TY - JOUR T1 - Bayesian Comparison of Neurovascular Coupling Models Using EEG-fMRI A1 - Rosa, Maria J. A1 - Kilner, James M. A1 - Penny, Will D. Y1 - 2011/06/16 N2 - Author Summary Functional magnetic resonance imaging (fMRI), with blood oxygenation level-dependent (BOLD) contrast, is a widely used technique for studying the human brain. However, the relationship between neuronal activity and blood flow, the basis of fMRI, is still under much debate. A growing body of evidence from animal studies suggests that fMRI signals are more closely coupled to synaptic input activity than to the spiking output of a neuronal population. However, data from neurosurgical patients does not seem to support this view and this hypothesis hasn't yet been tested in the healthy human brain. Here we design a powerful and efficient modelling framework that can be used to non-invasively compare different biologically plausible hypotheses of neurovascular coupling. We use this framework to explore the contribution of these two aspects of neuronal activity (synaptic and spiking) to the generation of hemodynamic signals in human visual cortex, with Electroencephalographic (EEG)-fMRI data. Our results provide preliminary evidence that depending on the frequency of the visual stimulus and underlying firing rate, fMRI relates closer to synaptic activity (low-frequencies) or to both synaptic and spiking activities (high-frequencies). JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 6 UR - https://doi.org/10.1371/journal.pcbi.1002070 SP - e1002070 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002070 ER -