Determination of awareness in patients with severe brain injury using EEG power spectral analysis

Abstract

Objective: To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury.

Methods: We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range).

Results: In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls.

Conclusions: EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury.

Significance: EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate.

Figure 1. Brain MRIs showing major features of structural damage in the three patient subjects (PSs)

A. PS 1: T1-weighted MRI shows diffuse atrophy. B. PS 2: T2 FLAIR MRI shows focal injuries to frontal and occipital lobes and distortion from craniectomy on right (visit 1, top), and right occipital and bifrontal injuries, and fluid collection under cranioplasty site on right (visit 2, bottom). C. PS 3: T1-weighted axial image shows bithalamic and right medial temporo-occipital lobe strokes with minimal cerebral atrophy; T2-weighted sagittal image shows loss of majority of midline pons and midbrain.

Figure 2. Overview of task paradigm and signal processing

A. Timeline of audio presentation and response period during EEG recording. Illustrated commands are those used in the motor imagery task. Only EEG from the period “Three 3 sec snippets” is used for further analysis. B. Data preprocessing steps. C. Data analysis steps.

Figure 3. Power spectral analysis of EEG in HC 1 during one run of the motor imagery task

A. Power spectra (with 95% jackknife error bars) for two Laplacian channels from Run 1 of HC 1 performing motor imagery versus rest. Frequencies with differences (TGT p ≤ 0.05 by jackknife) are noted by *s in the lower part of the graph. B. Summary for Run 1 across all channels: circles represent frequencies with differences between task and rest (TGT p ≤ 0.05 by jackknife): red-filled means more power in the task condition; blue-open means more power in the rest condition. Rectangles are drawn around contiguous groups of frequencies that span a range of greater than 2 Hz (Section 2.8). Horizontal bars on the left represent p-values of the FLD: * to right of bar of Oz implies this FLD p-value is significant after FDR (0.05) correction. Head maps on the left show locations of the channels.

Figure 4. Power spectral analysis of EEG in HC 1 for all runs of the motor imagery task

Plotting conventions as in Figure 3B.

Figure 5. Power spectral analysis of EEG in HC 2 for all runs of the motor imagery task

Plotting conventions as in Figure 3B. Arrows refer to findings discussed in Section 3.1.

Figure 6. Power spectral analysis of EEG for each HC, for all runs of the motor imagery task combined within each subject

Plotting conventions for the upper section of each panel as in Figure 3B; lower sections indicate differences in log power (task minus baseline) at selected frequencies. Headmaps rendered via EEGLAB’s “topoplot” command (http://sccn.ucsd.edu/eeglab).

Figure 7. Power spectral analysis of EEG for each HC, for all runs of the navigation imagery task combined within each subject

Plotting conventions as in Figure 6.

Figure 8. Power spectral analysis of PS 1 for the motor imagery task

each run analyzed separately (upper panels, plotted as in Figure 3B) and both runs combined (plotted as in Figure 6). Right lower panel shows example power spectra (Laplacian channels Pz and C4).

Figure 9. Power spectral analysis of PS 2 for the motor imagery task on visit 1

each run analyzed separately (upper panels, plotted as in Figure 3B) and both runs combined (plotted as in Figure 6). Right lower panel shows example power spectra (Laplacian channel Pz).

Figure 10. Power spectral analysis of PS 3 for the motor imagery task on visit 1

each run analyzed separately (plotted as in Figure 3B) and both runs combined (plotted as in Figure 6). Arrows refer to findings discussed in Section 3.2.