EEG-based indices as outcome measures for a memory rehabilitation treatment in stroke patients

The efficacy of cognitive rehabilitation treatments after stroke is routinely assessed by means of neuropsychological tests battery. More evidences indicate that the neuroplasticity phenomena which occurs after stroke can be characterized by investigating brain networks changes. Despite the efforts in the field, a complete description of connectivity patterns characterizing different phases of cognitive recovery in stroke patients is still missing. In this work, we proposed a combined approach of advanced methodologies for effective connectivity estimation and graph theory for defining EEG-based descriptors able to: i) characterize the brain processes at the basis of a memory rehabilitation treatment and ii)support its clinical evaluation. We derived neurophysiological indices from a previous study on healthy subjects and then we used them as outcome measures of a rehabilitation treatment on stroke-patients.