Neural basis of global resting-state fMRI activity

Abstract

Functional MRI (fMRI) has uncovered widespread hemodynamic fluctuations in the brain during rest. Recent electroencephalographic work in humans and microelectrode recordings in anesthetized monkeys have shown this activity to be correlated with slow changes in neural activity. Here we report that the spontaneous fluctuations in the local field potential (LFP) measured from a single cortical site in monkeys at rest exhibit widespread, positive correlations with fMRI signals over nearly the entire cerebral cortex. This correlation was especially consistent in a band of upper gamma-range frequencies (40-80 Hz), for which the hemodynamic signal lagged the neural signal by 6-8 s. A strong, positive correlation was also observed in a band of lower frequencies (2-15 Hz), albeit with a lag closer to zero. The global pattern of correlation with spontaneous fMRI fluctuations was similar whether the LFP signal was measured in occipital, parietal, or frontal electrodes. This coupling was, however, dependent on the monkey's behavioral state, being stronger and anticipatory when the animals' eyes were closed. These results indicate that the often discarded global component of fMRI fluctuations measured during the resting state is tightly coupled with underlying neural activity.cortex | electrophysiology | local field potential | functional connectivity | monkey T he mammalian cerebral cortex is subdivided into specialized regions for various cognitive functions, such as the processing of sensory stimuli, memory, and the execution of movements. This functional specialization notwithstanding, the brain does not cease to show pronounced dynamic activity in the absence of cognitive or sensory stimulation. Significant ongoing spontaneous activity has been demonstrated using optical (1, 2), electrophysiological (3-5), and functional imaging (6, 7) techniques in several species under a variety of behavioral states. FMRI allows for visualization of large-scale, spatial patterns of such intrinsic activity, which is achieved by mapping patterns of activity covariation between brain regions. The temporal correlation between fluctuations in different regions is then often taken as a measure of "functional connectivity" between the corresponding brain areas (8-11). These fluctuations typically exhibit their highest intervoxel coherence at low temporal frequencies (<0.1 Hz) and can be observed during alertness (12, 13), sleep (14, 15), light sedation (16), and general anesthesia (17,18). Experiments are beginning to address the spatiotemporal characteristics of these spontaneous fluctuations in animal models (19)(20)(21), with initial studies in macaques suggesting a human-like pattern of functional connectivity (7,22).In humans, spontaneous activity is typically investigated in the so-called resting state, a term that is only loosely defined and which typically amounts to a subject lying in the scanner without an explicit stimulus or task. Under these conditions, analysis of spatiotemporal coherence of fMRI activity reveals several distin...

Mesoscale infraslow spontaneous membrane potential fluctuations recapitulate high-frequency activity cortical motifs

“…In agreement with these studies, advancements permitting simultaneous localized neurophysiological measurements alongside fMRI indicate that changes in low-frequency (2-15 Hz) LFP and the slow modulation of gamma frequency LFP signals are strong neurophysiological correlates of activity for both evoked-and resting-state BOLD signal fluctuations in nonhuman primates 45,47,48 . Similar correlative findings between spontaneous infraslow (o0.1 Hz) frequency activity in LFP and resting-state BOLD signal have also been observed in anaesthetized rats 38 .…”

“…Neuroimaging of spontaneous infraslow activity has been the focus of tremendous research interest, but has typically relied upon imaging modalities that indirectly reflect neuronal activity [45][46][47][48] and have thus raised questions about the underlying nature and interpretation of these data 22,36 . Innovative efforts to directly assess the neurophysiological basis of fMRI BOLD signal fluctuations have revealed much about the best electrophysiological correlates of these signals, but these approaches require specialized recording equipment and technical analysis to remove electrical artifacts and are limited in their spatial coverage.…”

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

“…[56][57][58] This is a maximum estimate because a considerable amount of the fluctuation amplitude of the BOLD signal may also be influenced by physiologic noise, motion, and electronic imperfections in the scanner. [59][60][61] Furthermore, the BOLD signal fluctuations measured in resting-state fMRI, which are on the order of o0.1 Hz, do not account for the majority of spontaneous neuronal signal variations, 62 suggesting lower than 10% variations in CMR O2 . Therefore, we believe that the energy demand for the lower frequency signaling could be less than our current energy estimate for spontaneous fluctuations in the BOLD signal.…”

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults

“…A potential reason for this is the uniquely strong relationship between global-regression rs-CVR estimates and frame-wise motion, as shown in Table 4. In addition, the extent to which the global signal truly represents vascular effects is still unclear (Scholvinck et al, 2010), warranting further assessments.…”