Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm can provide a more accurate, quantitative assessment of children with CMD (Kim et al., 2022). This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC.
Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set.
Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS – p < 0.001; MCS v UWS – p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed).
Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC.