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Blockade of the scalp electroencephalographic (EEG) sensorimotor rhythm (SMR) is a well-known phenomenon following attempted or executed motor functions. Such a frequency-specific power attenuation of the SMR occurs in the alpha and beta frequency bands and is spatially registered at primary somatosensory and motor cortices. Here, we hypothesized that resting-state fluctuations of the SMR in the alpha and beta frequency bands also covary with resting-state sensorimotor cortical activity, without involving task-related neural dynamics. The present study employed functional magnetic resonance imaging (fMRI) to investigate the neural regions whose activities were correlated with the simultaneously recorded SMR power fluctuations. The SMR power fluctuations were convolved with a canonical hemodynamic response function and correlated with blood-oxygen-level dependent (BOLD) signals obtained from the entire brain. Our findings show that the alpha and beta power components of the SMR correlate with activities of the pericentral area. Furthermore, brain regions with correlations between BOLD signals and the alpha-band SMR fluctuations were located posterior to those with correlations between BOLD signals and the beta-band SMR. These results are consistent with those of event-related studies of SMR modulation induced by sensory input or motor output. Our findings may help to understand the role of the sensorimotor cortex activity in contributing to the amplitude modulation of SMR during the resting state. This knowledge may be applied to the diagnosis of pathological conditions in the pericentral areas or the refinement of brain–computer interfaces using SMR in the future.
Since Berger’s first electroencephalogram (EEG) recordings from the human scalp in the late 1920s, a number of studies have led to new insights into the function and mechanisms of intrinsic oscillations underlying brain activities (
Modulations of the SMR can be segregated into two physiologically different components. The alpha frequency band is located slightly posterior to the beta (
Does SMR also show some spontaneous fluctuations during the resting state, and, if so, is the resting-state SMR fluctuation correlated with blood-oxygen-level dependent (BOLD) signal changes in the sensorimotor areas? Spatial localization of alpha and beta components of the resting-state EEG-SMR has yet to be directly confirmed, but several lines of collateral evidence have supported such correlations. For instance, studies on sensory stimulation have shown that the prestimulus amplitude of the alpha-SMR has a significant impact on sensory stimulus detection (
Here, based upon previous knowledge suggesting an association between spontaneous SMR fluctuation during the resting state and activity of the pericentral brain regions, we addressed the following hypotheses: (1) the spontaneous SMR power modulations were correlated with a surrogate marker of brain activity that covaries with resting-state sensorimotor cortical activity as measured by BOLD-fMRI in the pericentral area, and (2) the area correlated with alpha-band SMR was located posterior to the area correlated with beta-band SMR. To test such hypotheses, we employed EEG-fMRI simultaneous recording to identify the relationship between SMR modulations and whole-brain activity during the resting state.
Nineteen healthy subjects (13 men and 6 women; aged 21–25 years) participated in this study. None had any sleep, medical, or psychiatric disorders. The purpose and experimental procedure were explained to the subjects, and all subjects gave informed written consent. The study was conducted in accordance with the Declaration of Helsinki and was approved by Keio University Faculty of Science and Technology Bioethics Committee and Saiseikai Kanagawa-ken Hospital Ethics Committee.
The subjects were asked to lie still on a scanner bed in the dark for 10 min with their eyes opened and fixed on a small black cross. EEG signals were recorded with an MR-compatible amplifier (BrainAmp MR plus, Brain Products GmbH, Germany) and an EEG electrode cap (BrainCap MR, Brain Products GmbH, Germany) providing 63 EEG channels and 1 electrocardiogram (ECG) channel. Their electrodes were placed according to the modified International 10–10 system (
Functional images were acquired on a 1.5-T MR scanner (Signa Excite, GE Medical Systems, United Kingdom) and whole-brain, T2-weighted BOLD data were acquired using an echo planar image sequence (repetition time TR = 3000 ms; echo time TE = 40 ms; flip angle = 70 degrees; voxel size = 3.75 mm × 3.75 mm × 4.0 mm; 30 axial slices with no gap, 200 scans). To achieve phase synchronization clocks for digital sampling between the MRI data and the EEG system, the EEG system clock was synchronized with a SyncBox device (Brain Products GmbH, Germany) and the MRI scanner’s 10 MHz master synthesizer. The scanner also delivered each TR trigger signal that marked the onset time of every fMRI volume acquisition. These markers were used for fMRI scanning artifact correction of the EEG data.
An outline of the analyses is shown in
The analysis flow in EEG-fMRI simultaneous recording study. FFT, Fast Fourier transformation; HRF, hemodynamic responses; MNI, Montreal Neurological Institute; FWHM, full width at half maximum; GLM, General Linear Model; BOLD, blood-oxygen-level dependent; SMR, sensorimotor rhythm; CSF, cerebrospinal fluid; FWE, family-wise error.
Electroencephalogram data were processed by Brain Vision Analyzer 2.0 (Brain Products GmbH, Germany) and the MR gradient-artifacts and ballistocardiogram in the EEG signals were corrected using the average template subtraction method (
It is known that the EEG signal obtained around the pericentral area contains cognitive components, such as activity related to the “mirror neuron systems,” in addition to the sensorimotor idling activity component (
The fMRI data were pre-processed with Statistical Parametric Mapping (SPM12, Wellcome Department of Imaging Neuroscience
For the correlation analysis of BOLD signals with SMR power modulation in each frequency band, we followed a previous approach in the simultaneous EEG-fMRI study (
In the first-level analysis, we generated regression coefficient contrast images of alpha- and beta-band SMR modulations for each subject. Then, for the second-level, group data analysis, the contrast images were fed into a one-sample
A typical SMR time series of a single subject is shown in
Time course and frequency results of the EEG.
Correlation maps of the SMR modulation wave elicited from C3 in each frequency band.
Brain regions whose activity correlated with the power of the alpha-band SMR modulation.
Model | Correlation type | Brain region | Side | MNI coordinates | Cluster size | ||||
---|---|---|---|---|---|---|---|---|---|
Alpha | Negative | Triangular part of the inferior frontal gyrus | R | 50 | 38 | -6 | 5.95 | 6.30 × 10-5 | 316 |
Postcentral gyrus | L | -52 | -32 | 52 | 5.88 | 7.23 × 10-6 | 2002 | ||
R | 46 | -28 | 62 | 5.85 | 7.61 × 10-6 | 1250 | |||
Middle frontal gyrus | L | -44 | 28 | 28 | 5.57 | 1.36 × 10-5 | 430 | ||
Superior parietal lobule | R | 22 | -68 | 50 | 5.53 | 1.50 × 10-5 | 791 | ||
L | -16 | -58 | 64 | 5.25 | 2.72 × 10-5 | 642 | |||
Superior frontal gyrus | R | 26 | 2 | 62 | 5.25 | 2.73 × 10-5 | 241 | ||
Opercular part of the inferior frontal gyrus | R | 56 | 22 | 16 | 5.03 | 4.34 × 10-5 | 838 | ||
Middle occipital gyrus | L | -34 | -84 | 30 | 4.54 | 1.27 × 10-4 | 202 | ||
Brain regions whose activity correlated with the power of the SMR beta1- and beta2-bands.
Model | Correlation type | Brain region | Side | MNI coordinates | Cluster size | ||||
---|---|---|---|---|---|---|---|---|---|
Beta1 | Negative | Middle frontal gyrus | R | 38 | 20 | 30 | 6.38 | 2.61 × 10-5 | 314 |
Beta2 | Positive | Thalamus | R | 2 | -12 | 4 | 4.42 | 1.65 × 10-4 | 270 |
L | -6 | -8 | 6 | 3.71 | 8.06 × 10-4 | 270 | |||
Negative | Superior frontal gyrus | L | -10 | 24 | 58 | 6.51 | 2.00 × 10-6 | 326 | |
R | 22 | 54 | 30 | 4.72 | 8.47 × 10-5 | 202 | |||
Postcentral gyrus | L | -44 | -28 | 50 | 6.33 | 2.86 × 10-6 | 1262 | ||
R | 52 | -18 | 52 | 5.94 | 6.41 × 10-6 | 1024 | |||
Opercular part of the inferior frontal gyrus | R | 42 | 14 | 24 | 6.09 | 4.64 × 10-6 | 1758 | ||
Posterior orbital gyrus | R | 32 | 24 | -18 | 5.88 | 7.22 × 10-6 | 313 | ||
Superior temporal gyrus | L | -60 | -20 | 2 | 5.40 | 1.98 × 10-5 | 293 | ||
Lingual gyrus | L | -20 | -68 | -10 | 5.01 | 4.50 × 10-5 | 219 | ||
R | 20 | -66 | -4 | 4.68 | 9.34 × 10-5 | 376 | |||
Middle occipital gyrus | R | 32 | -82 | 32 | 4.72 | 8.52 × 10-5 | 224 | ||
Superior frontal gyrus medial part | R | 6 | 50 | 18 | 4.58 | 1.17 × 10-4 | 340 | ||
Middle temporal gyrus | R | 60 | -30 | 0 | 4.40 | 1.73 × 10-4 | 228 | ||
We further examined a spatial topography of fMRI signal correlated with both the alpha- and beta2-band SMR modulations in the left pericentral area, where the C3 electrode was located.
Spatial distributions of the correlations between BOLD signal and each SMR modulation in the pericentral area. Red areas correlated with alpha-band SMR modulation, green areas correlated with beta2-SMR modulation, and yellow areas are overlapped regions correlated with modulations of both alpha- and beta2-bands. These regions were adjusted from statistical maps to those based on the atlas of the pericentral area in SPM12.
The distributions of statistically significant voxels along the anterior–posterior axis. The black lines show the number of significant voxels correlated with alpha-band SMR modulation and the dashed lines show those correlated with beta2-band SMR modulation.
In the present study, we employed simultaneous EEG-fMRI recordings in healthy human subjects to investigate the whole-brain hemodynamic responses associated with spontaneous SMR fluctuations. We found significant correlations between BOLD signals of activities in the sensorimotor regions and modulation of EEG-SMRs in the resting state. In addition, the regions with negative correlations between BOLD signals and the alpha-band SMR were distributed posterior to those correlated with the beta-band SMR.
Two of the four frequency components, alpha- and beta2-band, showed distributions of significant correlations locally around C3 and its periphery. According to
Both the alpha- and beta2-band SMR components were correlated with BOLD signals around the bilateral pericentral areas. Previous fMRI studies also found that in the resting state, BOLD signals in the bilateral sensorimotor cortices were correlated with one another, a phenomenon referred to as the
Although the topographic map of the EEG alpha-band SMR correlation was similar to that of the beta2 correlation, it may reflect somatosensory-dominant activities of the cortex. Our fMRI results may indicate functional differences between the alpha- and beta-band components of the SMR. Although both SMR components were correlated with BOLD signals around the pericentral area, the area correlated with the alpha-band SMR was in the parietal region and that correlated with the beta-band SMR was the frontal region. Recent findings suggest that the functional role of alpha oscillations is closely related to the activity of intrinsic cortical networks, indicating that the alpha-band signal occurs in different cortical layers (
Previous studies reported the SMR to be most prominent in central scalp regions in the area of the sensorimotor cortex (
No EMG/visual monitoring was employed to rule out potential bodily movements during EEG-fMRI.
The work presented here was carried out as a collaboration among all authors. ST and JU conceived and designed the research; ST and SS performed experiments; ST analyzed data; ST, TH, and JU interpreted results of experiments; ST prepared figures and drafted the manuscript; all authors edited and revised the manuscript; all authors have read and approved the final version of the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Sayoko Ishii, Kumi Nanjo, and Sawako Ohtaki for their technical support.