Dacosta, R. 1, 2 , Graña, M. 1 & Mataro, M. 2
1 Computational Intelligence Group, UPV/EHU
2 Neuropsychology Group of the Department of Psychiatry and Clinical Psychobiology, Faculty of Medicine, University of Barcelona
The main aim of the current PhD research was to identify functional, structural and metabolic changes of patients suffering from an ischemic stroke and to attempt to relate them with cognitive recovery by applying the most up-to-date neuroimaging techniques.
Much of our current knowledge in relation to cognitive brain function is based on the modular paradigm, in which brain areas are postulated to act as independent processors for specific complex cognitive function. This paradigm, although has helped to build much of the present understanding of disease pathophysiology, has serious limitations when applied to the explanation of clinical and cognitive dysfunctions after a neurological insult. In stroke, clinical and cognitive deficits are not always easily explicable by the lesion localization itself, lesions of some areas tend to have more severed effects than others and individual outcomes seem to be due more to residual anatomy than to lesion localization. This scenario makes difficult to predict which patient will recover and will reintegrate into society and which will be relegated to a life of disability.
Novel research utilizing probabilistic Independent Component Analysis, Diffusion Tensor Imaging, Spectroscopy Imaging, and Graph Theory Analysis has reported properties of the human brain as a complex network as well as has revealed that the contralesional hemisphere is not so ?healthy? as assumed at first glance.