Rosa, MJ and Kilner, JM and Penny, WD (2011) Bayesian Comparison of Neurovascular Coupling Models Using EEG-fMRI. PLOS COMPUT BIOL , 7 (6) , Article e1002070. 10.1371/journal.pcbi.1002070.
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Functional magnetic resonance imaging (fMRI), with blood oxygenation level-dependent (BOLD) contrast, is a widely used technique for studying the human brain. However, it is an indirect measure of underlying neuronal activity and the processes that link this activity to BOLD signals are still a topic of much debate. In order to relate findings from fMRI research to other measures of neuronal activity it is vital to understand the underlying neurovascular coupling mechanism. Currently, there is no consensus on the relative roles of synaptic and spiking activity in the generation of the BOLD response. Here we designed a modelling framework to investigate different neurovascular coupling mechanisms. We use Electroencephalographic (EEG) and fMRI data from a visual stimulation task together with biophysically informed mathematical models describing how neuronal activity generates the BOLD signals. These models allow us to non-invasively infer the degree of local synaptic and spiking activity in the healthy human brain. In addition, we use Bayesian model comparison to decide between neurovascular coupling mechanisms. We show that the BOLD signal is dependent upon both the synaptic and spiking activity but that the relative contributions of these two inputs are dependent upon the underlying neuronal firing rate. When the underlying neuronal firing is low then the BOLD response is best explained by synaptic activity. However, when the neuronal firing rate is high then both synaptic and spiking activity are required to explain the BOLD signal.
|Title:||Bayesian Comparison of Neurovascular Coupling Models Using EEG-fMRI|
|Open access status:||An open access publication. A version is also available from UCL Discovery.|
|Additional information:||© 2011 Rosa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This work was supported by the Wellcome Trust and the Portuguese Foundation for Science and Technology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.|
|Keywords:||DYNAMIC CAUSAL-MODELS, NITRIC-OXIDE, BOLD SIGNAL, NEURONAL-ACTIVITY, POPULATION-DYNAMICS, CEREBRAL ENERGETICS, MATHEMATICAL-MODEL, VISUAL-STIMULATION, GAMMA-OSCILLATIONS, FIELD POTENTIALS|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Imaging Neuroscience|
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Motor Neuroscience and Movement Disorders
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