NO RESTING-STATE FUNCTIONAL CONNECTIVITY DIFFERENCES BETWEEN HW AND LW 84 4.4 STRENGTHS AND LIMITATIONS 87 4.5 FUTURE DIRECTIONS 90 4.6 CONCLUSION 91 REFERENCES 92 APPENDIX: DECLARATION OF HONOUR / EIGENSTÄNDIGKEITSERKLÄRUNG 131 / Background. Excessive worry is characterized by persistent, repetitive negative thoughts that are perceived as intrusive and uncontrollable. Chronic worrying can become a severely debilitating mental activity and is thought to contribute to the development, maintenance and deterioration of a range of somatic health problems and mental disorders. Theoretical accounts and empirical findings suggest that excessive worry is associated with impaired bottom-up salience-processing, insufficient top-down attentional control, deficits in emotion regulation and abnormal self-referential mental functions. Neuroimaging studies of excessive worry indicate functional activation and connectivity alterations in limbic and paralimbic brain structures that support reactivity to emotional stimuli, in prefrontal structures implicated in top-down processes underlying attentional control and emotion regulation, and in cortical midline structures involved in self-referential mental activity. However, with regard to the presence, the exact localization of the brain areas involved and the directionality of the effects, these studies have presented largely heterogenous results. The high variability of findings makes it difficult to achieve a coherent understanding of the neurobiological mechanisms of excessive worry. To extend this understanding and provide future directions for continued research in this area, the aim of this thesis was threefold: (i) to synthesize the emotional task-based fMRI literature on excessive worry in a quantitative, data-driven manner for the purpose of identifying consistent functional perturbations across studies; (ii) to determine the psychological processes with which the identified brain regions are associated and the functional brain networks in which they operate; and (iii) to examine abnormalities in basic brain organization associated with excessive worry. Methods. A state-of-the-art coordinate-based meta-analysis was conducted applying the activation likelihood estimation (ALE) algorithm to determine concordance among 16 neuroimaging experiments reporting alterations in brain functional activity during emotional processing between individuals experiencing high versus normal levels of worry. The identified regions were behaviorally characterized using functional magnetic resonance imaging (fMRI) metadata. Additionally, meta-analytic-connectivity modeling (MACM) was used to determine their global functional connectivity (FC) patterns and thus identify related brain networks. Finally, resting-state fMRI was used to compare FC patterns between 21 high and 21 low worriers in the absence of task-related brain activation. Dispositional worry was assessed using the Penn State Worry Questionnaire as a reliable self-report measure of severe worry. Seed-based analyses with the meta-analytically derived brain regions as seeds and a data-driven multi-voxel pattern analysis (MVPA) were performed to detect FC differences between the two groups. In addition, cross-group correlations between state worry levels and the FC patterns of the seed regions as well as the MVPA-derived component scores were analyzed. Results. The meta-analysis revealed convergent aberrations in high compared to normal worriers mainly in a left-hemispheric cluster comprising parts of the middle frontal gyrus, inferior frontal gyrus and anterior insula. Behavioral characterization indicated the identified cluster to be associated with language processing and memory. Furthermore, meta-analytic connectivity mapping yielded strong functional connections between the observed convergent regions and frontal, temporal, and parietal brain regions that overlap with parts of two behaviorally relevant brain networks, specifically the salience network (SN) and the default network (DN). The resting-state FC (rsFC) analyses revealed no differences between high and normal worriers and also no correlations between rsFC patterns and state worry, neither using the seed-based nor the MVPA approach. Conclusions. The results of this thesis indicate that excessive worry is related to disturbed functioning in brain areas that have been related to bottom-up and top-down attentional control as well as emotion generation and regulation. Behavioral analysis uncovered associations between the identified cluster and language processing that might be related to the exaggerated inner speech processes in worry prone individuals. This association has so far remained rather unnoticed and requires further exploration. Moreover, the identified brain regions constitute key nodes within interacting neural networks that support internally and externally oriented cognition and control the dynamic interplay among these processes. Their altered cross-network dynamics may underlie the inability of worry-prone individuals to disengage from internally oriented cognitions when adaptive responding would require an external focus of attention. The null-findings of the resting-state analyses might be due to the study design or caused by characteristics of worry itself, but are not interpreted as evidence that abnormalities in the brain's intrinsic connectivity associated with excessive worrying are absent. The results of this thesis may guide future research that could, for example, investigate whether and how the dynamic temporal interactions within and between the networks identified here differ depending on the severity of worry. The ALE results provide an a priori selection of brain regions for such studies. Increasing our understanding of the aberrations in brain networks that underlie excessive worry and the psychological functions that are impaired as a result will provide targets for improving therapeutic interventions.:Contents TABLES VIII FIGURES IX ABBREVIATIONS X ABSTRACT 1 1 THEORETICAL BACKGROUND 6 1.1 WORRY 6 1.1.1 DEFINITION, NATURE AND FUNCTION OF WORRY 6 1.1.2 THE WORRY CONTINUUM – NORMAL VERSUS MALADAPTIVE WORRY 7 1.1.3 THE DELETERIOUS EFFECTS OF EXCESSIVE WORRY 8 1.1.4 THEORETICAL MODELS OF EXCESSIVE WORRY 11 1.2 FUNCTIONAL BRAIN NETWORKS AND EXCESSIVE WORRY 18 1.2.1 A SYSTEMS NEUROSCIENCE VIEW OF EXCESSIVE WORRY 18 1.2.2 EMPIRICAL EVIDENCE: FMRI STUDIES ON EXCESSIVE WORRY 20 1.3 RESEARCH QUESTION 32 2 STUDY I: A QUANTITATIVE META-ANALYSIS OF FMRI STUDIES INVESTIGATING EMOTIONAL PROCESSING IN EXCESSIVE WORRIERS: APPLICATION OF ACTIVATION LIKELIHOOD ESTIMATION ANALYSIS 35 2.1 ABSTRACT 36 2.2 INTRODUCTION 37 2.3 METHODS 40 2.3.1 LITERATURE SEARCH AND STUDY SELECTION 40 2.3.2 ACTIVATION LIKELIHOOD ESTIMATION 46 2.3.3 META-ANALYTIC CONNECTIVITY MODELING 47 2.3.4 ANALYSIS OF BEHAVIORAL DOMAIN PROFILES 47 2.4 RESULTS 48 2.4.1 SIGNIFICANT ALE CLUSTERS 48 2.4.2 FUNCTIONAL CONNECTIVITY OF THE DERIVED ALE-CLUSTER – MACM-ANALYSIS 51 2.4.3 FUNCTIONAL CHARACTERIZATION OF THE DERIVED ALE-CLUSTER – BEHAVIORAL ANALYSIS 54 2.5 DISCUSSION 55 2.6 CONCLUSION 59 2.7 SUPPLEMENTARY MATERIAL STUDY I: LISTING OF ALE CLUSTERS SIGNIFICANT AT P < 0.001 UNCORRECTED, CLUSTER SIZE > 100MM3 60 3 STUDY II: HIGH AND LOW WORRIERS DO NOT DIFFER IN UNSTIMULATED RESTING-STATE BRAIN CONNECTIVITY 61 3.1 ABSTRACT 62 3.2 INTRODUCTION 63 3.3 MATERIALS AND METHODS 65 3.3.1 PARTICIPANTS AND PROCEDURE 65 3.3.2 FMRI DATA ACQUISITION 66 3.3.3 SELF-REPORT ASSESSMENTS AND STATE WORRY ASSESSMENT 66 3.3.4 STATISTICAL ANALYSES 67 3.4 RESULTS 69 3.4.1 SELF-REPORT MEASURES 69 3.4.2 FMRI RESULTS 72 3.5 DISCUSSION 72 3.6 CONCLUSION 75 3.7 SUPPLEMENTARY MATERIAL STUDY II: STATE WORRY ASSESSMENT 75 4 GENERAL DISCUSSION 76 4.1 CONVERGENT ABERRANT FUNCTION IN THE MFG-IFG-INSULA-CLUSTER 76 4.2 META-ANALYTIC FUNCTIONAL CHARACTERIZATION AND CONNECTIVITY MAPPING OF THE MFG-IFG-INSULA CLUSTER 82 4.3 NO RESTING-STATE FUNCTIONAL CONNECTIVITY DIFFERENCES BETWEEN HW AND LW 84 4.4 STRENGTHS AND LIMITATIONS 87 4.5 FUTURE DIRECTIONS 90 4.6 CONCLUSION 91 REFERENCES 92 APPENDIX: DECLARATION OF HONOUR / EIGENSTÄNDIGKEITSERKLÄRUNG 131