Journal of Neuroscience · 2011 · 184 citations · 45 references
Life SciencesNeuroscienceElectrophysiologyNeurophysiologySystems NeuroscienceBrain ImagingCerebral Cortex PhysiologyCerebral PhysiologyCortical PhysiologyElectroencephalographyFunctional NeuroimagingBlood Oxygenation Level-dependent ContrastBlood Oxygenation Level-dependent ImagingBrain Functional ImagingBrain RegionsFunctional Magnetic Resonance ImagingFunctional Magnetic Resonance Imaging CorrelatesFunctional MriLocal Field Potential Recording
The relationship between blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal and the underlying neural electrical activity in humans is a topic of intense interest to systems neuroscience. This relationship has generally been assumed to be invariant regardless of the brain region and the cognitive task being studied. We critically evaluated these assumptions by comparing the BOLD-fMRI response with local field potential (LFP) measurements during visually cued common noun and verb generation in 11 humans in whom 1210 subdural electrodes were implanted. As expected, power in the mid-gamma band (60-120 Hz) correlated positively (r(2) = 0.16, p < 10(-16)) and power in the beta band (13-30 Hz) correlated negatively (r(2) = 0.09, p < 10(-16)) with the BOLD signal change. Beta and mid-gamma band activity independently explain different components of the observed BOLD signal. Importantly, we found that the location (i.e., lobe) of the recording site modulates the relationship between the electrocorticographic (ECoG) signal and the observed fMRI response (p < 10(-16), F(21,1830) = 52.7), while the type of language task does not. Across all brain regions, ECoG activity in the gamma and beta bands explains 22% of the fMRI response, but if the lobar location is considered, 28% of the variance can be explained. Further evaluation of this relationship at the level of individual gyri provides additional evidence of differences in the BOLD-LFP relationship by cortical locus. This spatial variability in the relationship between the fMRI signal and neural activity carries implications for modeling of the hemodynamic response function, an essential step for interregional fMRI comparisons.
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