Human consciousness is supported by dynamic complex patterns of brain signal coordination.

Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern's implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain's ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

Disentangling conscious from unconscious cognitive processing with event-related EEG potentials.

By looking for properties of consciousness, cognitive neuroscience studies have dramatically enlarged the scope of unconscious cognitive processing. This emerging knowledge inspired the development of new approaches allowing clinicians to probe and disentangle conscious from unconscious cognitive processes in non-communicating brain-injured patients both in terms of behaviour and brain activity. This information is extremely valuable in order to improve diagnosis and prognosis in such patients both at acute and chronic settings. Reciprocally, the growing observations coming from such patients suffering from disorders of consciousness provide valuable constraints to theoretical models of consciousness. In this review we chose to illustrate these recent developments by focusing on brain signals recorded with EEG at bedside in response to auditory stimuli. More precisely, we present the respective EEG markers of unconscious and conscious processing of two classes of auditory stimuli (sounds and words). We show that in both cases, conscious access to the corresponding representation (e.g.: auditory regularity and verbal semantic content) share a similar neural signature (P3b and P600/LPC) that can be distinguished from unconscious processing occurring during an earlier stage (MMN and N400). We propose a two-stage serial model of processing and discuss how unconscious and conscious signatures can be measured at bedside providing relevant informations for both diagnosis and prognosis of consciousness recovery. These two examples emphasize how fruitful can be the bidirectional approach exploring cognition in healthy subjects and in brain-damaged patients.

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

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.

Probing consciousness with event-related potentials in the vegetative state.

OBJECTIVE: Probing consciousness in noncommunicating patients is a major medical and neuroscientific challenge. While standardized and expert behavioral assessment of patients constitutes a mandatory step, this clinical evaluation stage is often difficult and doubtful, and calls for complementary measures which may overcome its inherent limitations. Several functional brain imaging methods are currently being developed within this perspective, including fMRI and cognitive event-related potentials (ERPs). We recently designed an original rule extraction ERP test that is positive only in subjects who are conscious of the long-term regularity of auditory stimuli. METHODS: In the present work, we report the results of this test in a population of 22 patients who met clinical criteria for vegetative state. RESULTS: We identified 2 patients showing this neural signature of consciousness. Interestingly, these 2 patients showed unequivocal clinical signs of consciousness within the 3 to 4 days following ERP recording. CONCLUSIONS: Taken together, these results strengthen the relevance of bedside neurophysiological tools to improve diagnosis of consciousness in noncommunicating patients.