892 resultados para resting-state networks


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We investigated the differences in the resting state corticolimbic blood flow between 20 unmedicated depressed patients and 21 healthy comparisons. Resting state cerebral blood flow (CBF) was measured with H215O PET. Anatomical MRI scans were performed on an Elscint 1.9 T Prestige system for PET-MRI coregistration. Significant changes in cerebral blood flow indicating neural activity were detected using an ROI-free image subtraction strategy. In addition, the resting blood flow in patients was correlated with the severity of depression as measured by HAM-D scores. Depressed patients showed decreases in blood flow in right anterior cingulate (Brodmann areas 24 and 32) and increased blood flow in left and right posterior cingulate (Brodmann areas 23, 29, 30), left parahippocampal gyrus (Brodmann area 36), and right caudate compared with healthy volunteers. The severity of depression was inversely correlated with the left middle and inferior frontal gyri (Brodmann areas 9 and 47) and right medial frontal gyrus (Brodmann area 10) and right anterior cingulate (Brodmann areas 24, 32) blood flow, and directly correlated with the right thalamus blood flow. These findings support previous reports of abnormalities in the resting state blood flow in the limbic-frontal structures in depressed patients compared to healthy volunteers. Hum Brain Mapp, 2012. (C) 2011 Wiley Periodicals, Inc.

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Capire come modellare l'attività del cervello a riposo, resting state, è il primo passo necessario per avvicinarsi a una reale comprensione della dinamica cerebrale. Sperimentalmente si osserva che, quando il cervello non è soggetto a stimoli esterni, particolari reti di regioni cerebrali presentano un'attività neuronale superiore alla media. Nonostante gli sforzi dei ricercatori, non è ancora chiara la relazione che sussiste tra le connessioni strutturali e le connessioni funzionali del sistema cerebrale a riposo, organizzate nella matrice di connettività funzionale. Recenti studi sperimentali mostrano la natura non stazionaria della connettività funzionale in disaccordo con i modelli in letteratura. Il modello implementato nella presente tesi per simulare l'evoluzione temporale del network permette di riprodurre il comportamento dinamico della connettività funzionale. Per la prima volta in questa tesi, secondo i lavori a noi noti, un modello di resting state è implementato nel cervello di un topo. Poco è noto, infatti, riguardo all'architettura funzionale su larga scala del cervello dei topi, nonostante il largo utilizzo di tale sistema nella modellizzazione dei disturbi neurologici. Le connessioni strutturali utilizzate per definire la topologia della rete neurale sono quelle ottenute dall'Allen Institute for Brain Science. Tale strumento fornisce una straordinaria opportunità per riprodurre simulazioni realistiche, poiché, come affermato nell'articolo che presenta tale lavoro, questo connettoma è il più esauriente disponibile, ad oggi, in ogni specie vertebrata. I parametri liberi del modello sono stati scelti in modo da inizializzare il sistema nel range dinamico ottimale per riprodurre il comportamento dinamico della connettività funzionale. Diverse considerazioni e misure sono state effettuate sul segnale BOLD simulato per meglio comprenderne la natura. L'accordo soddisfacente fra i centri funzionali calcolati nel network cerebrale simulato e quelli ottenuti tramite l'indagine sperimentale di Mechling et al., 2014 comprovano la bontà del modello e dei metodi utilizzati per analizzare il segnale simulato.

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Il lavoro che ho sviluppato presso l'unità di RM funzionale del Policlinico S.Orsola-Malpighi, DIBINEM, è incentrato sull'analisi dati di resting state - functional Magnetic Resonance Imaging (rs-fMRI) mediante l'utilizzo della graph theory, con lo scopo di valutare eventuali differenze in termini di connettività cerebrale funzionale tra un campione di pazienti affetti da Nocturnal Frontal Lobe Epilepsy (NFLE) ed uno di controlli sani. L'epilessia frontale notturna è una peculiare forma di epilessia caratterizzata da crisi che si verificano quasi esclusivamente durante il sonno notturno. Queste sono contraddistinte da comportamenti motori, prevalentemente distonici, spesso complessi, e talora a semiologia bizzarra. L'fMRI è una metodica di neuroimaging avanzata che permette di misurare indirettamente l'attività neuronale. Tutti i soggetti sono stati studiati in condizioni di resting-state, ossia di veglia rilassata. In particolare mi sono occupato di analizzare i dati fMRI con un approccio innovativo in campo clinico-neurologico, rappresentato dalla graph theory. I grafi sono definiti come strutture matematiche costituite da nodi e links, che trovano applicazione in molti campi di studio per la modellizzazione di strutture di diverso tipo. La costruzione di un grafo cerebrale per ogni partecipante allo studio ha rappresentato la parte centrale di questo lavoro. L'obiettivo è stato quello di definire le connessioni funzionali tra le diverse aree del cervello mediante l'utilizzo di un network. Il processo di modellizzazione ha permesso di valutare i grafi neurali mediante il calcolo di parametri topologici che ne caratterizzano struttura ed organizzazione. Le misure calcolate in questa analisi preliminare non hanno evidenziato differenze nelle proprietà globali tra i grafi dei pazienti e quelli dei controlli. Alterazioni locali sono state invece riscontrate nei pazienti, rispetto ai controlli, in aree della sostanza grigia profonda, del sistema limbico e delle regioni frontali, le quali rientrano tra quelle ipotizzate essere coinvolte nella fisiopatologia di questa peculiare forma di epilessia.

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Reduced motor activity has been reported in schizophrenia and was associated with subtype, psychopathology and medication. Still, little is known about the neurobiology of motor retardation. To identify neural correlates of motor activity, resting state cerebral blood flow (CBF) was correlated with objective motor activity of the same day. Participants comprised 11 schizophrenia patients and 14 controls who underwent magnetic resonance imaging with arterial spin labeling and wrist actigraphy. Patients had reduced activity levels and reduced perfusion of the left parahippocampal gyrus, left middle temporal gyrus, right thalamus, and right prefrontal cortex. In controls, but not in schizophrenia, CBF was correlated with activity in the right thalamic ventral anterior (VA) nucleus, a key module within basal ganglia-cortical motor circuits. In contrast, only in schizophrenia patients positive correlations of CBF and motor activity were found in bilateral prefrontal areas and in the right rostral cingulate motor area (rCMA). Grey matter volume correlated with motor activity only in the left posterior cingulate cortex of the patients. The findings suggest that basal ganglia motor control is impaired in schizophrenia. In addition, CBF of cortical areas critical for motor control was associated with volitional motor behavior, which may be a compensatory mechanism for basal ganglia dysfunction.

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Abnormal perceptions and cognitions in schizophrenia might be related to abnormal resting states of the brain. Previous research found that a specific class (class D) of sub-second electroencephalography (EEG) microstates was shortened in schizophrenia. This shortening correlated with positive symptoms. We questioned if this reflected positive psychotic traits or present psychopathology.

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Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

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Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.

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The crystal structure of the resting state of cytochrome P450cam (CYP101), a heme thiolate protein, shows a cluster of six water molecules in the substrate binding pocket, one of which is coordinating to iron(III) as sixth ligand. The resting state is low-spin and changes to high-spin when substrate camphor binds and H2O is removed. In contrast to the protein, previously synthesised enzyme models such as H2O[BOND]FeIII(porph)(ArS−) were shown to be purely high-spin. Iron(S−)porphyrins with different distal sites mimicking proposed remote effects have been prepared and studied by cw-EPR. The results indicate that the low-spin of the resting state of P450cam is due to the fact that the water molecule coordinating to iron has an OH−-like character because of hydrogen bonding and polarisation of the water cluster, respectively.

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Crown-capped iron(S−) porphyrins 1·H2O and 2·H2O and their corresponding Ba2+ complexes have been prepared as active site analogues of the resting state of cytochrome P450cam. cw-EPR studies and electronic structure calculations at the density functional theory (DFT) level of model systems suggest a functional role of the water cluster of P450cam.

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The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.