Development of new mathematical models for determination of image biomarkers of cerebral function from fMRI data

Functional magnetic resonance imaging (fMRI) measures the blood oxygen level dependent (BOLD) response to neural activation, the so-called neurovascular coupling. Since the introduction of fMRI our knowledge of brain function has increased substantially.

The potential of fMRI to provide image biomarkers for brain disorders has been strongly emphasized but the translation to diagnostic radiology has been slow.

The slow clinical translation is partly caused by the entanglement of neural and vascular contributions to the BOLD response that complicates the interpretation of acquired data.

However, as we have shown previously, high-resolution preclinical data can inform mathematical models that provide mechanistic interpretations of the BOLD response in fMRI in terms of neuronal, intracellular, and vascular dynamics. Thus, such neurovascular coupling models bridge the gap between neural and vascular contributions to the BOLD response.

In the present grant proposal, we will aim to improve our neurovascular coupling model by adding neural and vascular mechanisms concordant with multimodal MRI measurements and to advance the model to describe cognitive processes in multiple brain regions by mechanistic functional connectivity modelling.