Accelerated Cognitive Ageing (ACA) is a phenomenon in which patients suffer from a faster decline in cognitive capacity as compared to cognitive decline caused by normal/typical ageing. In other terms, people with ACA tend to have an older brain with respect to cognitive functions than their aged-matched healthy peers. This brain disorder is mainly diagnosed in patients with epilepsy, and, if better understood, could also provide a model for ‘heathy’ cognitive brain ageing.
The ACA is now investigated by psychologists, radiologists and researchers, in order to find neurological origins or effects of such a cognitive decline. Using magnetic resonance imaging (MRI) techniques, these biomarkers are expected to be found in functional networks of the brain and their dynamics.
Also, normal ageing has been proven to be linked to weakened effective connectivity within the Salience network – a dynamic switch between rest and cognitive executive functions. The between-network (between salience and other brain networks) connectivity seem to be less effective in elderly as well. Therefore, the salience network should be investigated thoroughly, especially in terms of functional dynamics.
This project is part of the multi-disciplinary program called Neu3ca (http://neu3ca.org/), which aims at imaging, diagnosing, and treating brain neurodegenerative disorders, such as ACA, that affects the ageing brain.
In this research project we aim at assessing the dynamics of the salience network and its causal relations with other brain networks in functional MRI. We will apply and further develop modeling techniques for this. These techniques include Granger causality analysis, wavelet-based signal analysis, and the results will be correlated with the cognitive test outcomes of the patients. All experiments will be performed and validated on clinical data. Preliminary results have shown already the importance of that salience network in autism. This network and its efficiency is also involved in ageing and showed already dynamics differences in neurodegenerative disorders. Hence, we expect functional dynamics impairments/differences in our ACA group.
Here we aim at assessing thoroughly the salience networks, i.e., within- and between-network correlation and causal analyses. Therefore a deeper understanding of subject-specific salience network (dynamic) connectivity is needed by means of independent component analysis or seed-based (e.g., voxel-to-voxel) approaches. Metrics extracted from those dynamics (or changes in dynamics) should be then regularized and normalized to count for inter-subject variability, and lead to generalization of our findings.