Format

Send to

Choose Destination
See comment in PubMed Commons below
Hum Brain Mapp. 2008 Jan;29(1):97-106.

A novel method for integrating MEG and BOLD fMRI signals with the linear convolution model in human primary somatosensory cortex.

Author information

1
Department of Medical Biophysics, University of Toronto, Ontario, Canada. nangini@sten.sunnybrook.utoronto.ca

Abstract

Characterizing the neurovascular coupling between hemodynamic signals and their neural origins is crucial to functional neuroimaging research, even more so as new methods become available for integrating results from different functional neuroimaging modalities. We present a novel method to relate magnetoencephalography (MEG) and BOLD fMRI data from primary somatosensory cortex within the context of the linear convolution model. This model, which relates neural activity to BOLD signal change, has been widely used to predict BOLD signals but typically lacks experimentally derived measurements of neural activity. In this study, an fMRI experiment is performed using variable-duration (< or =1 s) vibrotactile stimuli applied at 22 Hz, analogous to a previously published MEG study (Nangini et al., [2006]: Neuroimage 33:252-262), testing whether MEG source waveforms from the previous study can inform the convolution model and improve BOLD signal estimates across all stimulus durations. The typical formulation of the convolution model in which the input is given by the stimulus profile is referred to as Model 1. Model 2 is based on an energy argument relating metabolic demand to the postsynaptic currents largely responsible for the MEG current dipoles, and uses the energy density of the estimated MEG source waveforms as input to the convolution model. It is shown that Model 2 improves the BOLD signal estimates compared to Model 1 under the experimental conditions implemented, suggesting that MEG energy density can be a useful index of hemodynamic activity.

PMID:
17290370
PMCID:
PMC4896808
DOI:
10.1002/hbm.20361
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Wiley Icon for PubMed Central
    Loading ...
    Support Center