109 research outputs found

    Quantitation in MRI : application to ageing and epilepsy

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    Multi-atlas propagation and label fusion techniques have recently been developed for segmenting the human brain into multiple anatomical regions. In this thesis, I investigate possible adaptations of these current state-of-the-art methods. The aim is to study ageing on the one hand, and on the other hand temporal lobe epilepsy as an example for a neurological disease. Overall effects are a confounding factor in such anatomical analyses. Intracranial volume (ICV) is often preferred to normalize for global effects as it allows to normalize for estimated maximum brain size and is hence independent of global brain volume loss, as seen in ageing and disease. I describe systematic differences in ICV measures obtained at 1.5T versus 3T, and present an automated method of measuring intracranial volume, Reverse MNI Brain Masking (RBM), based on tissue probability maps in MNI standard space. I show that this is comparable to manual measurements and robust against field strength differences. Correct and robust segmentation of target brains which show gross abnormalities, such as ventriculomegaly, is important for the study of ageing and disease. We achieved this with incorporating tissue classification information into the image registration process. The best results in elderly subjects, patients with TLE and healthy controls were achieved using a new approach using multi-atlas propagation with enhanced registration (MAPER). I then applied MAPER to the problem of automatically distinguishing patients with TLE with (TLE-HA) and without (TLE-N) hippocampal atrophy on MRI from controls, and determine the side of seizure onset. MAPER-derived structural volumes were used for a classification step consisting of selecting a set of discriminatory structures and applying support vector machine on the structural volumes as well as morphological similarity information such as volume difference obtained with spectral analysis. Acccuracies were 91-100 %, indicating that the method might be clinically useful. Finally, I used the methods developed in the previous chapters to investigate brain regional volume changes across the human lifespan in over 500 healthy subjects between 20 to 90 years of age, using data from three different scanners (2x 1.5T, 1x 3T), using the IXI database. We were able to confirm several known changes, indicating the veracity of the method. In addition, we describe the first multi-region, whole-brain database of normal ageing

    The face of early cognitive decline? Shape and asymmetry predict choice reaction time independent of age, diet or exercise

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    Slower reaction time is a measure of cognitive decline and can occur as early as 24 years of age. We are interested if developmental stability predicts cognitive performance independent of age and lifestyle (e.g., diet and exercise). Developmental stability is the latent capacity to buffer ontogenetic stressors and is measured by low fluctuating asymmetry (FA). FA is random – with respect to largest side – departures from perfect morphological symmetry. Degree of asymmetry has been associated with physical fitness, morbidity and mortality in many species, including humans. We expected that low FA (independent of age, diet and exercise) will predict faster choice reaction time (i.e., correct keyboard responses to stimuli appearing in a random location on a computer monitor). Eighty-eight university students self-reported their fish product consumption, exercise, had their faces 3D scanned and cognitive performance measured. Unexpectedly, increased fish product consumption was associated with worsened choice reaction time. Facial asymmetry and multiple face shape variation parameters predicted slower choice reaction time independent of sex, age, diet or exercise. Future work should develop longitudinal interventions to minimize early cognitive decline among vulnerable people (e.g., those who have experienced ontogenetic stressors affecting optimal neurocognitive development).

    Deep learning of brain asymmetry digital biomarkers to support early diagnosis of cognitive decline and dementia

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    Early identification of degenerative processes in the human brain is essential for proper care and treatment. This may involve different instrumental diagnostic methods, including the most popular computer tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. These technologies provide detailed information about the shape, size, and function of the human brain. Structural and functional cerebral changes can be detected by computational algorithms and used to diagnose dementia and its stages (amnestic early mild cognitive impairment - EMCI, Alzheimer’s Disease - AD). They can help monitor the progress of the disease. Transformation shifts in the degree of asymmetry between the left and right hemispheres illustrate the initialization or development of a pathological process in the brain. In this vein, this study proposes a new digital biomarker for the diagnosis of early dementia based on the detection of image asymmetries and crosssectional comparison of NC (normal cognitively), EMCI and AD subjects. Features of brain asymmetries extracted from MRI of the ADNI and OASIS databases are used to analyze structural brain changes and machine learning classification of the pathology. The experimental part of the study includes results of supervised machine learning algorithms and transfer learning architectures of convolutional neural networks for distinguishing between cognitively normal subjects and patients with early or progressive dementia. The proposed pipeline offers a low-cost imaging biomarker for the classification of dementia. It can be potentially helpful to other brain degenerative disorders accompanied by changes in brain asymmetries

    Visual Cortex

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    The neurosciences have experienced tremendous and wonderful progress in many areas, and the spectrum encompassing the neurosciences is expansive. Suffice it to mention a few classical fields: electrophysiology, genetics, physics, computer sciences, and more recently, social and marketing neurosciences. Of course, this large growth resulted in the production of many books. Perhaps the visual system and the visual cortex were in the vanguard because most animals do not produce their own light and offer thus the invaluable advantage of allowing investigators to conduct experiments in full control of the stimulus. In addition, the fascinating evolution of scientific techniques, the immense productivity of recent research, and the ensuing literature make it virtually impossible to publish in a single volume all worthwhile work accomplished throughout the scientific world. The days when a single individual, as Diderot, could undertake the production of an encyclopedia are gone forever. Indeed most approaches to studying the nervous system are valid and neuroscientists produce an almost astronomical number of interesting data accompanied by extremely worthy hypotheses which in turn generate new ventures in search of brain functions. Yet, it is fully justified to make an encore and to publish a book dedicated to visual cortex and beyond. Many reasons validate a book assembling chapters written by active researchers. Each has the opportunity to bind together data and explore original ideas whose fate will not fall into the hands of uncompromising reviewers of traditional journals. This book focuses on the cerebral cortex with a large emphasis on vision. Yet it offers the reader diverse approaches employed to investigate the brain, for instance, computer simulation, cellular responses, or rivalry between various targets and goal directed actions. This volume thus covers a large spectrum of research even though it is impossible to include all topics in the extremely diverse field of neurosciences

    Commonalities and differences between schizophrenia and bipolar disorder

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    Etude expérimentale des dynamiques temporelles du comportement normal et pathologique chez le rat et la souris

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    155 p.Modern neuroscience highlights the need for designing sophisticated behavioral readout of internal cognitive states. From a thorough analysis of classical behavioral test, my results supports the hypothesis that sensory ypersensitivity might be the cause of other behavioural deficits, and confirm the potassium channel BKCa as a potentially relevant molecular target for the development of drug medication against Fragile X Syndrome/Autism Spectrum Disorders. I have also used an innovative device, based on pressure sensors that can non-invasively detect the slightest animal movement with unprecedented sensitivity and time resolution, during spontaneous behaviour. Analysing this signal with sophisticated computational tools, I could demonstrate the outstanding potential of this methodology for behavioural phenotyping in general, and more specifically for the investigation of pain, fear or locomotion in normal mice and models of neurodevelopmental and neurodegenerative disorders

    A longitudinal study of cortical EEG to olfactory stimulation : involving inter- and intra- subjective responses

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    This thesis forms the largest and most systematic study of the topographical EEG response to odour. The evolutionary history of the olfactory sense is briefly presented and its relevance to humans in the present day is considered. This thesis examines the information processing that occurs in this sensory system. The type of processing that the olfactory system utilises at each anatomical stage is discussed. The character of olfactory information that may reach neocortical levels in humans is considered in the light of the technology available to detect such information. The neurogenesis of the EEG is considered, together with questions concerning its postulated functional significance. The empirical work carried out uses the most advanced methodology for this type of study. The large number of odourants and subjects, combined with the longitudinal element, make this the most ambitious study of this nature undertaken. The issues surrounding the analysis and interpretation of EEG data arc fully discussed and the impact of Chaos theory is considered. Five major analysis techniques were used on the data collected, but largely negative findings arc reported. The reasons for the failure of this experimental paradigm are discussed and improvements arc suggested for future work. The major contribution of this thesis lies in its exploration of the assumptions of the EEG response to odour. The thesis notes the lack of a conceptual framework that has hindered progress in the area of the "odour" EEG. Recent developments in neural network theory and Chaos theory are highlighted as possible alternative approaches to the modelling and understanding of the olfactory system

    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

    2016 IMSAloquium, Student Investigation Showcase

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    Welcome to the twenty-eighth year of the Student Inquiry and Research Program (SIR)! This is a program that is as old as IMSA. The SIR program represents our unending dedication to enabling our students to learn what it is to be an innovator and to make contributions to what is known on Earth.https://digitalcommons.imsa.edu/archives_sir/1026/thumbnail.jp
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