Synchronized delta oscillations correlate with the resting-state functional MRI signal

Abstract

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in ␣-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dosedependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the ␥ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the ␦ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain.electroencephalogram ͉ spontaneous fluctuations ͉ functional connectivity T he human brain is thought to be composed of multiple coherent neuronal networks of variable scales that support sensory, motor, and cognitive functions (1). The traditional approach to studying such networks has been to use specific tasks to probe neurobiological responses. In contrast, recent studies have demonstrated the existence of spontaneous, low-frequency (i.e., Ͻ0.1 Hz) fluctuations in the functional MRI (fMRI) signal of the resting brain that exhibit coherence patterns within specific neuronal networks in the absence of overt task performance or explicit attentional demands (2-4). Such precisely patterned spontaneous activity has been reported in both awake human and anesthetized nonhuman primates (5). Recently, ''resting-state'' fMRI has been applied to study alterations in brain networks under such pathological conditions as Alzheimer's disease (6), multiple sclerosis (7), and spatial neglect syndrome (8). These studies collectively suggest that, rather than simple physiological artifacts induced by cardiac pulsations or respiration, as was originally suspected, these widely distributed coherent low-frequency fMRI fluctuations have a direct neural basis (9, 10). However, more than a decade since they were first identified, the linkage between neuronal activity and restingstate fMRI signal remains largely unknown, underscoring the clear and critical need for well controlled animal models to investigate this phenomenon.Across various states of vigilance, the electrical activity of neuronal networks is known to oscillate at various frequencies and amplitudes, with high-frequency oscillations confined to local networks, whereas large networks are recruited during slow oscillations (11,12). Imposed tasks alter local field potent...

Dorsolateral caudate nucleus differentiates cocaine from natural reward-associated contextual cues

“…S4). Anesthesia does not seem to significantly alter brain networks revealed during the resting state (54,55), and our whole brain ANOVA analysis produced brain regions compellingly consistent with those seen in awake, behaving models of drug addiction.…”

“…MRI experiments were performed on a Bruker Biospin 9.4-T scanner (Bruker) equipped with an active-shielded gradient coil. A birdcage coil driven in linear mode was used for radio frequency excitation, and a single-turn circular surface coil (2.5 cm in diameter) was used for signal reception (55). Anatomical localization of slices was standardized using T2-weighted images (T2WI) with a rapid acquisition with relaxation enhancement (RARE) sequence.…”

Local synchronization and amplitude of the fluctuation of spontaneous brain activity in attention-deficit/hyperactivity disorder: a resting-state fMRI study

“…It seems that the neurophysiology of ALFF is more straightforward than that of ReHo. LFFs are associated with activity of the gamma band in monkeys [26] , the delta band in rats [27] , and the alpha band in humans [28,29] . High local synchronization was revealed between the local field potentials from multiple cortical electrodes with a physical distance ranging from 2.6 mm to 10.6 mm in an electrophysiological study, and such local synchronization could be modulated by stimulation [30] .…”

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

“…Part of this spectral range is accessible with EEG. Over a much longer time scale in the order of several seconds to tens of seconds, network activity presents as comodulations in the power envelop of specific spectral bands, to which neuronal oscillations contribute (Leopold et al 2003;Lu et al 2007;Nir et al 2008) and which have an fMRI correlate (Magri et al 2012). Although extensive efforts have been made to characterize these "fast" and "slow" network interactions separately, their relationship has rarely been studied and remains largely unknown.…”

“…This is achieved by combining spectral information from EEG with spatial information from fMRI based on a putative temporal coupling between the spontaneous fMRI signals and the power fluctuations of individual EEG spectral components (Goldman et al 2002;Laufs et al 2003;Leopold et al 2003;Moosmann et al 2003;Lu et al 2007;Mantini et al 2007;Goense and Logothetis 2008;Scheeringa et al 2011;Liu et al 2012;Magri et al 2012). Specifically, we developed a novel "subspace" analysis method to decompose each brain region's fMRI signal into multiple component time-series signals that were temporally correlated with distinct EEG spectral components.…”