Skip to main content
Go to the home page of the European Commission (opens in new window)
English en
CORDIS - EU research results
CORDIS

Graph Signal Processing Models for Neurovascular Decoupling.

Project description

Cerebral vessel graph models for neurovascular understanding

The Blood Oxygenation Level Dependent (BOLD) signal is a key fMRI technique for measuring brain activity based on Neurovascular Coupling (NC). However, factors such as physiological changes and NC uncoupling complicate signal interpretation. Since there is no method to separate neuronal activity from vascular responses, BOLD analyses often overlook the role of blood vessels. Supported by the Marie Skłodowska-Curie Actions programme, the GRASPING NERVE project aims to develop a graph model of cerebral vessels to assess cerebrovascular connectivity and integrate BOLD signal fluctuations. This non-invasive approach will improve understanding of NC and facilitate studies on pathological NC uncoupling. The project will validate the model using high and ultra-high MRI fields, comparing BOLD with non-BOLD techniques.

Objective

Blood Oxygenation Level Dependent (BOLD) signal is a widespread functional Magnetic Resonance Imaging (fMRI) technique to non-invasively study brain activity, and it relies on the mechanism of Neurovascular Coupling (NC), i.e. changes in cerebral blood flow driven by neuronal activity. However, there are various confounding factors for NC, such as homoeostatic physiological changes, or NC uncoupling driven by certain pathologies. Currently, there is no method to disentangle the information associated with neuronal activity from the vascular response. This is an important issue in both physiological imaging and brain activity investigation, as the two signal sources act as competing confounding factors. Furthermore, although vessels are the main blood distribution system, they are mostly ignored when taking into account BOLD analyses.
In this project, I will first create a graph model of cerebral vessels to assess “cerebrovascular connectivity”. I will then use graph signal processing, a novel signal processing technique based on graphs, to embed BOLD signal fluctuations into the vascular and the more traditional tractography-based graphs to disentangle the propagation of neuronal activity and blood flow in these two pathways. This technique will allow disentangling the components of NC non-invasively, offering new insight on brain activity and neurovascular coupling, and allowing further studies on pathological NC uncoupling, such as pre-surgical imaging for tumour.
I will apply this model at the macro- (whole-brain) and meso- (grey-matter- layers) scale, connecting the properties of NC in functional imaging between them. The application will be validated in high (3 Tesla) and ultra-high (7 Tesla) MRI fields to address its feasibility for both research and clinical application. Finally, BOLD will be compared with non-BOLD functional techniques, such as Arterial Spin Labelling and Vascular Space Occupancy, to shed light into the imaging of NC and brain activity.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

See all projects funded under this funding scheme

Call for proposal

(opens in new window) HORIZON-MSCA-2022-PF-01

See all projects funded under this call

Coordinator

UNIVERSITEIT MAASTRICHT
Net EU contribution
€ 212 295,04
Address
MINDERBROEDERSBERG 4
6200 MD Maastricht
Netherlands
Region
Zuid-Nederland Limburg (NL) Zuid-Limburg
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data