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Abstract
Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire.
Highlights
The observation that spontaneous fluctuations in gamma range activity correlates with rsfMRI signals in non-human primates is consistent with studies observing a tight coupling between local BOLD activation and gamma band activity recorded from the same brain area in humans
Keller et al (2013) report that this similarity extends to anti-correlations observed between regions, the BOLD-ECoG correspondence was substantially weaker for interregional anti-correlations. While these findings provide support for the identification of overlapping resting-state functional networks with electrophysiology and fMRI techniques, it is important to directly confirm that regions showing putative connectivity do share functional responses under specific task conditions
Despite these differences, growing evidence suggests that changes in high frequency activity >40 Hz recorded from the human cortex has a broadband spectral representation, and the different subsampling of this frequency range will approximately track the same temporal process (Miller et al, 2014b)
Summary
The observation that spontaneous fluctuations in gamma range activity correlates with rsfMRI signals in non-human primates is consistent with studies observing a tight coupling between local BOLD activation and gamma band activity recorded from the same brain area in humans. Keller et al (2013) studied the spatial correlations observed with resting ECoG recordings from the lateral cortical surface (covering frontal, parietal, and temporal lobes) for fast (1– 10 Hz) or slow (0.1–1 Hz) modulations of high gamma-range activity (50–150 Hz).
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