https://archive-ouverte.unige.ch/unige:104893/ATTACHMENT01

The dynamic functional connectome: State-of-the-art and perspectives

Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the construction of classification methods based on deep learning architectures applied on brain regions defined by the Automated Anatomical Labeling (AAL). Gray Matter (GM) images from each brain area have been split into 3D patches according to the regions defined by the AAL atlas and these patches are used to train different deep belief networks. An ensemble of deep belief networks is then composed where the final prediction is determined by a voting scheme. Two deep learning based structures and four different voting schemes are implemented and compared, giving as a result a potent classification architecture where discriminative features are computed in an unsupervised fashion. The resulting method has been evaluated using a large dataset from the Alzheimer's disease Neuroimaging Initiative (ADNI). Classification results assessed by cross-validation prove that the proposed method is not only valid for differentiate between controls (NC) and AD images, but it also provides good performances when tested for the more challenging case of classifying Mild Cognitive Impairment (MCI) Subjects. In particular, the classification architecture provides accuracy values up to 0.90 and AUC of 0.95 for NC/AD classification, 0.84 and AUC of 0.91 for stable MCI/AD classification and 0.83 and AUC of 0.95 for NC/MCI converters classification.

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer’s Disease

Regulation of the cerebral circulation relies on the complex interplay between cardiovascular, respiratory, and neural physiology. In health, these physiologic systems act to maintain an adequate cerebral blood flow (CBF) through modulation of hydrodynamic parameters; the resistance of cerebral vessels, and the arterial, intracranial, and venous pressures. In critical illness, however, one or more of these parameters can be compromised, raising the possibility of disturbed CBF regulation and its pathophysiologic sequelae. Rigorous assessment of the cerebral circulation requires not only measuring CBF and its hydrodynamic determinants but also assessing the stability of CBF in response to changes in arterial pressure (cerebral autoregulation), the reactivity of CBF to a vasodilator (carbon dioxide reactivity, for example), and the dynamic regulation of arterial pressure (baroreceptor sensitivity). Ideally, cerebral circulation monitors in critical care should be continuous, physically robust, allow for both regional and global CBF assessment, and be conducive to application at the bedside. Regulation of the cerebral circulation is impaired not only in primary neurologic conditions that affect the vasculature such as subarachnoid haemorrhage and stroke, but also in conditions that affect the regulation of intracranial pressure (such as traumatic brain injury and hydrocephalus) or arterial blood pressure (sepsis or cardiac dysfunction). Importantly, this impairment is often associated with poor patient outcome. At present, assessment of the cerebral circulation is primarily used as a research tool to elucidate pathophysiology or prognosis. However, when combined with other physiologic signals and online analytical techniques, cerebral circulation monitoring has the appealing potential to not only prognosticate patients, but also direct critical care management.

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Regulation of the cerebral circulation: bedside assessment and clinical implications

Discovering Statistics Using SPSS

Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG

Ischemic stroke is associated with motor impairment and increased incidence of affective disorders such as anxiety/clinical depression. In non-stroke populations, successful management of such disorders and symptoms has been reported following diet supplementation with long chain omega-3-polyunsaturated-fatty-acids (PUFAs). However, the potential protective effects of PUFA supplementation on affective behaviors after experimentally induced stroke and sham surgery have not been examined previously. This study investigated the behavioral effects of PUFA supplementation over a 6-week period following either middle cerebral artery occlusion or sham surgery in the hooded-Wistar rat. The PUFA diet supplied during the acclimation period prior to surgery was found to be associated with an increased risk of acute hemorrhage following the reperfusion component of the surgery. In surviving animals, PUFA supplementation did not influence infarct size as determined 6 weeks after surgery, but did decrease omega-6-fatty-acid levels, moderate sickness behaviors, acute motor impairment, and longer-term locomotor hyperactivity and depression/anxiety-like behavior.

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Nicki Constantinou

Papers

Fish Oil Diet Associated with Acute Reperfusion Related Hemorrhage, and with Reduced Stroke-Related Sickness Behaviors and Motor Impairment