ArticlePLoS computational biology2011
Bayesian comparison of neurovascular coupling models using EEG-fMRI.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Multimodal EEG-MRI Neuroimaging in Schizophrenia-A Systematic and Mechanistic Review.Journal of clinical medicine · 2026Review
- Neuromodulation of Cerebral Blood Flow: A Physiological Mechanism and Methodological Review of Neurovascular Coupling.Bioengineering (Basel, Switzerland) · 2025Review
- Traces of EEG-fMRI coupling reveals neurovascular dynamics on sleep inertia.Scientific reports · 2024Article
- Toward an integrative neurovascular framework for studying brain networks.Neurophotonics · 2022Article
- Modeling the Hemodynamic Response Function Using EEG-fMRI Data During Eyes-Open Resting-State Conditions and Motor Task Execution.Brain topography · 2022Article
- Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans.PLoS computational biology · 2021Article
- Adiabatic dynamic causal modelling.NeuroImage · 2021Article
- Article
- Determining Excitatory and Inhibitory Neuronal Activity from Multimodal fMRI Data Using a Generative Hemodynamic Model.Frontiers in neuroscience · 2017Article
- Neurovascular Interactions in the Neurologically Compromised Neonatal Brain.Advances in experimental medicine and biology · 2016Article
- Investigating Human Neurovascular Coupling Using Functional Neuroimaging: A Critical Review of Dynamic Models.Frontiers in neuroscience · 2015Review
- Do monkey F5 mirror neurons show changes in firing rate during repeated observation of natural actions?Journal of neurophysiology · 2014Article
- Contributions and complexities from the use of in vivo animal models to improve understanding of human neuroimaging signals.Frontiers in neuroscience · 2014Review
- Transfer Function between EEG and BOLD Signals of Epileptic Activity.Frontiers in neurology · 2013Article
- Using TMS to study the role of the articulatory motor system in speech perception.Aphasiology · 2012Article
- Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells.PLoS computational biology · 2012Article
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3 authors.
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Abstract
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.
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