Dissertations / Theses: 'Functional connectivity'

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Rahal, Line. "Imagerie fonctionnelle ultrasonore du cerveau pour l'étude, le suivi et le traitement de la douleur aiguë et chronique." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLET041.

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Ces travaux de thèse visaient à démontrer l’intérêt de l’imagerie fonctionnelle ultrasonore pour la définition et le suivi de traitements thérapeutiques des manifestations douloureuses aiguës et chroniques. Dans le cadre d’un projet commun mêlant physique des ondes, imagerie, neurosciences et douleur, nous avons montré que cette jeune technologie d’imagerie pouvait être appliquée à l’imagerie de la douleur chez le petit animal anesthésié, à différents niveaux du système nerveux.Dans le but d’avoir une anesthésie adaptée, stable, reproductible d’un animal à l’autre, et contenant le moins d’agents modulateurs de la douleur possible, nous avons comparé six protocoles d’anesthésie différents. Cette étude a conclu que l’utilisation d’un mélange de kétamine et de médétomidine était le meilleur compromis pour nos futures expérimentations en douleur.La première étude sur les processus de la douleur s’est concentrée sur le test à la formaline, un modèle bien caractérisé de douleur inflammatoire court terme (1h). En effet, notre souhait était de débuter sur un modèle de douleur aiguë le plus court possible pouvant être réalisé chez l’animal anesthésié. Sur ce modèle, nous n’avons observé aucun changement significatif de connectivité fonctionnelle dans le cerveau des rats injectés. Nous avons alors choisi de nous tourner vers des modèles de douleur inflammatoire plus persistants.La seconde étude de cette thèse a porté sur l’étude des altérations de connectivité fonctionnelle et d’états cérébraux dans deux modèles de douleur inflammatoire : un modèle à court terme, induit par injection unilatérale d’adjuvant de Freund, et un modèle à long terme, qui est la polyarthrite induite par adjuvant (quatre semaines d’inflammation bilatérale). Tandis que nous n’avons pas obtenu de résultats significatifs d’altérations fonctionnelles dans le modèle court terme, le modèle long terme nous a apporté de nombreuses informations sur les altérations du système nerveux central pendant le processus de chronicisation.Enfin, la dernière étude a porté sur l’imagerie fonctionnelle ultrasonore des ganglions trigéminaux, structures du système nerveux périphérique, à la fois petites et profondes. Nous avons cherché à caractériser la réponse vasculaire de ces ganglions suite à des stimulations nociceptives mécaniques et chimiques de la cornée chez le rat anesthésié. Cette étude nous a permis de confirmer les observations obtenues par immunohistochimie du proto-oncogène c-fos et de valider l’imagerie fonctionnelle ultrasonore comme modalité pour l’imagerie de l’activation des ganglions trigéminaux chez le rat anesthésié, pour l’étude de la douleur trigéminale
Those thesis works aimed at demonstrating the value of functional ultrasound imaging for the definition and the tracking of acute and chronic pain therapeutic treatments. As part of a common project intertwining wave physics, imaging, neurosciences and pain, we demonstrated that this young imaging technology can be applied to pain imaging on the anesthetized small animal, at different levels of the nervous system.With the aim of obtaining an adapted anaesthesia, stable, reproducible from one animal to another, and containing as less pain modulating agents as possible, we compared six different anaesthetics protocols. This study was concluded by the use of the ketamine and medetomidine mixture as the best compromise for our future experiments in pain.The first study on pain processes has focused on the formaline test, a well characterized model of short term inflammatory pain (1h). Indeed, our wish was to start with an acute pain model as short as possible which may be performed on the anesthetized animal. With this model, we didn’t observe any significant change of functional connectivity in the brain of the injected rats. We then chose to turn to more ongoing models of inflammatory pain.The second study of this thesis dealt with the study of the functional connectivity and brain states alterations in two models of inflammatory pain: a short term model, induced by unilateral injection of Freund’s adjuvant, and a long term model, which is adjuvant induced polyarthritis (four weeks of bilateral inflammation). While we didn’t obtain significant results of functional alterations in the short term model, the long term model gave us ample information on the central nervous system alterations during the chronification process.Finally, the last study concerns the ultrasound functional imaging of the trigeminal ganglions, peripheral nervous system structures, both small and deeply located. We tried to characterize the vascular response of those ganglions following mechanical and chemical nociceptive stimulations of the cornea on the anesthetized rat. This study allowed us to confirm the observations obtained by immunohistochemistry of the proto-oncogene c-fos and to validate the functional ultrasound imaging as a modality for the imaging of the trigeminal ganglions in the anesthetized rat, for the study of trigeminal pain

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Nylén, Jan. "Exploring Ways of Visualizing Functional Connectivity." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-141182.

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Functional connectivity is a ﬁeld within neuroscience where measurements of co-activation between brain regions are used to test various hypotheses or explore how the brain activates depending on a given situation or task. After analysis, the underlying data in the ﬁeld consists of a n by n adjacency matrix where each cell represents a correlation value between two regions in the brain. Depending on the research question the number of regions and matrices incorporated varies and new visualizations are needed in order to portray them. In this thesis the design of an interactive web based visualization tool for functional connectivity was explored through an iterative design process. The design of the tool was based on existing guidelines, interviews and best practices in data visualization as well as an analysis of current visualization solutions used in functional connectivity. The ﬁnal concept and prototype uses a network plot for functional connectivity called the connectogram as well as a grouped bar graph to provide an intuitive and accessible way of comparing functional connectivity data by interacting with and highlighting networks and speciﬁc network data through direct manipulation. Results of qualitative evaluations of a prototype using data from a concurrent scientiﬁc project is presented. The prototype was found to be useful, engaging, easily perceivable and oﬀered an easy and quick way of exploring data sets.

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Goldstone, Aimée. "Functional connectivity of the ageing brain." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7651/.

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This thesis investigated the impact of advancing age on modifying the functional connectivity (FC) of both typical cortical resting-state networks and subcortical structures in the human brain. Furthermore, it explored how any differences in FC may be associated with changes in sleep quality, also thought to be affected by age, and how such interactions may contribute to typical cognitive disruption associated with older age. The results suggest that older age is associated with the heterogeneous, spatially specific re-organisation of resting-state networks (RSNs), as well as indicating gender-specific spatial re-organisation. Investigation of thalamic FC revealed that older adults exhibited greater thalamo-sensory and thalamo-hippocampal FC, which was related to cognitive performance on RT and memory tasks, respectively. Investigation into participant’s sleep patterns provided evidence that sleep quality was more variable amongst the older participants. Furthermore, older adults that slept the longest each night were found to exhibit patterns of thalamic FC which were associated with better cognitive performance, than seen in older shorter sleepers. These results provide preliminary evidence that sleep may be associated with more ‘preferable’ patterns of FC in older adults which may be beneficial for cognitive function.

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Merz, Susanne. "Functional connectivity in disorders of consciousness." Thesis, University of Aberdeen, 2013. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=211209.

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Disorders of consciousness (DoC) are a group of disorders that can occur after severe brain injury. DOC have been subdivided based on behavioural observations into: Coma, lacking any signs of wakefulness or awareness; the vegetative state, showing signs of wakefulness but lacking any signs of awareness; and the minimally conscious state, showing signs of wakefulness and infrequent and irregular signs of awareness. The so-called locked-in syndrome, a state where both wakefulness and awareness are intact, but no communication is possible due to a lack of muscle function, does not belong to the disorders of consciousness. However, it is difficult to distinguish the locked-in syndrome from DoC diagnostically, because consciousness can only be shown through consistent responses to a command and current methods for assessing consciousness rely on behavioural responses. Patients with locked-in syndrome might not be able to move voluntarily at all in the most severe cases. Behavioural assessment would then classify them as unaware. While this is an extreme and rare case, it illustrates the problem behavioural assessment poses. Such assessments are unable to distinguish the effects of impaired muscular control from impaired awareness, when either has reached an extreme level of severity. Brain damage that does not affect consciousness itself can nevertheless affect the results of the behavioural assessment of consciousness. It is then hardly surprising that the diagnosis of DoC is associated with a high level of uncertainty. The advantage of brain imaging methods is that they do not rely on the patients ability to produce a consistent behavioural response. There have therefore been efforts to use the brain imaging methods electroencephalography, positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) to aid diagnosis of disorder of consciousness. PET and fMRI have successfully been used to identify regions of difference in some patients in a DoC. Task-based fMRI has been used to identify intact consciousness, using tasks that require explicit understanding of instructions and wilful modulation of brain activity, but no motor control. One of these tasks consists of periods where the participant imagines playing tennis alternated with periods of rest. The ability to follow this paradigm is evidence of consciousness, and a few patients with a diagnosis of DoC have been shown to be able to do this task. However, the tennis task requires high order processing of the tasks requirements and the majority of patients does not respond to this task. fMRI tasks that test sensory modalities instead of consciousness have been used to show retained brain function even in DoC patients that do not respond to the tennis task. In this work the tennis task and a battery of other tasks including tactile, visual and auditory stimulation, were studied on a group of DoC patients. It was found that none of the patients responded to the task of imagining playing tennis, but retained sensory function could be identified in three out of seven patients. This highlights a strength of fMRI, namely that it can identify retained brain function below the level that is necessary for consciousness. However, the results also show that more than half of the patients studied here, did not show retained brain activation during the fMRI scan. For any of the patients that did not show a response, this can be due to an actual lack of retained brain function, but it can also be due to limitations of the task-based fMRI analysis. The fMRI tasks only test one sensory function at a time, for a short time. Thus a visual fMRI task for example, can only provide information about areas of the brain, that are involved in visual processing. And when vigilance is fluctuating, retained brain function can remain undetected, if vigilance is low during the scan. Functional connectivity analysis is a method to study internal connections between brain areas that is not dependent on an external task. It models the brain as a network of interconnected regions and studies the characteristics of this network. Graph theory is a mathematical field that has found application on many other fields using network analysis, like social sciences, metabolic network modelling or gene network modelling. In fMRI analysis, graph theory has been used to study different phenomena and pathologies and global network properties have been shown reproducibly. The work presented here aims to develop new methods based in graph theory aiding the identification of residual brain integrity. To allow an assessment of the brain network topology and its use in the assessment of residual brain integrity, a novel method was designed based on a graph theoretical measure. The method, termed Cortical Hubs And Related network Topology (CHART) is a two stage procedure. The rst stage identifies statistically significant differences in functional connectivity between two groups, using a measure of the average connectivity of each voxel, the weighted global connectivity. The second stage highlights the topology of the networks associated with those differences. Two fMRI datasets, with different underlying tasks and pathologies were used to test the CHART method. The first dataset was acquired from a group of patients with severe depression. It contrasted the state of the brain before and after successful treatment with electroconvulsive therapy. In this patient group the CHART method was able to identify an area of hyperconnectivity in the depressed state, compared to the treated state. This area of hyperconnectivity was connected to areas that had priorly been shown to be overly connected in the depressed state. The second dataset consisted of DoC patients, that had been extensively assessed behaviourally. Half of the patients were diagnosed to be in a vegetative state, the other half was diagnosed to be in a minimally conscious state. The first stage of CHART identified several areas of difference based on the weighted global connectivity. The second stage highlighted that the observed global differences were due to an overall lack of extended functional connectivity in the vegetative state patients. The addition of a healthy control group in stage two allowed comparison not only between the two DoC groups, but also with the healthy group. In summary it was observed that the spatial extent of the connectivity seen in the minimally conscious group resembles the spatial extent of the connectivity seen in the healthy control group, while the spatial extent of connectivity observed in the vegetative state group was minimal, compared to both healthy and minimally conscious group. Thus the spatial extent of connectivity is a distinguishing property for the vegetative state group studied here. However the first stage of the CHART method is a group based method. In disorders of consciousness, where the underlying pathology is different from case to case, this concept is problematic. Finding a meaningful group of interest is difficult or impossible, because lesions differ in location and extent. Individual differences in connectivity can be expected to be large, and a generalisation of the CHART result might not lead to improved diagnosis for every patient. For diagnosis, the patients individual characteristics must be taken into account. An additional objective of this work was therefore to develop a method to compare a single patient to a group of controls. An approach based on regression modelling was tested but failed to provide the necessary statistical sensitivity to detect impaired connectivity. In conclusion the CHART method developed in this work provides insights into the functional connectivity of a group of DoC patients. To assist diagnosis, further development of a method to compare a single subject to a group of controls will be important.

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Nauhaus, Ian Michael. "Functional connectivity in primary visual cortex." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1692099811&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Ghumman, Sukhmanjit. "Functional connectivity in patients with brain tumours." Mémoire, Université de Sherbrooke, 2018. http://hdl.handle.net/11143/12001.

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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.

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Björnfot, Cecilia. "Multiband functional magnetic resonance imaging (fMRI) for functional connectivity assessments." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149906.

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During resting state the brain exhibits synchronized activity within all major brain networks. Using blood oxygen level dependent (BOLD) resting state functional magnetic resonance imaging (fMRI) based detection it is possible to quantify the degree of correlation, connectivity, between regions of interest and assess information regarding the integrity of the inter-regional functional integration. A newly available multiband echo planar imaging (EPI) fMRI sequence allows for faster scan times which possibly allows us to better examine large-scale networks and increase the understanding of brain function/dysfunction. This thesis will assess how the newly developed sequence compares to a conventional EPI sequence for detecting resting state connectivity of canonical brain networks. The data acquisitions were made on a 3 Tesla scanner using a 32 channel head coil. The hypothesis was that the multiband sequence would produce a better result since it has faster sampling rate, thus more data points in its time-series to support the statistical analyses. Using Pearson’s linear correlation between the average time-series (approximately 12 minutes long) within a seed-region and all voxels contained in the image volume, correlation maps where created for each of the eight participants using data normalized to Montreal Neurological Institute (MNI) space. The resting state networks (RSN) were then found by performing a one sample T-test on group level. Six seed-coordinates, based on literature, where used revealing the the homotopic connections in anterior Hippocampus, Motor cortex, Dorsal attention, Visual and the Default mode network (DMN) as well for an anterior-posterior connection in the DMN. By comparing the maximum T-values within the regions for the RSN no systematic diﬀerence could be found between the multiband and conventional fMRI data. Further tests were conducted to evaluate if the sequences would diﬀerentiate in their results if the acquisition time was shortened, i.e shortening the time-series in the voxels. However no such diﬀerence could be established.Importantly, the results are speciﬁc to the 32 channel head coil used in the current study. Presumably recently available and improved coil designs could better exploit the multiband technique.

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Ing, Alex. "Comparing functional connectivity across the whole brain." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=225661.

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Functional connectivity MRI (fcMRI) based on the blood oxygen level dependent (BOLD) contrast has become a widely used modality for mapping the brain's functional architecture. In recent years, applications of fcMRI have led to numerous breakthroughs in both clinical research and basic sciences. However, there are a number of unresolved issues associated with fcMRI relating to both the modality itself, and to methods used to analyse fcMRI data. The aim of this thesis was twofold: to develop novel data analysis procedures, and to demonstrate their feasibility in dedicated neuroimaging studies. Subject head movement can act as a significant confound in fcMRI. Investigating this issue, it was found that subject motion can induce significant increases and decreases in functional connectivity across the brain. A novel motion correction method was developed, which proved more effective than standard procedures in the removal of motion induced connectivity changes. The BOLD contrast is not a direct measure of neural activity, it measures the hemodynamic response caused by changes in neural activity, which varies across the brain. The hypercapnic state is often used to calibrate the BOLD signal. This calibration crucially relies on the assumption that hypercapnia does not affect neuronal activity. An investigation into the hypercapnic state revealed that it is associated with both increases and decreases in functional connectivity. Whilst carrying out this investigation, a number of limitations, such as the need for a hypothesis and information loss, were identified in standard data analysis procedures. Three novel methods were developed to address these limitations. The efficacy of these methods was demonstrated in four different neuroimaging studies, which investigated functional connectivity changes induced by hypercapnia, aerobic exercise, hormonal changes across the menstrual cycle, and electroconvulsive therapy treatment in depression.

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Stringer, Michael S. "Functional connectivity approaches to focal neurological conditions." Thesis, University of Aberdeen, 2016. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=231782.

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A wide range of conditions are characterised by focal neurological symptoms, yet the pathophysiolgy often remains poorly understood. This thesis has focussed on applying functional neuroimaging in clinical groups. Migraines with aura are amongst the most common conditions posing a signiﬁcant burden to suﬀerers. Elevated connectivity was detected in the visual cortex of migraine with aura patients, potentially complementing one of the leading proposed mechanisms for attacks. Minor strokes patients are also aﬀected by focal symptoms after events which in some cases can be prolonged. Altered connectivity was observed in a number of regions reﬂecting previous ﬁndings for acute stroke. A group of transient ischaemic attack patients were also analysed, revealing subtle diﬀerences necessitating further study. Lastly disorders of consciousness pose acute challenges for treatment and ongoing care. Task based imaging was applied to form a more accurate picture of residual cognition. Additionally the correlation between measures derived from resting state data and cerebral glucose consumption was explored.

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Narayanan, Ananth. "Pharmacological Modulation of Functional Connectivity in Neuropsychological Disorders." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1353086436.

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Williams, Kathleen Anne. "Resting State Connectivity in the Rat Brain." Thesis, Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14059.

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Functional MRI is a method of imaging changes in blood oxygenation that accompany neural activity in the brain. A specific area within fMRI studies investigates what the brain is doing when it is not being stimulated. It is postulated that there are distinctly separate regions of the brain that are connected based upon functional relations and that these connected regions synchronously communicate even during rest. Resting state connectivity has become a tool to investigate neurological disorders in humans without specific knowledge of the mechanisms that correlate neural activity with brain metabolism and blood flow. This work attempts to characterize resting state connectivity in the rat brain to establish a model that will help elucidate the relationship between functional connectivity, as measured with fMRI, and brain function. Four analysis techniques, power spectrum estimation, cross correlation analysis, principle component analysis, and independent component analysis, are employed to examine data acquired during a non-stimulation, single-slice, gradient echo EPI sequence in search of functionally connected, spatially distant regions of the rat brain.

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Spencer, Matthew. "Evolving complex network models of functional connectivity dynamics." Thesis, University of Reading, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590143.

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Functional connectivity networks describe how regions of the brain interact. The timing, location, and frequency of these interactions inform about memory, decision making, motor movement, affective states, and more. However, while these interactions are well described as networks, these networks, like many others throughout nature, are constantly changing. Complex network evolution poses a highly dimensional problem but also contains much information about the system in question. In this thesis, a recent class of evolving complex network models was explored and extended to capture the functional connectivity dynamics observed in neuronal networks. Functional connectivity was investigated through data- and model-driven techniques at the cellular level, with cultures of cortical neurones on multi-electrode arrays, and at the whole-brain level, with electroencephalography. At the neuronal level, complex spatial dependencies were identified in bursts of excitation and two novel network models, the Starburst model and the Excitation Flow model, are used to capture the resulting functional connectivity. At the whole-brain level, functional connectivity dynamics were used to perform single-trial classification of intentional motor movement. Again, spatiotemporal dependencies were identified and used to present three novel techniques for modelling the network dynamics. The first two techniques decomposed networks into network templates (one model-based and one spectral-based) and modelled the dynamics with hidden Markov models. The final technique was a generalised evolving version of the Starburst model. The hidden Markov model of spectrally decomposed networks was shown to classify motor intentions with an accuracy around 80%. Firstly, this thesis shows that time plays an important role in the production of the complex network topologies observed in functional connectivity, both at the cellular and whole-brain leve1. Further, it is shown that evolving complex network models are very useful tools for modelling these topologies and that the network dynamics can be used to uncover features that are crucial to identifying functional states.

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Akram, Harith. "Application of MRI connectivity in stereotactic functional neurosurgery." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10052005/.

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This thesis examines potential applications of advanced MRI-connectivity studies in stereotactic functional neurosurgery. Several new analysis methodologies are employed to: (1) build predictive models of DBS surgery outcome; (2) refine the surgical target and (3) help build a better understanding of the pathogenesis of the treated conditions and the mechanism of action of DBS therapy. The experimental component is divided into three main parts focusing on the following pathologies: (1) Parkinson’s disease (PD), (2) tremor and (3) trigeminal autonomic cephalalgias (TAC). Section I: In the first experiment (chapter 3), resting state fMRI was used to find radiological biomarkers predictive of response to L-DOPA in 19 patients undergoing subthalamic nucleus (STN) DBS for PD. A greater improvement in UPDRS-III scores following L-DOPA administration was characterized by higher resting state functional connectivity (fcMRI) between the prefrontal cortex and the striatum (p=0.001) and lower fcMRI between the pallidum (p=0.001), subthalamic nucleus (p=0.003) and the paracentral lobule. In the second experiment (chapter 4), structural (diffusion) connectivity was used to map out the influence of the hyperdirect pathways on outcome and identify the therapeutic ‘sweet spots’ in twenty PD patients undergoing STN-DBS. Clusters corresponding to maximum improvement in symptoms were in the posterior, superior and lateral portion of the STN. Greater connectivity to the primary motor area, supplementary motor area and prefrontal cortex was predictive of higher improvement in tremor, bradykinesia and rigidity, and rigidity respectively. The third experiment (chapter 5) examined pyramidal tract (PT) activation in 20 PD patients with STN-DBS. Volume of tissue activation (VTA) around DBS contacts were modelled in relation to the PT. VTA/ PT overlap predicted EMG activation thresholds. Sections II: Pilot data suggest that probabilistic tractography techniques can be used to segment the ventrolateral (VL) and ventroposterior (VP) thalamus based on cortical and cerebellar connectivity in nine patients who underwent thalamic DBS for tremor (chapter 6). The thalamic area, best representing the ventrointermedialis nucleus (VIM), was connected to the contralateral dentate cerebellar nucleus. Streamlines corresponding to the dentato-rubro-thalamic tract (DRT) connected M1 to the contralateral dentate nucleus via the dentato-thalamic area. Good response was seen when the active contact’s VTA was in the thalamic area with the highest connectivity to the contralateral dentate nucleus. Section III: The efficacy and safety of DBS in the ventral tegmental area (VTa) in the treatment of chronic cluster headache (CH) and short lasting unilateral neuralgiform headache attacks (SUNA) were examined (chapters 7 and 8). The optimum stimulation site within the VTa that best controls symptoms was explored (chapter 9). The average responders’ deep brain stimulation activation volume lay on the trigemino-hypothalamic tract, connecting the trigeminal system and other nociceptive brainstem nuclei, with the hypothalamus, and the prefrontal and mesial temporal areas.

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Orban, Csaba. "Amygdala resting state functional connectivity in alcohol dependence." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/59191.

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Alcohol dependence is a global societal problem, yet current avenues for its treatment are largely ineffective in slowing its chronic-relapsing trajectory. Animal studies of alcohol dependence have described neuroadaptations in the amygdala that may play a central role in mechanisms of relapse. In this thesis, spontaneous amygdala network function was examined in abstinent alcohol dependent patients (ADP) using functional magnetic resonance imaging within the framework of a multi-site neuroimaging platform: ICCAM. Participants underwent five scans that included baseline, as well as scans under placebo, acute antagonism of μ-opioid, Dopamine D3 (DRD3) and Neurokinin-1 (NK1) receptor systems previously implicated in mechanisms of addiction. At baseline, amygdala – substantia nigra/ventral tegmental area (SN/VTA) resting state functional connectivity (RSFC) was elevated in abstinent ADP, despite widespread grey-matter (GM) volumetric atrophy, in both amygdala and SN/VTA, compared with age-matched healthy controls (HC). The strength of amygdala – SN/VTA RSFC in ADP was primarily associated with years of cumulative alcohol exposure, but not with amygdala or SN/VTA GM volume, length of abstinence, smoking status, or head motion. Amygdala RSFC with other regions showed sensitivity to core clinical features of ADP at baseline. Amygdala – frontoparietal (FPN) RSFC was inversely associated with abstinence length, with ADP in the first two months of abstinence showing significantly reduced amygdala – FPN RSFC compared with HC. Voxelwise comparison of amygdala RSFC between each drug session and placebo, did not reveal differential effects of receptor blockade on ADP and HC. Across both groups, however, the three drugs exhibited both overlapping and differential effects on distinct brain networks. Notably, amygdala RSFC in the superior temporal gyrus showed increases under NK1-antagonism, and decreases under naltrexone compared with placebo. Finally, amygdala – SN/VTA was significantly elevated in ADP relative to HC across all four sessions, suggesting that it may represent a stable neurophysiological feature of alcohol dependence.

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Savva, Androula. "Assessment of Functional Connectivity Impairment in Rat Brains." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-247593.

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While the rodent model has long been used in brain research, there exists no standardisedprocessing routine that can be employed for analysis and investigation of disease models. Thepresent thesis attempts to investigate a diseased brain model by implementing a collection ofscripts, combined with algorithms from existing neuroimaging software, and adapting themto the rodent brain, in an attempt to examine when and how monaural canal atresia affectsthe functional connectivity of the brain. We show that it is possible to use software tailoredto the human brain to pre-process the rodent model. Following conventional pipelines andresting state functional MRI (rs-fMRI)-specific strategies, the developed processing routineimplements the most basic steps suggested in literature. On the single-subject level, skullstripping was done using Mialite software, motion correction and distortion correction werebased on FMRIB software library (FSL) algorithms and motion artefacts were removed usingICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA). Following denoising,normalisation to standard space, smoothing and temporal filtering, group level analysis wasperformed. A univariate, hypothesis-driven method and a multivariate, data-driven methodwere used for group comparison and statistical inference. While seed-based correlationanalysis (SCA) did not return any significant results, independent component analysis (ICA) identified two components that show activation in areas of interest.
Djurmodeller med gnagare (råtta och mus) har länge använts i hjärnforskning. Men ännu finns det ingen standardiserad rutin för analys och utvärdering av bilddata från sådana sjukdomsmodeller. Detta arbete använder en råttmodell av sjukdomen ensidig hörselgångsatresi, som innebär att yttre hörselgången är igensatt på ena sidan. Detta görs genom att mjukvaruverktyg som utvecklats för att analysera bilddata från magnetkameraundersökning av den mänskliga hjärnan anpassas för att användas på motsvarande bilddata från råtta för att studera hur ensidig hörselgångsatresi påverkar hjärnans funktionella konnektivitet, dvs hur mönstren i hjärnaktivering samvarierar mellan olika delar av hjärnan (rs-fMRI). Vi visar att det är möjligt att använda mjukvara avsedd för människans hjärna för att förbehandla bilder av råtthjärna. Med hjälp av etablerade arbetsflöden och särskilda procedurer för rs-fMRI kunde den utvecklade proceduren implementera de viktigaste stegen i analysen. För varje individ avgränsades hjärnan med programmet Mialite, rörelsekorrigering och korrigering av rumsdistorsion gjordes med FSL, och rörelseartefakter avlägsnades med ICA-AROMA. Sedan brus tagits bort, och bilddata standardiserats till en standardanatomi och genomgått filtrering i rum och tid, gjordes analys på två grupper, med och utan artificiell hörselgångsatresi. En univariat, hypotesdriven metod och en multivariat, data-driven metod användes för gruppjämförelse och statistisk analys. Frö-baserad korrelationsanalys (SCA) gav inga signifikanta resultat, men oberoende-komponent-analys (ICA) påvisade två anatomiska områden med aktivering relaterad till skillnader mellan grupperna.

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McRae, Kateri Lynne. "Functional and Effective Connectivity of Effortful Emotion Regulation." Diss., The University of Arizona, 2007. http://hdl.handle.net/10150/194032.

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Emotion regulation plays an important role in emotional well-being, as well as in the protection against and recovery from mood and anxiety disorders. Previous studies of the functional neuroanatomy of emotion regulation have reported greater activity in prefrontal control-related regions during active regulation. These activations are accompanied by decreases in activity in emotion-responsive regions such as the amygdala and insula. These findings are widely interpreted as consistent with models of cognitive control that implicate top-down, negative influences from prefrontal cortex upon emotion-related processing in other regions. However, no studies to date have used measures of effective connectivity to investigate the likely influence of prefrontal control regions upon emotion-responsive regions in the context of effortful emotion regulation. In the present study, participants alternated between responding naturally to negative emotional stimuli and reinterpreting the negative stimuli with the goal of reducing their experienced negative affect. Functional magnetic resonance imaging (fMRI) was used to measure whole-brain blood-oxygen level dependent signal throughout the task. fMRI data were analyzed using partial least squares (PLS) and structural equations modeling (SEM) to test for differences in effective connectivity between natural and regulated emotional responding. Results indicate that three paths significantly distinguish between regulation and non-regulation negative conditions. The path from inferior frontal gyrus (IFG) to anterior cingulate cortex (ACC) was significantly less positive during regulation than natural responding. In addition, the reciprocal paths between ACC and insula were more negative during regulation than natural responding. Taken as a whole, these changes in effective connectivity are consistent with assumptions of top-down modulation during effortful emotion regulation. In addition, these changes suggest a pivotal role for the influence of IFG upon ACC and the ACC-insula loop in emotion regulation. The processes represented by these changes and implications for future research are discussed.

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Goparaju, Balaji. "High level motion: neural correlates and functional connectivity." Thesis, Boston University, 2012. https://hdl.handle.net/2144/21157.

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Thesis (M.Sc.Eng.) PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
This thesis uses functional magnetic resonance imaging (fMRI) data to investigate: 1. The neural substrate of high level visual motion 2. The functional connectivity between a behavioral task and resting state. In chapter 1, we find the neural substrate of a set of psychophysical high level motion tasks. Specifically, we used tasks of visually guided navigation, such as heading from optic flow, landmarks, motion parallax, and collision detection. We also used tasks underlying the ability to perform object recognition from motion cues alone such as 3D Structure From Motion (SFM) and Biological Motion (BM). fMRI data was analyzed with Brain Voyager and activated anatomical areas were delineated using Matlab scripts developed in the laboratory. Several regions within the dorsal visual system elicited significant BOLD activity: the dorsal-occipital (BA19) and parietal lobes (BA 37, 40, 7). The ventral areas (BA 20, 21, 22, 38) showed significant BOLD activity only in BM and SFM and in heading tests using landmarks or motion parallax. We generated a schematic map with the overlapping areas among high level motion tasks, which can aid in diagnosis and rehabilitation of motion deficits in neurological patients. In chapter 2, we computed the functional brain connectivity between the brain areas in a resting state (subject performs no task), and during task (subject performs a visual motion task). In the resting state, we found connectivity using correlations between the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and the hippocampal formation, which have been reported as the default mode network (DMN) since it represents correlated neural activity during a state of rest. We used bivariate correlations to compute functional connectivity using the CONN fMRI toolbox and in-house Matlab scripts. We computed a whole-brain analysis and compared network statistics in both, resting state and during task to investigate measures of integration such as path length and global efficiency, regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), and global measures such as small-worldness. The DMN and graph theoretical measures connectivity during task was stronger as compared with the resting state. We also computed these measures in task using a similar frequency spectrum as rest (0.009 Hz < f < 0.08 Hz), and in the full frequency spectrum. We find that on the whole, the connectivity measures in the DMN and the graph theoretical measure are stronger in the fullband signal processing analysis as compared to the bandpass version of the analysis.
2031-01-01

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18

Lee, Pamela Wen-Hsin. "Mutual information derived functional connectivity of the electroencephalogram (EEG)." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/219.

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Monitoring the functional connectivity between brain networks is becoming increasingly important in elucidating brain functionality in normal and disease states. Current methods of detecting networks in the recorded EEG such as correlation and coherence are limited by the fact that they assume stationarity of the relationship between channels, and rely on linear dependencies. Here we utilize mutual information (MI) as the metric for determining nonlinear statistical dependencies between electroencephalographic (EEG) channels. Previous work investigating MI between EEG channels in subjects with widespread diseases of the cerebral cortex had subjects simply rest quietly with their eyes closed. In motor disorders such as Parkinson’s disease (PD), abnormalities are only expected during performance of motor tasks, but this makes the assumption of stationarity of relationships between EEG channels untenable. We therefore propose a novel EEG segmentation method based on the temporal dynamics of the cross-spectrogram of the computed Independent Components (ICs). After suitable thresholding of the MI values between channels in the temporally segmented EEG, graphical theoretical analysis approaches are applied to the derived networks. The method was applied to EEG data recorded from six normal subjects and seven PD subjects on and off medication performing a motor task involving either their right hand only or both hands simultaneously. One-way analysis of variance (ANOVA) tests demonstrated statistically significant difference between subject groups. This proposed segmentation/MI network method appears to be a promising approach for EEG analysis.

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Rieubland, S. C. S. "Functional and anatomical connectivity patterns in the cerebellar cortex." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1400297/.

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The rules governing synaptic connectivity in neural circuits are still poorly understood. In the cerebellar cortex, the general wiring patterns between different cell types are known, but the precise circuit at the level of individual cells is still unclear. In the molecular layer, thought to be the principal site of cerebellar learning, I investigated three fundamental microcircuits and their connectivity: the network of chemically and electrically coupled inhibitory interneurons, their inhibitory connection to Purkinje cells, and their shared parallel fibre input, which together form a feed-forward inhibitory circuit. I used both electrophysiological and anatomical techniques to probe functional and structural connectivity patterns in these circuits. Optimisation was performed to combine electrophysiological recordings and imaging with a focused ion beam scanning electron microscope. The resulting high-resolution three-dimensional imaging reveals the precise connectivity of hundreds of individual parallel fibres. I found that their connectivity is constrained by volume exclusion rules between presynaptic boutons. These spatial constraints are overcome between directly adjacent interneurons and Purkinje cells, receiving input from a common parallel fibre bouton. Using multiple patch-clamp recordings, I found evidence for specific, non-random connectivity amongst molecular layer interneurons. The electrical and chemical networks are both highly clustered and their overlap is non-random. Inhibitory connections between interneurons are preferentially organized in a feed-forward (or transitive) fashion. I show that individual interneurons can both decrease and increase the inhibition received by Purkinje cells, via an indirect connection through electrically coupled interneurons. A highly specific connectivity pattern supports this control of inhibition of Purkinje cells by the coupled network. To summarize, I investigated the rules governing neural connectivity in the molecular layer: from spatial constraints, via formation of specific connectivity motifs, to the implementation of functional roles. This new information will help shape our understanding of the interactions and computations performed in the cerebellar cortex.

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Habberfield, Michael William. "Functional connectivity for wildlife populations across spatially complex landscapes." Thesis, State University of New York at Buffalo, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10163822.

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Integrating animal movement information with the spatial analysis of landscape structure is critical for restoring biological communities in spatially-structured landscapes. This integration can be accomplished by focusing on functional connectivity—a landscape’s potential for the movement of organisms among resource patches—in relation to the spatial and structural connectivity of landscape elements. I carried out three investigations in order to examine how landscape structure interacts with the ecological factors associated with animal movement processes, and thereby produce actionable outcomes for the restoration of wildlife populations. This work combined population- and individual-level data of dispersing wildlife to better resolve the influence of spatial structure on functional connectivity. First, I used a meta-analysis to quantify the relationship between structural and functional connectivity for a broad scope of animal species. Second, I assessed the influence of landscape position and habitat density on colonization, movement, and population dynamics of wood frogs (Lithobates sylvatica) within a network of restored vernal pools. Third, I experimentally evaluated dispersal and habitat selection of green frogs (Lithobates clamitans) within this vernal pool system.

The meta-analysis demonstrated that universal scaling relationships of species and the landscapes they are moving through interact as key drivers mediating the level of functional connectivity afforded to wildlife by structural connectivity. Mark-recapture data revealed rapid colonization of the restored vernal pool network by wood frogs, with subsequently moderate levels of frog movement among neighboring pools. Local pool density interacted with the colonization process and terrestrial habitat availability to limit wood frog productivity within a pool cluster. Experimental dispersal data for green frogs artificially translocated within the pool network showed key differences between movement in familiar and novel environments. Differing movement behaviors and habitat selection patterns indicated that a habitat patch for this species is on the scale of a pool cluster rather than an individual pool. Together, the observed spatial dynamics of these vernal pool amphibians contribute a framework for improving amphibian dispersal modeling, potential responses to rapid environmental changes, and predicting colonization and subsequent population dynamics in restored systems. The results of this dissertation improve our understanding of how spatial structure interacts with organism-specific factors to produce observed patterns of functional connectivity.

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Joules, Richard Bryan. "Functional connectivity and machine learning for psychiatric drug development." Thesis, King's College London (University of London), 2015. http://kclpure.kcl.ac.uk/portal/en/theses/functional-connectivity-and-machine-learning-for-psychiatric-drug-development(23f2637e-2604-4b82-82e2-619e084cd6d3).html.

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The human brain is a complex biological network consisting of spatially separated but functionally integrated regions. Study of functional connectivity gained immense popularity in recent years providing new insight into the mechanisms underlying complex functions and the fundamental organisation of the brain. This has led to the emergence of new techniques for investigating connectivity, such as the application of pattern recognition techniques and the investigation of network dynamics. While highly promising, the application of these new techniques to pharmacological imaging data has not yet been fully explored. In this thesis we apply pattern recognition techniques to functional connectivity measures obtained for pharmacological imaging data to discriminate patterns of whole brain connectivity. Furthermore, we demonstrate that consideration of functional connectivity dynamics provides additional insight into the effect of pharmacological interventions. Specifically, we explore the effects of the N-methyl-D-aspartate receptor antagonist, ketamine, on the connectivity within the human brain. We argue that the investigation of connectivity is a more appropriate tool for the investigation of this compound due to the highly distributed pattern of effects, as compared to traditional approaches investigating amplitude effects. We demonstrate the applicability of pattern recognition techniques for the discrimination pharmacological states using measures of regional connectivity over the whole brain, using network interactions and through the inspection of network dynamics. We expand upon traditional approaches in our investigation, introducing a new approach to investigate network effects and temporal dynamics of connectivity organisation.

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22

Wennberg, Johannes. "Longitudinal assessment of functional connectivity impairment in rat brains." Thesis, KTH, Tillämpad fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254160.

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23

Popeo, Mariagrazia. "Assessing functional connectivity in the newborn brain using fNIRS." Doctoral thesis, Università degli studi di Trento, 2019. https://hdl.handle.net/11572/368751.

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Functional connectivity represents a powerful approach to describe the intrinsic activity of the brain. It reveals the organization and correlations among anatomically separated regions supporting similar cognitive and sensory processes. Using functional Magnetic Resonance Imaging (fMRI), the recurrent spatial characteristics of these patterns have been extensively explored in the adult brain and their disruption has been found to be associated with psychiatric and developmental disorders. Unveiling the processes of emergence of resting state networks at a very early stage of life could shed light on the neuronal origins of these diseases. However, the study of the inception and development of functional connectivity in the newborn brain poses exceptional challenges, due to the complexity of dealing with non-compliant subjects. To this end, cortical activity at birth can be investigated using functional Near Infrared Spectroscopy (fNIRS) that represents a promising non-invasive neuroimaging method for developmental studies. In the present thesis, I applied fNIRS to assess functional connectivity in term neonates. The first part of the dissertation is dedicated to investigating the maturation of a specific resting state network, the Default Mode Network, within the first 48 hours of life. The study aimed to examine its emergence, for the first time, using optical imaging on newborns immediately after birth. While the majority of fMRI literature focused on large-scale spatial patterns, I took a different approach measuring an intrinsic and localized fingerprint feature of the network, consistently detected in adult subjects. In the second part of the dissertation, I aimed at improving the anatomical representation of brain connectivity, inferred only from signals collected at the scalp. Thus, I developed and validated a method for the reconstruction of spatially distributed functional signals on a dedicated template for term newborn subjects. The intent is to promote the shift from a sensor space description (one signal for each channel) to a source space representation in which the origin of the signal is reconstructed with better anatomical fidelity. The reliability of the reconstruction method was tested on synthetic and real data. In the former case, I simulated spatially correlated neural activity in the cortex, thus enabling assessment of the reconstructed images against a ground-truth map. Analyses of functional connectivity in both sensor and source space showed that the Default Mode Network is still immature at birth, with a lack of homotopic correlation in the lateral parietal cortices, and no evidence of anticorrelation with the Dorsal Attention Network, a well established feature in the adult brain. Overall the work presented in the thesis contributes to the understanding of functional connectivity in the infantâ€™s brain and provides useful tools for source-based connectivity analysis and for probe design and optimization.

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Popeo, Mariagrazia. "Assessing functional connectivity in the newborn brain using fNIRS." Doctoral thesis, University of Trento, 2019. http://eprints-phd.biblio.unitn.it/3768/1/Thesis_Popeo_Mariagrazia.pdf.

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Functional connectivity represents a powerful approach to describe the intrinsic activity of the brain. It reveals the organization and correlations among anatomically separated regions supporting similar cognitive and sensory processes. Using functional Magnetic Resonance Imaging (fMRI), the recurrent spatial characteristics of these patterns have been extensively explored in the adult brain and their disruption has been found to be associated with psychiatric and developmental disorders. Unveiling the processes of emergence of resting state networks at a very early stage of life could shed light on the neuronal origins of these diseases. However, the study of the inception and development of functional connectivity in the newborn brain poses exceptional challenges, due to the complexity of dealing with non-compliant subjects. To this end, cortical activity at birth can be investigated using functional Near Infrared Spectroscopy (fNIRS) that represents a promising non-invasive neuroimaging method for developmental studies. In the present thesis, I applied fNIRS to assess functional connectivity in term neonates. The first part of the dissertation is dedicated to investigating the maturation of a specific resting state network, the Default Mode Network, within the first 48 hours of life. The study aimed to examine its emergence, for the first time, using optical imaging on newborns immediately after birth. While the majority of fMRI literature focused on large-scale spatial patterns, I took a different approach measuring an intrinsic and localized fingerprint feature of the network, consistently detected in adult subjects. In the second part of the dissertation, I aimed at improving the anatomical representation of brain connectivity, inferred only from signals collected at the scalp. Thus, I developed and validated a method for the reconstruction of spatially distributed functional signals on a dedicated template for term newborn subjects. The intent is to promote the shift from a sensor space description (one signal for each channel) to a source space representation in which the origin of the signal is reconstructed with better anatomical fidelity. The reliability of the reconstruction method was tested on synthetic and real data. In the former case, I simulated spatially correlated neural activity in the cortex, thus enabling assessment of the reconstructed images against a ground-truth map. Analyses of functional connectivity in both sensor and source space showed that the Default Mode Network is still immature at birth, with a lack of homotopic correlation in the lateral parietal cortices, and no evidence of anticorrelation with the Dorsal Attention Network, a well established feature in the adult brain. Overall the work presented in the thesis contributes to the understanding of functional connectivity in the infant’s brain and provides useful tools for source-based connectivity analysis and for probe design and optimization.

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Goldhacker, Markus [Verfasser], and Elmar [Akademischer Betreuer] Lang. "Frequency-resolved dynamic functional connectivity and scale stability of connectivity-states / Markus Goldhacker ; Betreuer: Elmar Lang." Regensburg : Universitätsbibliothek Regensburg, 2017. http://d-nb.info/1124679944/34.

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26

Rocchi, Federico. "Chemogenetic modulation of fMRI connectivity." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/335219.

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Resting-state fMRI (rsfMRI) has been widely used to map intrinsic brain network organization of the human brain both in health and in pathological conditions. However, the neural underpinnings and dynamic rules governing brain-wide rsfMRI coupling remain unclear. Filling this knowledge gap is of crucial importance, given our current inability to decode and reverse-engineer clinical signatures of aberrant connectivity into interpretable neurophysiological events that can help understand or diagnose brain disorders. Toward this goal, here we combined chemogenetics, rsfMRI, and in vivo electrophysiology in the mouse to investigate how regional manipulations of brain activity (i.e. neural inhibition, or excitation) causally contribute to whole-brain fMRI network organization. In a first set of proof of concept investigations, we empirically probed the widely held notion that neural inhibition of a cortical node would result in reduced fMRI coupling of the silenced area and its long-range terminals. Surprisingly, we found that chronic inhibition of the mouse medial prefrontal cortex (PFC) via viral overexpression of a potassium channel paradoxically increased fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Notably, acute chemogenetic inhibition of the PFC reproduced analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we found that chemogenetic inhibition of the PFC enhances low frequency (0.1 - 4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes, with important implications for neural modeling and interpretation of fMRI overconnectivity in brain disorders. Importantly, our observation that neural inhibition of the PFC results in fMRI overconnectivity allowed us to predict that neural activation of the same area might produce opposite results, i.e. fMRI underconnectivity and neural desynchronization. To test this hypothesis, we used chemogenetics to increase local excitatory-inhibitory (E/I) balance in the PFC. As predicted, chemogenetic stimulation of CamkII-expressing neurons, or inhibition of fast-spiking parvalbumin-expressing neurons, produced similar rsfMRI signatures of rsfMRI underconnectivity. Both manipulations produced analogous electrophysiological signatures characterized by increased firing activity and a robust LFP power shift towards higher (i.e. γ) frequencies, effectively reversing the corresponding neural signature observed in DREADD inhibition studies. Importantly, the same E/I affecting perturbations were also associated with socio-communicative deficits in behaving mice hence underscoring the behavioral relevance of the employed manipulations. These results show that excitatory/inhibitory balance critically biases brain-wide fMRI coupling, pointing at a possible unifying mechanistic link between E/I imbalance and rsfMRI connectivity disruption in developmental disorders. More broadly, these investigations reveal a set of fundamental rules linking regional brain activity to macroscale functional connectivity, offering opportunities to physiologically interpret rsfMRI signatures of functional dysconnectivity in human brain disorders.

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Radhakrishnan, Rupa M. D. "Altered Functional Activation and Network Connectivity Underlies Working Memory Dysfunction in Adolescents with Epilepsy." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1515514289145094.

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28

Edde, Manon. "Approche multimodale de connectivité fonctionnelle et structurelle pour l’analyse du déclin cognitif au cours du vieillissement : étude au sein de la cohorte des 3Cités." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLEP011.

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Le vieillissement s’accompagne de modifications cérébrales dont l’hétérogénéité expliquerait en partie la variabilité inter-individuelle du déclin cognitif. Ces modifications concernent aussi bien les aspects structurels que fonctionnels. L’imagerie cérébrale multimodale a apporté des éléments de compréhension sur la relation structure-fonction, mais reste peu étudiée dans le cadre du vieillissement. Au cours de ce travail, la connectivité fonctionnelle de repos (CF) et structurelle (CS) prélevées dans l’espace natif ont été explorées chez 120 sujets âgés (cohorte 3C) afin d’étudier leur lien avec les trajectoires cognitives modélisées sur les 12 ans de suivi. Dans notre échantillon, les niveaux de CF inter-hémisphérique élevés sont associés avec les altérations globales du parenchyme cérébral (atrophie de la substance grise et charge lésionnelle de la substance blanche) et avec le déclin en mémoire épisodique. Les paramètres de diffusion corrigés de l’eau libre et extraits du faisceau cingulaire reconstruit par tractographie sont associés au déclin en fluence verbale. D’autre part, une CF élevée et une CS basse entre le cortex cingulaire postérieur ventral (vPCC) et le precuneus A7m sont associés avec le déclin en mémoire épisodique, indépendamment du volume hippocampique. Enfin, les sujets âgés présentent un déficit de réorganisation de l’architecture fonctionnelle de repos à court terme après la réalisation d’une tâche d’apprentissage. Ainsi, le vieillissement cérébral s’accompagne de différents types de modifications de CF (augmentation, diminution, déficit de réorganisation à court terme) offrant ainsi au cerveau un répertoire de réponse plus complexe que la CS
Aging is associated with changes in the brain, the heterogeneity of which partly explains the inter-individual variability of cognitive decline. These changes concern both the structural and functional aspects. Multimodal brain imaging has provided some insights into the structure-function relationship, but this has been little studied in the context of aging. In this work, functional rest (CF) and structural (CS) connectivity from native space were explored in 120 elderly subjects (cohort 3C) to study their relationship to cognitive trajectories modeled on the 12 years of follow-up. In our sample, elevated interhemispheric CF levels are associated with global changes in cerebral parenchyma (gray matter atrophy and white matter injury burden) and episodic memory decline. The diffusion parameters corrected for free-water, extracted from the cingulum tract are associated with the decline in verbal fluency. On the other hand, high CF and low CS between posterior ventral cingulate cortex (vPCC) and precuneus A7m are associated with episodic memory decline, regardless of hippocampal volume. Finally, the elderly subjects present a deficit of short-term reorganization of the rest-functional architecture after a learning task. Thus, cerebral aging is associated with different patterns of CF changes (increase, decrease, short-term reorganization deficit) thus providing to the brain a more complex response repertoire than CS

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Mukherjee, Prerona. "Functional disconnection and social cognition in schizophrenia." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5901.

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Introduction Social and emotional functions play a key role in schizophrenia. Both positive symptoms, such as hallucinations and persecutory delusions, as well as negative symptoms such as social withdrawal, and flattened affect impact socioemotional function. These functions involve distributed brain networks. The ‘Disconnection Hypothesis’, a plausible unifying theory of schizophrenia, proposes connectivity within such networks as a core pathological feature of schizophrenia. Connectivity is also related to specific genetic risk factors. Therefore the present project addresses the hypothesis that individuals with schizophrenia might show disconnection within socio-emotional brain networks, and examines the effects of a functional polymorphism of the BDNF gene on connectivity within these networks. Methods Here I examined the brain activation and connectivity for implicit emotional reaction and social judgment in schizophrenia, as well as with variation in the val66met polymorphism of BDNF. Brain activation was examined with functional magnetic resonance imaging, and effective connectivity was estimated using psycho-physiological interactions, from the bilateral amygdala to the whole brain (using a facial image paradigm for explicit approachability judgement and implicit fear response respectively). Results Individuals with schizophrenia showed reduced activation in the right lingual gyrus, right superior temporal gyrus and left amygdala during fear processing, as well as reduced connectivity from the left amygdala to the right temporo-parietal junction and precuneus. During approachability judgments, patients overactivated the right inferior frontal gyrus and right precuneus and showed reduced connectivity from the bilateral amygdala to the right inferior frontal gyrus. Met allele carriers of the BDNF val66met polymorphism showed overactivation in the medial anterior cingulate cortex, and bilateral insula, as well as reduced connectivity between the anterior cingulate cortex and hippocampus. For approachability judgment, met carriers overactivated the middle occipital gyrus, and showed reduced connectivity from the left amygdala to the right parahippocampal gyrus and medial frontal gyrus, as well as the left posterior cingulate gyrus, pre and post central gyrus, middle temporal gyrus and cerebellum. Conclusion In conclusion, connectivity between the amygdala and brain regions associated with a range of socially relevant functions were found to be reduced in both patients, and met allele carriers of the BDNF val66met SNP. Given the key role of the amygdala in affective processing this diffuse disconnection in networks for socio-emotional functions might mediate the aberrant emotional and social behavior seen in individuals with schizophrenia.

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Craddock, Richard Cameron. "Support vector classification analysis of resting state functional connectivity fMRI." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31774.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Hu, Xiaoping; Committee Co-Chair: Vachtsevanos, George; Committee Member: Butera, Robert; Committee Member: Gurbaxani, Brian; Committee Member: Mayberg, Helen; Committee Member: Yezzi, Anthony. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Akerman, Colin J. "The development of functional connectivity in the mammalian geniculocortical pathway." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365701.

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Yao, Ye. "Variability of structurally constrained and unconstrained functional connectivity in schizophrenia." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/110754/.

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In this thesis, entropy is used to characterize intrinsic ageing properties of the human brain. Analysis of fMRI data from a large dataset of individuals, using resting state BOLD signals, demonstrated that a functional connectivity entropy associated with brain activity increases with age. During an average lifespan, the entropy, which was calculated from a population of individuals, increased by approximately 0.1 bits, due to correlations in BOLD activity becoming more widely distributed. This is attributed to the number of excitatory neurons and the excitatory conductance decreasing with age. Incorporating these properties into a computational model leads to quantitatively similar results to the fMRI data. The dataset involved males and females and significant differences were found between them. The entropy of males at birth was lower than that of females. However, the entropies of the two sexes increase at different rates, and intersect at approximately 50 years; after this age, males have a larger entropy. In addition, the connectivity between different brain areas provides evidence about normal function and dysfunction. Changes are described in the distribution of these connectional strengths in schizophrenia using a large sample of resting-state fMRI data. The functional connectivity entropy, which measures the dispersion of the functional connectivity distribution, was lower in patients with schizophrenia than in controls, reflecting a reduction in both strong positive and negative correlations between brain regions. The decrease in the functional connectivity entropy was strongly associated with an increase in the positive, negative, and general symptoms. Using an integrate-and-fire simulation model based on anatomical connectivity, it is shown that a reduction in the efficacy of the NMDA mediated excitatory synaptic inputs can reduce the functional connectivity entropy to resemble the pattern seen in schizophrenia. Spatial variation in connectivity is an integral aspect of the brain's architecture. In the absence of this variability, the brain may act as a single homogenous entity without regional specialization. In this thesis, we investigate the variability in functional links categorized on the basis of the presence of direct structural paths (primary) or indirect paths mediated by one (secondary) or more (tertiary) brain regions ascertained by diffusion tensor imaging. We quantified the variability in functional connectivity using an unbiased estimate of unpredictability (functional connectivity entropy) in a neuropsychiatric disorder where structure-function relationship is considered to be abnormal. 34 patients and 32 healthy controls underwent DTI and resting state functional MRI scans. Less than one-third (27.4% in patients, 27.85% in controls) of functional links between brain regions were regarded as direct primary links on the basis of DTI tractography, while the rest were secondary or tertiary. The most significant changes in the distribution of functional connectivity in schizophrenia occur in indirect tertiary paths with no direct axonal linkage in both early (p=0.0002, d=1.46) and late (p=1_10).

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Schulz, D. P. A. "The structure of functional connectivity in cat primary visual cortex." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1394406/.

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The key to understanding how the brain works is to understand the computations it performs. The structure of anatomical and functional connectivity determines what the brain can compute and how it does so. Correlations have served as a tool for analysing connectivity for over five decades. The mammalian visual cortex has become the most intensively researched cortical area and is unmatched for our knowledge of its anatomical layout and, most importantly, stimulus selectivity. Furthermore, recent perspectives on correlations have arisen from information theory and network models of the brain. The purpose of this dissertation is to determine the precise structure of functional connectivity in cat primary visual cortex. We aim to contribute to and extend previous work by analysing the structure of neural responses and correlations during spontaneous activity, the presentation of artificial stimuli and the presentation of natural stimuli. We report on a comprehensive set of twenty functional and neurophysiological factors, and reveal how previously unexplored factors govern correlations in visual cortex in vivo. Furthermore we find novel functional relationships between factors governing the responses of neurons, and report on a set of properties which allow to distinguish narrow from broad spiking cells. Much attention is devoted to the precise functional dependency of correlations upon firing rate, with the development of methods to remove the firing rate modulation. We show that timescale is an important determinant of correlations, and that natural stimuli generate different correlations than artificial stimuli. We also show that during spontaneous activity, neurons are more likely to fire together if they are tuned to a similar orientation. These results emphasize that both spontaneous and stimulus driven cortical activity contain rich structure that is far from a decorrelated state.

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Shah, Chintan. "Effects of Exercise Therapy on Functional Connectivity in Parkinson's Disease." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1364514398.

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Greenwald, Katherine Rose. "Habitat fragmentation, functional landscape connectivity, and metapopulation processes in amphibians." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1243366608.

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Kay, Benjamin P. "Resting-State Functional Connectivity in Treatment-Resistant Idiopathic Generalized Epilepsy." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1380612937.

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Tailor, Nisha. "Functional connectivity between the basolateral amygdala and ventral hippocampal formation." Thesis, University of Manchester, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529242.

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Milton, Jami Lynn. "Functional microcircuits and development of laminar connectivity in visual cortex /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2001. http://wwwlib.umi.com/cr/ucsd/fullcit?p3013706.

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Greenwald, Katherine R. "Habitat fragmentation, functional landscape connectivity, and metapopulation processes in amphibians." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1243366608.

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Guzmán-Veléz, Edmarie. "Association between bilingualism and functional brain connectivity in older adults." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2217.

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Older bilingual adults typically perform better than monolinguals in tasks of executive control, and are diagnosed later with dementia. Studies have also shown structural and functional brain differences between bilinguals and monolinguals. However, it remains poorly understood how language history influences the functional organization of the aging brain. The current study investigated; 1) differences in resting-state functional connectivity between monolinguals and bilinguals in the Default Mode Network (DMN), Frontoparietal Network (FPN), Executive Control Network (ECN), Language Network (LANG), and a network consisting of structures associated with tasks of executive control coined the Bilingual Control Network (BCN); 2) the relationship of cognitive performance with functional connectivity of the BCN; and 3) whether proficiency, age of second language acquisition, degree of second language exposure, and frequency of language use predicts the network’s functional connectivity. Healthy older bilinguals (N=10) were matched pairwise for age, sex and education to healthy older monolinguals (N=10). All participants completed a battery of cognitive tests, a language history questionnaire, and a 6-minute functional scan during rest. Results showed that groups did not differ in cognitive performance, or in the functional connectivity of the FPN, ECN, LANG, or BCN. However, monolinguals had significantly stronger functional connectivity in the DMN compared to bilinguals. Later age of second language acquisition and lower proficiency were also associated with greater DMN functional connectivity. None of these variables predicted BCN’s functional connectivity. However, bilinguals showed stronger functional connectivity with other structures outside of the canonical networks compared to monolinguals. Finally, vocabulary scores, local switch cost accuracy and reaction time were negatively correlated with BCN’s functional connectivity. Overall, these findings illustrate differences in functional brain organization associated with language experience in the DMN, while challenging the “bilingual advantage” hypothesis. The results also suggest a possible neural mechanism by which bilingualism might mediate cognitive reserve.

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Sharman, Michael. "Neuroimaging biomarkeurs of structural and functional connectivity in Parkinson's disease." Paris 6, 2011. http://www.theses.fr/2011PA066644.

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Parkinson’s disease (PD) is a debilitating neurodegenerative disorder involving progressive motor dysfunction, most commonly affecting elderly individuals. A hallmark of disease pathology is a loss of dopaminergic neurons in the substantia nigra and their terminals in the striatum. Neurodegeneration is thought to lead to a destabiliation of the normal signalling that occurs between these, and other cortical and subcortical brain regions. An important challenge for neuroscience lies in differentiating PD neuropathology from similar disorders, as well as those impairments that occur as part of normal aging. The purpose of this thesis was to apply neuroimaging, specifically magnetic resonance imaging (MRI), to identify and evaluate biomarkers of PD. Biomarkers are objective measures of biological state that can be used to quantify a disease, including the symptoms associated with its appearance and progression. Three standalone studies formed the basis of this work. In the first study, outliers in diffusion weighted MRI (DW-MRI) were probed using simulations and real data analyses, to understand their impact on candidate biomarker metrics. Metrics were found to be highly sensitive to error, and data correction was recommended to minimise bias in further analyses. A q-space interpolation method was proposed for identifying and correcting corruptionaffected data, and a decision support system outlined with which to treat this data. In the second study, candidate biomarkers in DW-MRI and resting state functional MRI (rsfMRI) were evaluated to determine their performance as metrics of structural and functional connectivity. A unique, multimodal paradigm demonstrated that anatomical and functional deficits could be attributed to PD for particular connections relevant to the sensorimotor circuit. In the third study, validation of the candidate biomarkers identified in PD was performed in a group of healthy subjects. Here, the objective was to understand the effects of aging on the same associative, limbic and sensorimotor circuitry connecting cortical and subcortical brain regions. Age-related variations in anatomical connectivity were found to differentially affect certain circuits, and nuances in biomarker metrics were observed for particular brain structures. Interestingly, associative circuit functional connections also appeared strengthened. Overall, this thesis successfully identified and evaluated several new candidate biomarkers for PD, as well as furthered an understanding of brain structure and function as it relates to PD, through the development of new analytical pipelines. In addition, tentative conclusions could be drawn regarding the differentiation of PD dysfunction from brain function in healthy elderly subjects
La maladie de Parkinson (MDP) est une maladie neurodégénérative qui atteint le plus souvent les personnes âgées et qui se manifeste par des troubles moteurs qui s’aggravent au cours du temps. L'objectif de cette thèse était d'identifier et d'évaluer des biomarqueurs de la MDP grâce à l'imagerie par résonance magnétique (IRM). Ce travail est constitué de trois différentes études. La première étude visait à mieux comprendre l'influence de la qualité des données acquises sur les mesures de biomarqueurs candidats en IRM pondérée en diffusion (IRM-DW) en utilisant un jeu de données simulées dans un premier temps, puis un jeu de données réelles dans un deuxième temps. Dans la deuxième étude, les patrons de connectivité structurelle et fonctionnelle ont été évalués en IRM-DW et en IRM fonctionnelle au repos (IRMf-rs) pour déterminer leur efficacité en tant que biomarqueurs candidats. Un paradigme multimodal unique a permis d'isoler des déficits anatomiques et fonctionnels qui concernaient des connexions isolées du circuit sensorimoteur particulièrement touchées dans la MDP. Dans la troisième étude, la validation des biomarqueurs candidats identifiés précédemment a été effectuée dans un groupe de volontaires sains. Les changements de connectivité anatomiques liés à l'âge affectaient différemment les trois circuits corticales-souscorticales. Dans l'ensemble, cette thèse a permis d'une part d'identifier et d'évaluer plusieurs nouveaux biomarqueurs dans la MDP, d'autre part d'approfondir notre compréhension du rapport entre les anomalies structurelles et fonctionnelles du cerveau en ce qui concerne la MDP, tout en développant de nouveaux outils analytiques de neuroimagerie

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Berkström, Charlotte. "Ecological connectivity in East African seascapes." Doctoral thesis, Stockholms universitet, Systemekologiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-75194.

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Coral reefs, seagrass beds and mangroves constitute a complex mosaic of habitats referred to as the tropical seascape. Great gaps exist in the knowledge of how these systems are interconnected. This thesis sets out to examine ecological connectivity, i.e. the connectedness of ecological processes across multiple scales, in Zanzibar and Mafia Island, Tanzania. Paper I examined the current knowledge of interlinkages and their effect on seascape functioning, revealing that there are surprisingly few studies on the influences of cross-habitat interactions and food-web ecology. Furthermore, 50% of all fish species use more than one habitat and 18% of all coral reef fish species use mangrove or seagrass beds as juvenile habitat in Zanzibar. Paper II examined the seascape of Menai Bay, Zanzibar using a landscape ecology approach and studied the relationship between fish and landscape variables. The amount of seagrass within 750m of a coral reef site was correlated with increased invertebrate feeder/piscivore fish abundance, especially Lethrinidae and Lutjanidae, which are known to perform ontogenetic and feeding migrations. Within patch seagrass cover was correlated with nursery species abundance. Paper III focused on a seagrass-dominated seascape in Chwaka Bay, Zanzibar and showed that small-scale habitat complexity (shoot height and density) as well as large-scale variables such as distance to coral reefs affected abundance and distribution of a common seagrass parrotfish Leptoscarus vaigiensis. Paper IV studied the connectivity and functional role of two snappers (Lutjanus fulviflamma and L. ehrenbergii) using stable isotopes (δ15N and δ13C) and found that connectivity between habitats was maintained by ontogenetic and foraging migrations by these species. The thesis concludes that ecological connectivity and multi-habitat usage by fish is a general and important characteristic in the Western Indian Ocean and should be considered in management planning.

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 4: Submitted.

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Almashaikhi, Talal. "Electrical brain stimulation and human insular connectivity." Thesis, Lyon 1, 2013. http://www.theses.fr/2013LYO10174/document.

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Le cortex insulaire est le cinquième lobe du cerveau en charge de l'intégration de nombreuses fonctions cognitives, sous-tendues par une organisation cytoarchitectonique etune connectivité aussi riche que complexe. Ce travail vise à évaluer la connectivité fonctionnelle insulaire du cerveau humain par le biais de stimulation électrique intra-cérébrale et de potentiels évoqués cortico-corticaux (PECC) réalisés chez des patients explorés en stéréoélectroencéphalographie (SEEG) pour une épilepsie partielle réfractaire. Nous avons développé un protocole automatisé permettant destimuler successivement l’ensemble des bipoles d’enregistrement intracérébraux (deux plots contigus d’une même électrode) disponibles chez les patients explorés en SEEG. Deux sériesde 20 stimulations monophasiques d’une durée unitaire de 1 ms et d’une intentisté de 1 mA, étaient délivrés à une fréquence de 0,2 Hz au niveau de chaque bipole (105 en moyenne,produisant un total d’environ 11.000 PECC par patient). Un premier travail a consisté dans lamise au point d’une méthode fiable d’analyse statistique objective des PECC significatifs, encomplement de l’analyse visuelle, sur un échantillon de 33017 enregistrements chez trois patients. L’analyse a porté sur les quatre fenêtres temporelles post-stimulation suivantes: 10-100 ms, 100-300 ms, 300-500 ms, 500-1000 ms. La seconde partie de notre thèse a appliquéces méthodes à l’étude des connections intra-insulaires sur un échantillon de10 patients présentant au moins deux éléctrodes intra-insulaires. La dernière partie de notre travail s’est intéressé aux efférences insulaires sur un échantillon de 11 patients. L’étude des PECC apporte des éléments de connectivité fonctionnelle derésolution spatiale et temporelle inégalée, complémentaires de ceux découlant des techniquesde neuroimagerie. La gestion complexe du volume de données à gérer pour chaque patientpeut être résolu par des procédures d’analyse statistiques automatisée de sensibilité etspécificité satisfaisante. Le pattern des connections intra- et extra-insulaires révélé par cetteapproche permet une meilleure compréhension de la physiologie de l’insula chez l’Homme etdes modalités de propagations des décharges épileptiques impliquant ce lobe
The insular cortex is the fifth lobe of the brain and is in charge of the integration of many cognitive functions, underpinned by a rich cytoarchitectonic organization and a complex connectivity. Our work aims to evaluate the insular functional connectivity of the human brain using intracerebral electrical stimulation and recording of cortico-cortical evoked potentials (CCEPs) in patients investigated with stereoelectroencephalography (SEEG) for refractory partial epilepsy. We first developed an automated protocol to stimulate successively all intracerebral recorded bipoles (two contiguous leads of the same electrode) available in patients undergoing SEEG. Two sets of 20 monophasic stimulation of 1 ms duration and 1mA intensity were delivered at a frequency of 0.2 Hz at each bipole (105 on average, producing a total of about 11,000 recordings per patient). We then develop a reliable and objective statistical method to detect significant CCEPs as a complement to visual analysis, and validate this approach on a sample of 33017 recordings in three patients. The analysis was performed over four distinct post-stimulus epochs: 10-100 ms, 100-300 ms, 300-500 ms, 500-1000 ms. In the second part of our thesis, we applied these methods to the study of intrainsular connections on a sample of 10 patients with at least two intra-insular electrodes. The last part of our work used the same approach to investigate insular efferents in a sample of 11 patients. The study of CCEPs provides novel and important findings regarding the human brain functional connectivity, with unmatched spatial and temporal resolutions as compared to neuroimaging techniques. The complex management of large volume of data in each patient can be solved by automated statistical analysis procedures with satisfactory sensitivity and specificity. The pattern of connections within and outside the insula revealed by this approach provides a better understanding of the physiology of the Human insula as well as of the propagation of epileptic discharges involving this lobe

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Wang, Yao. "Structural and Functional Connectivity Analyses of Rat Brains Based on fMRI Experiments." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/153.

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Various topics on functional magnetic resonance imaging (fMRI) analyses have been in study through the last 30 years. This work delineates the pathways required for resting-state functional connectivity analyses, which illuminates the correlations between different rat brain regions and can be presented in a functional connectivity matrix. The matrix is built based on the category nomenclature system of Swanson Rat Atlas 1998. From which a structural connectivity matrix is also built. This work developed the complete functional connectivity counterpart to the physical connections and explored the relationships between the functional and structural connectivity matrices. The functional connectivity matrices developed in this work map the entire rat brain. The results demonstrate that where structural connectivities exist, functional connectivities exist as well. The methodologies used to create the functional and structural analyses were completely independent.

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Zaidel, Liam. "Changes in brain functional connectivity following Donepezil treatment in Alzheimer's Disease." Access to abstract only; dissertation is embargoed until after 5/16/2007, 2006. http://www4.utsouthwestern.edu/library/ETD/etdDetails.cfm?etdID=175.

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Abou, Elseoud A. (Ahmed). "Exploring functional brain networks using independent component analysis:functional brain networks connectivity." Doctoral thesis, Oulun yliopisto, 2013. http://urn.fi/urn:isbn:9789526201597.

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Abstract Functional communication between brain regions is likely to play a key role in complex cognitive processes that require continuous integration of information across different regions of the brain. This makes the studying of functional connectivity in the human brain of high importance. It also provides new insights into the hierarchical organization of the human brain regions. Resting-state networks (RSNs) can be reliably and reproducibly detected using independent component analysis (ICA) at both individual subject and group levels. A growing number of ICA studies have reported altered functional connectivity in clinical populations. In the current work, it was hypothesized that ICA model order selection influences characteristics of RSNs as well as their functional connectivity. In addition, it was suggested that high ICA model order could be a useful tool to provide more detailed functional connectivity results. RSNs’ characteristics, i.e. spatial features, volume and repeatability of RSNs, were evaluated, and also differences in functional connectivity were investigated across different ICA model orders. ICA model order estimation had a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Notably, at low model orders neuroanatomically and functionally different units tend to aggregate into large singular RSN components, while at higher model orders these units become separate RSN components. Disease-related differences in functional connectivity also seem to alter as a function of ICA model order. The volume of between-group differences reached maximum at high model orders. These findings demonstrate that fine-grained RSNs can provide detailed, disease-specific functional connectivity alterations. Finally, in order to overcome the multiple comparisons problem encountered at high ICA model orders, a new framework for group-ICA analysis was introduced. The framework involved concatenation of IC maps prior to permutation tests, which enables statistical inferences from all selected RSNs. In SAD patients, this new correction enabled the detection of significantly increased functional connectivity in eleven RSNs
Tiivistelmä Toiminnallisten aivoalueiden välinen viestintä on todennäköisesti avainasemassa kognitiivisissa prosesseissa, jotka edellyttävät jatkuvaa tiedon integraatiota aivojen eri alueiden välillä. Tämä tekee ihmisaivojen toiminnallisen kytkennällisyyden tutkimuksesta erittäin tärkeätä. Kytkennälllisyyden tutkiminen antaa myös uutta tietoa ihmisaivojen osa-alueiden välisestä hierarkiasta. Aivojen hermoverkot voidaan luotettavasti ja toistettavasti havaita lepotilan toiminnasta yksilö- ja ryhmätasolla käyttämällä itsenäisten komponenttien analyysia (engl. Independent component analysis, ICA). Yhä useammat ICA-tutkimukset ovat raportoineet poikkeuksellisia toiminnallisen konnektiviteetin muutoksia kliinisissä populaatioissa. Tässä tutkimuksessa hypotetisoitiin, että ICA:lla laskettaujen komponenttien lukumäärä (l. asteluku) vaikuttaa tuloksena saatujen hermoverkkojen ominaisuuksiin kuten tilavuuteen ja kytkennällisyyteen. Lisäksi oletettiin, että korkea ICA-asteluku voisi olla herkempit tuottamaan yksityiskohtaisia toiminnallisen jaottelun tuloksia. Aivojen lepotilan hermoverkkojen ominaisuudet, kuten anatominen jakautuminen, volyymi ja lepohermoverkkojen havainnoinnin toistettavuus evaluoitin. Myös toiminnallisen kytkennällisyyden erot tutkitaan eri ICA-asteluvuilla. Havaittiin että asteluvulla on huomattava vaikutus aivojen lepotilan hermoverkkojen tilaominaisuuksiin sekä niiden jakautumiseen alaverkoiksi. Pienillä asteluvuilla hermoverkojen neuroanatomisesti erilliset yksiköt pyrkivät keräytymään laajoiksi yksittäisiksi komponenteiksi, kun taas korkeammilla asteluvuilla ne havaitaan erillisinä. Sairauksien aiheuttamat muutokset toiminnallisessa kytkennällisyydessä näyttävät muuttuvan myös ICA asteluvun mukaan saavuttaen maksiminsa korkeilla asteluvuilla. Korkeilla asteluvuilla voidaan havaita yksityiskohtaisia, sairaudelle ominaisia toiminnallisen konnektiviteetin muutoksia. Korkeisiin ICA asteluvun liittyvän tilastollisen monivertailuongelman ratkaisemiseksi kehitimme uuden menetelmän, jossa permutaatiotestejä edeltävien itsenäisten IC-karttoja yhdistämällä voidaan tehdä luotettava tilastollinen arvio yhtä aikaa lukuisista hermoverkoista. Kaamosmasennuspotilailla esimerkiksi kehittämämme korjaus paljastaa merkittävästi lisääntynyttä toiminnallista kytkennällisyyttä yhdessätoista hermoverkossa

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Hsu, Chun Liang. "Exploring differences in functional connectivity between senior fallers and non-fallers." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43555.

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Background: Falls among seniors are a major health issue. About 30% of community-dwelling adults aged 65 years and older experience one or more falls per year. Although not all falls lead to injury, 20% require medical attention and 5% result in fracture. Fall-related injuries are the leading cause of mortality due to unintentional injuries among those 65 and older. Key falls risk factors are categorized into physical factors (e.g. gait speed, balance, muscle strength, etc.) and neurocognitive factors (e.g. cognitive performance, brain volume, etc.). To date, few studies have examined the brain function on falls risk. My thesis explores this question through functional connectivity MRI analysis. Method: A cross-sectional functional magnetic resonance imaging study consisted of 44 (23 non-fallers and 21 fallers) community dwelling older adults. Participants performed the finger tapping motor task and I examined for differences in functional connectivity of four age-related neural networks: default mode network (DMN), fronto-executive network (FE), fronto-parietal network (FP), and motor network (Mot). Results: Significant between-group differences were identified in between-network functional connectivity. Fallers showed decreased connectivity between the FP network and Mot network (p<0.05) and increased connectivity between the FP network and DMN (p=0.04). No significant within-network differences were observed between the two groups. Conclusion: Results from this study extend our current knowledge on the neural basis of falls in community-dwelling older adults, and suggest a history of falls is associated with disruptions in neural network patterns that are undetectable by traditional clinical testing. Thus, a history of falls may be an early clinical biomarker for dementia risk. Future research is required to examine the directionality of this relationship as well as explore innovative falls-prevention strategies.

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Masud, Mohammad Shahed. "New statistical methods to derive functional connectivity from multiple spike trains." Thesis, University of Plymouth, 2011. http://hdl.handle.net/10026.1/547.

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Analysis of functional connectivity of simultaneously recorded multiple spike trains is one of the major issues in the neuroscience. The progress of the statistical methods to the analysis of functional connectivity of multiple spike trains is relatively slow. In this thesis two statistical techniques are presented to the analysis of functional connectivity of multiple spike trains. The first method is known as the modified correlation grid (MCG). This method is based on the calculation of cross-correlation function of all possible pair-wise spike trains. The second technique is known as the Cox method. This method is based on the modulated renewal process (MRP). The original paper on the application of the Cox method (Borisyuk et al., 1985) to neuroscience data was used to analyse only pairs and triplets of spike trains. This method is further developed in this thesis to support simultaneously recorded of any possible set of multiple spike trains. A probabilistic model is developed to test the Cox method. This probabilistic model is based on the MRP. Due to the common probabilistic basis of the probabilistic model and the Cox method, the probabilistic model is a convenient technique to test the Cox method. A new technique based on a pair-wise analysis of Cox method known as the Cox metric is presented to find the groups of coupled spike trains. Another new technique known as motif analysis is introduced which is useful in identifying interconnections among the spike trains. This technique is based on the triplet-wise analysis of the Cox method. All these methods are applied to several sets of spike trains generated by the Enhanced Leaky and Integrate Fire (ELIF) model. The results suggest that these methods are successful for analysing functional connectivity of simultaneously recorded multiple spike trains. These methods are also applied to an experimental data recorded from cat’s visual cortex. The connection matrix derived from the experimental data by the Cox method is further applied to the graph theoretical methods.

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Su, M. T. "Functional and structural connectivity of reading networks in the adult brain." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1527606/.

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Language processing draws upon many distributed regions in the brain. Reading in particular is a skill that emerges from the interaction between brain regions involved in phonological and orthographical processing. This project examined the reading network in adults (18-35 years old) with and without developmental dyslexia. Each participant was assessed on a comprehensive battery of standardised neuropsychological tests, which assessed IQ, reading accuracy and comprehension, spelling, phonological processing, working memory, grammatical understanding, motor coordination, and expressive and receptive language skills. In addition, each participant underwent a non-invasive MRI scan, during which structural and functional images were acquired. More specifically, T1-weighted and diffusion-weighted images were acquired to assess structural networks in the brain, whereas a simple reading task and resting-state fMRI were acquired to assess the functional networks involved in reading. Individuals with dyslexia were found to show reduced activation and reduced connectivity in regions typically associated with skilled reading. Moreover, results suggested that they rely on more effortful processing and attentional mechanisms instead to compensate for their reading difficulties. All in all, results indicated that individuals with developmental dyslexia had abnormal functional and structural brain networks related to reading performance, as well as other functions, such as working memory. These findings suggest that for successful reading remediation, it is important to focus on the integration of phonology with orthography, as well as with working memory. Literacy problems such as developmental dyslexia are thus better characterised as a complex disorder with multiple deficits rather than by a single phonological deficit.

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Wilson, Rebecca. "Investigating dynamic functional connectivity during NREM sleep using combined EEG-fMRI." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6777/.

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Brain activity recoded with EEG during sleep is shown to be dynamic. However the relationship between this dynamic activity and the brain’s functional architecture is not well understood. The aim is to investigate the sensitivity of functional magnetic resonance imaging (fMRI) functional connectivity (FC) in the assessment of dynamic changes in brain function with sleep stage, focussing on the FC of intrinsically connected networks (ICNs) underlying functionality. Firstly the dynamic capability of resting-state fMRI signal fluctuations to calculate FC is investigated, highlighting the benefits of dynamic FC analysis and the validity of measuring FC using thirty-second epochs. Simultaneous EEG-fMRI was then used to investigate the effects of sleep on ICN FC, showing ICN re-organisation with sleep stage, which is modulated by prior wakefulness and sleep history. Furthermore, the network reorganisation was specific to certain ICNs, providing evidence for their association with sleep-wake behaviour. We also show FC variability between epochs of the same sleep stage, suggesting additional dynamic FC changes across the sleep cycle, a promising area of future investigation. Overall, this work demonstrates that dynamic FC is a useful measure of brain activity during sleep and regionally specific functional brain reorganisation can be used as a sensitive marker of the sleeping brain.

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Dissertations / Theses on the topic 'Functional connectivity'

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