Neurovascular networks: a new framework for modelling structural and functional connectivity in aging mice
The emerging consensus that the brain functions as a single, complex system has led to the popularity of a network approach to studying brain function. Functional connectivity, a measure of the coordinated activity between brain regions, has been observed in neuroimaging studies to change during aging and could be related to cognitive decline. However, in humans, neuronal activity cannot be measured directly. Instead, our main neuroimaging technique measures blood oxygenation which is an indicator of neuronal activity through the coupling between neurons and blood vessels. Given that aging is associated with changes in blood vessels and in neuron-vessel coupling, the neuronal and vascular contributions to functional connectivity during aging cannot be distinguished. Furthermore, the timeline of neurovascular changes during normal aging is not well known because it is typically measured only at one point in time.
We propose to leverage innovative tools in 1) longitudinal brain imaging in the mouse to observe the evolution of neurons and blood vessels during aging; 2) mathematical modeling to study the connectivity of neurons from observed patterns of neuronal activity. Using this model, we will predict and then experimentally measure the effect on neuronal dynamics of perturbating blood vessels in a way similar to what naturally occurs in the aging brain, by causing microscopic strokes in capillaries. Our hypothesis is that during normal aging, vascular micro-strokes precede in time and could cause changes in neuronal activity. Our approach creates a new line of research combining measures of neuro-vascular coupling with models of neuronal networks, allowing to better understand the process of normal brain aging. The results are expected to improve the power of neuroimaging for studying aging and could help guide future studies of preventive and curative approaches for alleviating the consequences of aging on brain function.
Michèle Desjardins , Université Laval
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