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BOLD matches neuronal activity at the mm scale: A combined 7 T fMRI and ECoG study in human sensorimotor cortex.

Authors :
Siero, Jeroen C.W.
Hermes, Dora
Hoogduin, Hans
Luijten, Peter R.
Ramsey, Nick F.
Petridou, Natalia
Source :
NeuroImage. Nov2014, Vol. 101, p177-184. 8p.
Publication Year :
2014

Abstract

High resolution BOLD fMRI has the potential to map activation patterns of small neuronal populations at the scale of cortical columns. However, BOLD fMRI does not measure neuronal activity, but only a correlate thereof, since it measures blood dynamics. To confirm that BOLD activation maps reflect neuronal population activity patterns, a direct comparison with neuro-electrophysiological data from the same cortical patch is necessary. Here, we compare BOLD activation patterns obtained with fMRI at 7 T to electrophysiological patterns obtained with implanted high density electrocorticography (ECoG) grids in the same patch of human sensorimotor cortex, and with similar resolution (1.5 mm). We used high spatially sampled high-frequency broadband (HFB) power from ECoG, which reflects local neuronal population activity. The spatial distribution of 7 T BOLD activation matched the spatial distribution of ECoG HFB-power changes in the covered patch of sensorimotor cortex. BOLD fMRI activation foci were located within 1–3 mm of the HFB-power ECoG foci. Both methods distinguished individual finger movement activation within a 1 cm cortical patch, revealing a topographical medial to lateral layout for the little finger to index to thumb. These findings demonstrate that the BOLD signal at 7 T is strongly correlated with the underlying electrophysiology, and is capable of discriminating patterns of neuronal population activity at a millimeter scale. The results further indicate the utility of 7 T fMRI for investigation of intra-area organization of function and network dynamics. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10538119
Volume :
101
Database :
Academic Search Index
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
98359545
Full Text :
https://doi.org/10.1016/j.neuroimage.2014.07.002