45 research outputs found

    A Gaussian-mixed Fuzzy Clustering Model on Valence-Arousal-related fMRI Data-Set

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    Previous medical experiments illustrated that Valence and Arousal were high corresponded to brain response by amygdala and orbital frontal cortex through observation by functional magnetic resonance imaging (fMRI). In this paper, Valence-Arousal related fMRI data-set were acquired from the picture stimuli experiments, and finally the relative Valence -Arousal feature values for a given word that corresponding to a given picture stimuli were calculated. Gaussian bilateral filter and independent components analysis (ICA) based Gaussian component method were applied for image denosing and segmenting; to construct the timing signals of Valence and Arousal from fMRI data-set separately, expectation maximal of Gaussian mixed model was addressed to calculate the histogram, and furthermore, Otsu curve fitting algorithm was introduced to scale the computational complexity; time series based Valence -Arousal related curve were finally generated. In Valence-Arousal space, a fuzzy c-mean method was applied to get typical point that represented the word relative to the picture. Analyzed results showed the effectiveness of the proposed methods by comparing with other algorithms for feature extracting operations on fMRI data-set including power spectrum density (PSD), spline, shape-preserving and cubic fitting methods

    Recent Advances in Signal Processing

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    The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    ELECTROPHYSIOLOGICAL MECHANISMS FOR PREPARING CONTROL IN TIME

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    Cognitive control is critical in guiding goal-directed behavior, preparing neural resources and adapting processing to promote optimal action in a given environment. According to the Dual Mechanisms of Control theory (Braver, 2012), control can be dichotomized into proactive and reactive modes of control, utilized reciprocally in ahead-of-time preparation versus last-minute, stimulus-evoked reaction. Although a substantial body of work has tested differences between proactive control and reactive control, the underlying assumption of proactive control as a unitary process has not been systematically investigated. Very little is known as to how or when proactive control is initiated, sustained, or implemented. As time is an integral building block of perception, cognition, and action (Buhusi & Meck, 2005), one should expect temporal information to be integrated into proactive control. Cognitive control is costly (Shenhav, Botvinick, & Cohen, 2013), and a temporally-guided modulation of control may offer substantial cost savings. By measuring proactive control on a sub-second time-scale, we can begin to gauge whether dissociable sub-types of proactive control are utilized demanding on temporal demands. Moreover, by comparing proactive control processes across different temporal demands, we can parse out when different aspects of control are computed and implemented. Through a meta-analytic review and three empirical experiments, this dissertation provides insight into how timing dynamics may influence the computation, maintenance, and instantiation of proactive cognitive control. First, a meta-analysis on the cued control literature reveals that seemingly trivial experimental parameters shape the use of proactive versus reactive control. Two EEG studies then demonstrate how modulating timing dynamics influences prefrontal mechanisms for preparatory cognitive control. In a final EEG study, we compare the mechanisms utilized to retain control goals versus visuo-spatial working memory items. Overall, this dissertation elucidates several novel electrophysiological mechanisms by which timing information is implemented in the computation and retention of cognitive control rules. Further, we provide evidence that individual differences in impulsivity and working memory shape distinct aspects of preparation. The findings reported here make clear that timing information is critical in guiding proactive control processes, and support a fundamental reconsideration of proactive control based on temporal dynamics

    Epilepsy

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    With the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well

    Cerebrovascular dysfunction in cerebral small vessel disease

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    INTRODUCTION: Cerebral small vessel disease (SVD) is the cause of a quarter of all ischaemic strokes and is postulated to have a role in up to half of all dementias. SVD pathophysiology remains unclear but cerebrovascular dysfunction may be important. If confirmed many licensed medications have mechanisms of action targeting vascular function, potentially enabling new treatments via drug repurposing. Knowledge is limited however, as most studies assessing cerebrovascular dysfunction are small, single centre, single imaging modality studies due to the complexities in measuring cerebrovascular dysfunctions in humans. This thesis describes the development and application of imaging techniques measuring several cerebrovascular dysfunctions to investigate SVD pathophysiology and trial medications that may improve small blood vessel function in SVD. METHODS: Participants with minor ischaemic strokes were recruited to a series of studies utilising advanced MRI techniques to measure cerebrovascular dysfunction. Specifically MRI scans measured the ability of different tissues in the brain to change blood flow in response to breathing carbon dioxide (cerebrovascular reactivity; CVR) and the flow and pulsatility through the cerebral arteries, venous sinuses and CSF spaces. A single centre observational study optimised and established feasibility of the techniques and tested associations of cerebrovascular dysfunctions with clinical and imaging phenotypes. Then a randomised pilot clinical trial tested two medications’ (cilostazol and isosorbide mononitrate) ability to improve CVR and pulsatility over a period of eight weeks. The techniques were then expanded to include imaging of blood brain barrier permeability and utilised in multi-centre studies investigating cerebrovascular dysfunction in both sporadic and monogenetic SVDs. RESULTS: Imaging protocols were feasible, consistently being completed with usable data in over 85% of participants. After correcting for the effects of age, sex and systolic blood pressure, lower CVR was associated with higher white matter hyperintensity volume, Fazekas score and perivascular space counts. Lower CVR was associated with higher pulsatility of blood flow in the superior sagittal sinus and lower CSF flow stroke volume at the foramen magnum. Cilostazol and isosorbide mononitrate increased CVR in white matter. The CVR, intra-cranial flow and pulsatility techniques, alongside blood brain barrier permeability and microstructural integrity imaging were successfully employed in a multi-centre observational study. A clinical trial assessing the effects of drugs targeting blood pressure variability is nearing completion. DISCUSSION: Cerebrovascular dysfunction in SVD has been confirmed and may play a more direct role in disease pathogenesis than previously established risk factors. Advanced imaging measures assessing cerebrovascular dysfunction are feasible in multi-centre studies and trials. Identifying drugs that improve cerebrovascular dysfunction using these techniques may be useful in selecting candidates for definitive clinical trials which require large sample sizes and long follow up periods to show improvement against outcomes of stroke and dementia incidence and cognitive function

    Proceedings of the 7th Sound and Music Computing Conference

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    Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010

    Tätigkeitsbericht 2017-2019/20

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