Elsevier

NeuroImage

Volume 74, 1 July 2013, Pages 288-297
NeuroImage

Infraslow LFP correlates to resting-state fMRI BOLD signals

https://doi.org/10.1016/j.neuroimage.2013.02.035Get rights and content

Abstract

The slow fluctuations of the blood-oxygenation-level dependent (BOLD) signal in resting-state fMRI are widely utilized as a surrogate marker of ongoing neural activity. Spontaneous neural activity includes a broad range of frequencies, from infraslow (< 0.5 Hz) fluctuations to fast action potentials. Recent studies have demonstrated a correlative relationship between the BOLD fluctuations and power modulations of the local field potential (LFP), particularly in the gamma band. However, the relationship between the BOLD signal and the infraslow components of the LFP, which are directly comparable in frequency to the BOLD fluctuations, has not been directly investigated. Here we report a first examination of the temporal relation between the resting-state BOLD signal and infraslow LFPs using simultaneous fMRI and full-band LFP recording in rat. The spontaneous BOLD signal at the recording sites exhibited significant localized correlation with the infraslow LFP signals as well as with the slow power modulations of higher-frequency LFPs (1–100 Hz) at a delay comparable to the hemodynamic response time under anesthesia. Infraslow electrical activity has been postulated to play a role in attentional processes, and the findings reported here suggest that infraslow LFP coordination may share a mechanism with the large-scale BOLD-based networks previously implicated in task performance, providing new insight into the mechanisms contributing to the resting state fMRI signal.

Highlights

► First simultaneous fMRI and infraslow LFP recordings in rat brain ► Temporal correlation between infraslow LFP and resting state BOLD fluctuations ► Correlation localized to cortex near electrode and contralateral hemisphere. ► Relationship was present under two different anesthetics.

Introduction

Resting-state fMRI is widely employed to investigate functional connectivity and the activity of large-scale networks in the brain (Biswal et al., 1995, Fox and Raichle, 2007). The spontaneous low-frequency fluctuations (< 0.1 Hz) in the blood-oxygen-level dependent (BOLD) signal have been postulated to reflect variations in neural activity over time. Researchers investigating the neural substrate of resting-state fMRI have reported a correlational relationship between the spontaneous BOLD fluctuations and slow fluctuations of the band-limited power (BLP) of the local field potential (LFP) in the well-recognized frequency bands from delta to gamma (Magri et al., 2012, Pan et al., 2011, Shmuel and Leopold, 2008). It has been suggested that the infraslow components of electrophysiological recordings (below 0.5 Hz) also play a functional role in the coordination of large-scale networks (Birbaumer et al., 1990, He et al., 2008, Khader et al., 2008), but their relationship to the BOLD fluctuations in the resting state is largely unknown. The infraslow fluctuations have traditionally been discarded due to concerns about contamination from drift and non-neural variation, but more recently this frequency range has received increasing attention as a growing body of research demonstrates its relevance to cognitive processing (Khader et al., 2008). For example, Rosler et al. demonstrated that a larger amplitude of a slow wave pattern was linked to more specific modular resources of cognition, which seems to reflect a connection between slow wave amplitude and how strongly a particular cell assembly is activated at a given time (Rosler et al., 1997). DC-EEG studies have linked infraslow activity to fluctuations in attentional control and reaction time in both normal subjects and attention deficit/hyperactivity disorder (ADHD) patients (Helps et al., 2010, Monto et al., 2008). Infraslow fluctuations of negative shifts may represent increased cortical excitability because of widespread depolarization in the dendritic trees of cortical pyramidal neurons, thereby facilitating the processing of stimuli presented to a more easily excitable network (Elbert, 1993, Rockstroh et al., 1993).

The frequency correspondence between the infraslow electrical activity and the spontaneous BOLD signal has led several groups to postulate a direct link between the two (Drew et al., 2008, He et al., 2008). In support of a relationship between infraslow electrophysiological signals and BOLD fluctuations, He et al. compared the correlation structures of the sensorimotor network via fMRI and electrocorticography (ECoG) separately on the same group of epilepsy patients and demonstrated largely similar topography in the correlation patterns whether revealed by spontaneous slow BOLD signals or by spontaneous slow cortical potentials (He et al., 2008), suggesting the two are closely linked. However, to obtain the temporal relationship between the BOLD signal and infraslow neural activity, technically-challenging simultaneous fMRI and direct current (DC) recording experiments are essential. To date, previous simultaneous fMRI and intracortical recording were limited to conventional LFP bands (> 0.5 Hz) (Goense and Logothetis, 2008, Logothetis et al., 2001, Pan et al., 2011, Shmuel and Leopold, 2008). We have recently developed an animal model of simultaneous fMRI and electrophysiology using micro-glass Ag/AgCl electrodes implanted in the rat brain (Pan et al., 2010b, Pan et al., 2011). The slowly varying components in electrophysiology can be more faithfully recorded with chloridized silver than with other kinds of electrodes (Tallgren et al., 2005). Full-band local field potentials were recorded from the somatosensory cortex (S1FL, n = 13) and the caudate putamen (CP, n = 3) while fMRI was acquired simultaneously from the same slice. The low frequency BOLD fluctuations were compared to the simultaneously-recorded infraslow LFPs to examine spatial co-localization and the temporal relationship between the signals. To partially account for potentially confounding effects of anesthesia on the vasculature, two anesthetics with different effects on neural activity and the vasculature (isoflurane (ISO) group, n = 6 rats; dexmedetomidine (DMED) group, n = 7 rats) were compared in S1FL data.

Our results demonstrate that the spontaneous BOLD signals at the recording sites exhibited significant correlation with the infraslow LFP fluctuations as well as power modulation of traditional LFPs at a delay comparable to the hemodynamic response time in stimulation studies. Highly localized correlation was also observed in the homologous cortical area in the opposite hemisphere, demonstrating a close correlational relationship between spontaneous fluctuations in the infraslow potentials and BOLD signals and suggesting that coherent infraslow fluctuations may play an important role in functional connectivity.

Section snippets

Animal preparation and electrode implantation

All animal experiments were performed in compliance with NIH guidelines and were approved by the Emory University Institutional Animal Care and Use Committee. Sprague–Dawley rats (male, 200–300 g, n = 16, Charles River) were used in this study. All rats were anesthetized with 2% isoflurane during surgery. A fine tip electrode (~ 10 μm in diameter, borosilicate pipettes) with 1–5 MΩ was prepared with a micropipette puller (PE-2; NARISHIGE). The electrode was filled with artificial cerebrospinal fluid

Tight local coupling between infraslow LFP and BOLD signals

Robust BOLD/infraslow LFP correlations were observed in rats under both isoflurane (ISO, Fig. 1A) and dexmedetomidine (DMED, Fig. 1B) anesthesia. In both groups of rats, our data showed that the strongest correlation between infraslow LFP and BOLD occurs in voxels near the recording electrode in S1FL of the recording hemisphere (Figs. 1A and B), with contralateral S1FL also exhibiting relatively high correlation. As expected, the pattern of correlation with the BOLD signal is highly similar

Discussion

The wide disparities in time scale make it challenging to establish a direct relationship between slow BOLD fluctuations and the well-recognized faster neural oscillations in electrophysiology. These fast electrophysiological frequencies (> 0.5 Hz) cannot be captured directly by BOLD due to the low-pass filter inherent in the vasculature (Logothetis and Wandell, 2004). Most researchers have chosen to calculate band-limited power for time bins corresponding to the sampling interval between BOLD

Acknowledgments

Funding sources: NIH, 1R21NS072810-01A1 and 1R21NS057718-01.

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