Sunrise Session
Hemodynamic Modelling of fMRI Time Signals
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Session Topic: Educational Q&A: fMRI/Diffusion/Perfusion Sunrise
Session Sub-Topic: Hemodynamic Modelling of fMRI Time Signals
Sunrise Session
ORGANIZERS: Susan Francis, Richard Buxton, Benedikt Poser
| Tuesday Parallel 1 Live Q&A | Tuesday, 11 August 2020, 13:45 - 14:30 UTC | Moderators: Richard Buxton |
Skill Level: Intermediate
Session Number: S-M-04
Overview
This entry-level Sunrise course is part of the four-day series on signal modelling, spanning from fMRI, to ASL perfusion, microstructure, and diffusion micro-structure modelling. The focus of this session is hemodynamic modelling of fMRI time signals. The aim is to provide curious researchers who want to get started with fMRI signal modelling with a concise but comprehensive overview on the topic, followed by an actual step-by-step live demonstration. As such, the first 30 minutes will be dedicated to introducing the topic, covering the basics of neurovascular coupling, the contributors to the hemodynamic response (CBF, CBF, CMRO2, BOLD), and describe the common models that explain their relationship and transients. The second speaker will give a live demonstration that illustrates these models and walk the audience through the steps of common modelling scenarios.
Target Audience
Any researchers who want to get started with fMRI signal modelling.
Educational Objectives
As a result of attending this course, participants should be able to:
- Explain the biophysical relationship between the actors in the hemodynamic fMRI response;
- Describe the most common models of neurovascular signals;
- Describe the scope and limitations of these models; and
- Demonstrate simple modeling tasks themselves.
| Biophysical Modelling to Deconvolve Neurovascular Signals
Jingyuan Chen
Functional magnetic resonance imaging (fMRI) tracks neuronal activities indirectly through neurovascular modulation of T2 or T2* relaxivity consequent to altered neuronal metabolism. Dissecting neurovascular dynamics driving the macroscopic fMRI fluctuations will not only lead to more accurate characterizations of neuronal activities, but also provide a wealth of meaningful biophysical metrics for clinical and neuroscience inferences. This lecture will first explain how various hemodynamic components responsive to neuronal activities (including oxygen metabolism, cerebral blood flow and blood volume) give rise to transient dynamics in fMRI signals; then provide an overview of models commonly employed to deconvolve neurovascular information.
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