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Project

Improved classification of Alzheimer's disease assessed from the slowly propagating waves of BOLD intensity, the Quasi-Periodic patterns, observed in dynamic resting-state fMRI in a AD rat model at rest and upon sensory stimulation.

The rsfMRI field has seen a shift from 'static' blood-oxygen level dependent (BOLD) signal analysis to time-resolved dynamic analysis. Dynamic rsfMRI (drsfMRI) is a state-of-the-art approach, which has revealed many new insights into the macro-scale organization of functional networks and could already identify short-lasting large scale spatiotemporal patterns of BOLD activity, the 'Quasi-Periodic Patterns' (QPPs) in humans and rats. The QPPs describe recurring spatiotemporal neural events that display anti-correlation between two major brain networks (DMN and TPN), and therefore represent likely contributors to their functional organisation. Therefore, we reason that QPPs could provide new insights into AD network dysfunction and improve disease diagnosis. We postulate the hypothesis that QPPs would help understand the aberrant DMN and TPN Functional Connectivity (FC) observed in Alzheimer's disease, and might serve as a more sensitive biomarker than conventional rsfMRI measures, improving AD classification both in an early pre-plaque stage as late post-plaque stage. In this project, we will use state-of-the-art MRI to investigate: a) how QPPs in a rat model for AD (TgF344), differs from control animals, b) the vascular contribution to QPPs, c) how these QPPs might interact with sensory stimulation processing, d) how the QPPs acquired at rest or sensory stimulation contribute to the DMN and DMN-TPN FC, and how they improve AD classification.
Date:1 Jan 2020 →  31 Dec 2023
Keywords:NEURODEGENERATIVE BRAIN DISEASES, NEURO MRI, FUNCTIONAL MAGNETIC RESONANCE
Disciplines:Biomedical image processing, Diagnostic radiology, Medical imaging and therapy not elsewhere classified, Neurological and neuromuscular diseases