Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness.

A multivariate pattern classifier can decode single-trial EEG responses to auditory novelty, distinguishing local (automatic) from global (conscious) novelty detection. In 38 high-density EEG, MEG, and intracranial EEG recordings, the method overcame individual variability and multiple-comparison issues. Local responses were robust to distraction, while global responses depended on attention. Among 104 patients in vegetative state (VS), minimally conscious state (MCS), and conscious state (CS), local response decoding was significant in about 60% of recordings regardless of consciousness state. For global responses, significant decoding occurred in 14% of VS patients, 31% of MCS patients, and 52% of CS patients, indicating that global novelty decoding tracks consciousness level.

Study at a glance

Abstract

Detecting residual consciousness in unresponsive patients is a major clinical concern and a challenge for theoretical neuroscience. To tackle this issue, we recently designed a paradigm that dissociates two electro-encephalographic (EEG) responses to auditory novelty. Whereas a local change in pitch automatically elicits a mismatch negativity (MMN), a change in global sound sequence leads to a late P300b response. The latter component is thought to be present only when subjects consciously perceive the global novelty. Unfortunately, it can be difficult to detect because individual variability is high, especially in clinical recordings. Here, we show that multivariate pattern classifiers can extract subject-specific EEG patterns and predict single-trial local or global novelty responses. We first validate our method with 38 high-density EEG, MEG and intracranial EEG recordings. We empirically demonstrate that our approach circumvents the issues associated with multiple comparisons and individual variability while improving the statistics. Moreover, we confirm in control subjects that local responses are robust to distraction whereas global responses depend on attention. We then investigate 104 vegetative state (VS), minimally conscious state (MCS) and conscious state (CS) patients recorded with high-density EEG. For the local response, the proportion of significant decoding scores (M=60%) does not vary with the state of consciousness. By contrast, for the global response, only 14% of the VS patients' EEG recordings presented a significant effect, compared to 31% in MCS patients' and 52% in CS patients'. In conclusion, single-trial multivariate decoding of novelty responses provides valuable information in non-communicating patients and paves the way towards real-time monitoring of the state of consciousness.