Dataset Information

Differential electrophysiological coupling for positive and negative BOLD responses during unilateral hand movements.

ABSTRACT: The coupling between neural cellular activity and blood oxygen level-dependent (BOLD) signal is of critical importance to the interpretation of fMRI. Largely unknown, however, is the degree to which different neuronal events (i.e., excitation and inhibition) maintain or disrupt the neural-hemodynamic relationship, especially in humans. In the present study, we compared local electroencephalographic (EEG) oscillations and the positive/negative BOLD responses of simultaneously recorded data from healthy human volunteers performing unilateral finger tapping at graded rates. By quantifying the single-trial modulations of EEG using source imaging, we tested for their correlation with positive BOLD response (PBR) and negative BOLD response (NBR) after coregistering their spatial locations. PBR was found to be overlapped with and correlated to the decrease of alpha (8-13 Hz) and beta (13-30 Hz) band EEG in the contralateral sensorimotor cortex. Regional EEG modulations at the sensorimotor cortex further predicted a spatially distributed and interconnected network of motor-related cortical areas. Alternatively, no significant correlation was found at the ipsilateral sensorimotor cortex between the NBR and EEG despite their spatial overlapping. This differential electrophysiological coupling of the positive and negative BOLD responses suggests that the underlying neuronal events may not only influence the direction of the signal change but also the neural-hemodynamic relationship.

SUBMITTER: Yuan H

PROVIDER: S-EPMC3142625 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Differential electrophysiological coupling for positive and negative BOLD responses during unilateral hand movements.

Yuan Han H Perdoni Christopher C Yang Lin L He Bin B

The Journal of neuroscience : the official journal of the Society for Neuroscience 20110601 26

The coupling between neural cellular activity and blood oxygen level-dependent (BOLD) signal is of critical importance to the interpretation of fMRI. Largely unknown, however, is the degree to which different neuronal events (i.e., excitation and inhibition) maintain or disrupt the neural-hemodynamic relationship, especially in humans. In the present study, we compared local electroencephalographic (EEG) oscillations and the positive/negative BOLD responses of simultaneously recorded data from h ...[more]

PMID: 21715623

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Project description:Alongside positive blood oxygenation level-dependent (BOLD) responses associated with interictal epileptic discharges, a variety of negative BOLD responses (NBRs) are typically found in epileptic patients. Previous studies suggest that, in general, up to four mechanisms might underlie the genesis of NBRs in the brain: (i) neuronal disruption of network activity, (ii) altered balance of neurometabolic/vascular couplings, (iii) arterial blood stealing, and (iv) enhanced cortical inhibition. Detecting and classifying these mechanisms from BOLD signals are pivotal for the improvement of the specificity of the electroencephalography-functional magnetic resonance imaging (EEG-fMRI) image modality to identify the seizure-onset zones in refractory local epilepsy. This requires models with physiological interpretation that furnish the understanding of how these mechanisms are fingerprinted by their BOLD responses. Here, we used a Windkessel model with viscoelastic compliance/inductance in combination with dynamic models of both neuronal population activity and tissue/blood O2 to classify the hemodynamic response functions (HRFs) linked to the above mechanisms in the irritative zones of epileptic patients. First, we evaluated the most relevant imprints on the BOLD response caused by variations of key model parameters. Second, we demonstrated that a general linear model is enough to accurately represent the four different types of NBRs. Third, we tested the ability of a machine learning classifier, built from a simulated ensemble of HRFs, to predict the mechanism underlying the BOLD signal from irritative zones. Cross-validation indicates that these four mechanisms can be classified from realistic fMRI BOLD signals. To demonstrate proof of concept, we applied our methodology to EEG-fMRI data from five epileptic patients undergoing neurosurgery, suggesting the presence of some of these mechanisms. We concluded that a proper identification and interpretation of NBR mechanisms in epilepsy can be performed by combining general linear models and biophysically inspired models.

Dataset Information

Differential electrophysiological coupling for positive and negative BOLD responses during unilateral hand movements.

Publications

Differential electrophysiological coupling for positive and negative BOLD responses during unilateral hand movements.

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