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Abstract:
We developed a novel method to visualize neural networks of endogenous activity that contribute to the variability observed in electrophysiological and functional imaging experiments. We compared activity recorded from a single electrode in the visual cortex of anesthetized monkeys with the time course of simultaneously recorded fMRI measurements. The electrophysiological signal we used was the band limited power (BLP) signal of the local field potential (LFP), which we have previously shown to exhibit slow and highly coherent fluctuations over large cortical distances. Whole-brain EPI images were collected in a 4.7 T scanner, while electrical activity was monitored with a single intracortical electrode. The maxima of cross-covariation between the BLP at that electrode and blood oxygen level-dependent (BOLD) signals for each voxel (1x1x2mm) in the imaged volume were used to generate maps of brain regions that were functionally linked with the spontaneous fluctuations on the electrode. We found that electrical activity at a single site was highly correlated with voxels throughout the brain. While covariation magnitude was greatest near the electrode tip, it remained significant even in distant brain regions, with cortical and subcortical sites showing different covariation patterns. Albeit preliminary, these results suggest that the electrophysiologically measured spontaneous activity in the visual cortex may result from large-scale fluctuations in global brain networks.
