Integration of Simultaneous Resting-State Electroencephalography, Functional Magnetic Resonance Imaging, and Eye-Tracker Methods to Determine and Verify Electroencephalography Vigilance Measure

Abstract

Background/Introduction: Concurrent electroencephalography and resting-state functional magnetic resonance imaging (rsfMRI) have been widely used for studying the (presumably) awake and alert human brain with high temporal/spatial resolution. Although rsfMRI scans are typically collected while individuals are instructed to focus their eyes on a fixated cross, objective and verified experimental measures to quantify degree of vigilance are not readily available. Electroencephalography (EEG) is the modality extensively used for estimating vigilance, especially during eyes-closed resting state. However, pupil size measured using an eye-tracker device could provide an indirect index of vigilance. Methods: Three 12-min resting scans (eyes open, fixating on the cross) were collected from 10 healthy control participants. We simultaneously collected EEG, fMRI, physiological, and eye-tracker data and investigated the correlation between EEG features, pupil size, and heart rate. Furthermore, we used pupil size and EEG features as regressors to find their correlations with blood-oxygen-level-dependent fMRI measures. Results: EEG frontal and occipital beta power (FOBP) correlates with pupil size changes, an indirect index for locus coeruleus activity implicated in vigilance regulation (r = 0.306, p < 0.001). Moreover, FOBP also correlated with heart rate (r = 0.255, p < 0.001), as well as several brain regions in the anticorrelated network, including the bilateral insula and inferior parietal lobule. Discussion: In this study, we investigated whether simultaneous EEG-fMRI combined with eye-tracker measurements can be used to determine EEG signal feature associated with vigilance measures during eyes-open rsfMRI. Our results support the conclusion that FOBP is an objective measure of vigilance in healthy human subjects. Impact statement We revealed an association between electroencephalography frontal and occipital beta power (FOBP) and pupil size changes during an eyes-open resting state, which supports the conclusion that FOBP could serve as an objective measure of vigilance in healthy human subjects. The results were validated by using simultaneously recorded heart rate and functional magnetic resonance imaging (fMRI). Interestingly, independently verified heart rate changes can also provide an easy-to-determine measure of vigilance during resting-state fMRI. These findings have important implications for an analysis and interpretation of dynamic resting-state fMRI connectivity studies in health and disease.

Keywords: EEG; eye tracker; heart rate; pupillometry; resting-state fMRI; vigilance.

FIG. 1.

The data analysis flowchart. Each of the modalities collected in this study required its own preprocessing steps to remove noise and artifacts and to recover missing data. After preprocessing EEG data, three features were extracted from the channels F3, F4, Fz, O1, O2, and Oz EEG data as follows: (1) power spectral density in the alpha band, (2) power spectral density in the beta band, and (3) alpha power ratio. The associations between these features and pupil size were investigated, and the feature with the highest association was selected for inclusion into further analysis. Next, the associations between that feature and the BOLD signal, as well as heart rate, were investigated. The pupil size was used as a regressor to evaluate the relationship with the BOLD signal. We also investigated the association between those three EEG features extracted from all 31 channels and pupil size and heart rate. BOLD, blood-oxygen-level-dependent; EEG, electroencephalography. Color images are available online.

FIG. 2.

Association between EEG features and pupil size. The correlation between EEG features from frontal (F3, F4, Fz) and occipital (O1, O2, Oz) channels, that is, (A) power spectral density in the alpha band, (B) power spectral density in the beta band (FOBP), and (C) alpha power ratio and pupil size are shown for each run and each subject. The runs with missing data are left empty. The asterisks show significant levels of correlation (corrected for multiple comparisons). FOBP, frontal and occipital beta power. Color images are available online.

FIG. 3.

The raincloud plots comparing the three sets of correlations between pupil size and EEG features. The top figure shows the raincloud plot for the r-to-z transformed correlation between pupil size and EEG features using six EEG channels (the runs were average for each subject for this analysis). The bottom plot shows the same analysis using all 31 EEG channels. Color images are available online.

FIG. 4.

Power spectral density in FOBP correlation map. The FOBP was used as a regressor in fMRI GLM analysis. The figure shows the cluster survived with sampling at uncorrected p < 0.005 and at cluster-size thresholded with AFNI's 3dClustSim using an improved spatial ACF, with a minimum cluster size of 146. ACF, autocorrelation function; AFNI, Analysis of Functional NeuroImages; fMRI, functional magnetic resonance imaging; GLM, general linear model. Color images are available online.

FIG. 5.

Association between FOBP and heart rate. The correlations between FOBP and heart rate are shown for each run and each subject. The runs with missing data are left empty. The asterisks show significant levels of the correlation. Color images are available online.

FIG. 6.

Pupil size correlation map. Pupil size was used as a regressor in fMRI GLM analysis. The figure shows the clusters survived with sampling at uncorrected p < 0.005 and at cluster-size thresholded with AFNI's 3dClustSim using an improved spatial ACF, with a minimum cluster size of 148. Color images are available online.