Bayesian comparison of neurovascular coupling models using EEG-fMRI

Area of Science:

• Neuroscience
• Biophysics
• Medical Imaging

Background:

• Functional magnetic resonance imaging (fMRI) using blood oxygenation level-dependent (BOLD) contrast is a key tool for brain research.
• The precise relationship between neuronal activity and the BOLD signal (neurovascular coupling) remains debated.
• Understanding neurovascular coupling is crucial for interpreting fMRI findings and relating them to other neural measures.

Purpose of the Study:

• To investigate and differentiate between various neurovascular coupling mechanisms.
• To determine the relative contributions of synaptic and spiking neuronal activity to the BOLD response.
• To explore how neuronal firing rates influence these contributions.

Main Methods:

• Development of a modeling framework integrating biophysically informed mathematical models.
• Acquisition of simultaneous Electroencephalography (EEG) and fMRI data during a visual stimulation task.
• Utilizing Bayesian model comparison to evaluate different neurovascular coupling hypotheses.

Main Results:

• The BOLD signal is influenced by both synaptic and spiking neuronal activity.
• The relative contribution of synaptic versus spiking activity to the BOLD signal is dependent on the underlying neuronal firing rate.
• At low firing rates, synaptic activity primarily drives the BOLD response; at high firing rates, both synaptic and spiking activity are necessary.

Conclusions:

• The study provides a novel framework for non-invasively inferring synaptic and spiking activity from EEG-fMRI data.
• Neurovascular coupling is a complex process where the contribution of different neuronal activities varies dynamically.
• This research refines our understanding of the BOLD signal, enhancing the interpretation of fMRI studies.