Fast fMRI can detect oscillatory neural activity in humans

Abstract

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.oscillations | hemodynamics | imaging | BOLD N euronal information processing is shaped by ongoing oscillatory activity, which modulates excitability in neuronal populations and supports the coordination of large-scale brain networks (1-3). In particular, the occurrence of low-frequency dynamics (0.1-2 Hz) within specific cortical regions has been suggested as a key mechanism underlying perception, attention, and awareness (4, 5), because conscious processes typically evolve on the timescale of hundreds of milliseconds (6) and may depend on cortical dynamics in this frequency range. Localizing >0.1-Hz oscillatory dynamics in the human brain is an essential step toward understanding the mechanisms of the many high-level cognitive processes that occur on these timescales. Studies of the spatial properties of neural oscillations in human subjects have been fundamentally limited by the ill-posed inverse problem of electromagnetic recordings: It is not possible to reconstruct the neural generators of EEG and magnetoencephalography (MEG) signals unambiguously, and signals from deep subcortical structures are rarely detected. Noninvasive neuroimaging approaches that can detect >0.1-Hz oscillations with higher spatial resolution are needed to advance studies of large-...

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“…This is due to well-known limitations in fMRI temporal resolution, arising from both the relatively low sampling rate of the BOLD signal (that only permit a maximum frequency resolution in the ~0.75 Hz slow delta range; Lewis et al, 2016), as well as its vascular underpinnings rendering it an indirect measure of neural activity. Despite advances in sub-second TR acquisition protocols (Lewis et al, 2016; Smith et al, 2013) and blind deconvolution methods that aim to separate the underlying neural activation from the HRF (detailed in the next section; Havlicek, Friston, Jan, Brazdil, & Calhoun, 2011), analysis of dynamic FC would undoubtedly benefit from greater involvement of MEG and EEG. These modalities provide millisecond resolution estimates of neural activity that are not confounded by hemodynamics.…”