Analysis of the oscillatory activity of the brain. Towards the understanding of the normal cognition and brain disorders
General Objective: MEG-based imaging and biomarker development. Application to neurological diseases.
Description: MEG imaging, multimodality, simulation tools and multivariate and non-linear analysis for cognitive neuroscience and clinical neurology. Study of the brain connectivity and synchronization phenomena for cognitive neuroscience and clinical applications. Biomarkers for the early detection of dementia. Profiles of functional connectivity and network architecture in early stages of AD to achieve a prediction value of who will develop AD. Assessment of the plasticity phenomena and network reorganization in patients with Traumatic Brain Injury and stroke. Study of the brain oscillatory activity associated with emotions and its implication in psychiatric disorders such as depression or Post-Traumatic Stress Disorder. Neurophysiological mechanisms of memory control or the intimate relations between memory and executive functions. Working memory and attentional process. Advanced analysis tools for the analysis of magnetoencephalographic temporal series including functional connectivity algorithms in sensor and in source space.
• Cognitive and Computational Neuroscience
• Clinical Neuroscience
• Computational Systems Biology
• Biological Networks
• Advanced Applied Mathematics to Biological Systems
• Neuromorphic Voice Processing
• Data Mining and Simulation
Contact: Fernando Maestú Unturbe
In this figure is depicted the functional connectivity profile at the sensor space of Mild Cognitive Impairment patients with increased genetic risk for the developing of dementia. Notice the increased fronto-posterior and interhemispheric connectivity during a resting state condition.
This figure is showing the reduced power of the signal at the high alpha frequency band in patients with Mild Cognitive Impairment in comparison with controls. Notice that this reduction in power is associated with episodic memory deficits in this patients.
Here we show those links which better differentiate between controls and MCI patients after computing a data mining process. This links are representing the increased synchronization in MCI patients in comparison to controls.