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.

Cerebral mechanisms of general anesthesia.

How does general anesthesia (GA) work? Anesthetics are pharmacological agents that target specific central nervous system receptors. Once they bind to their brain receptors, anesthetics modulate remote brain areas and end up interfering with global neuronal networks, leading to a controlled and reversible loss of consciousness. This remarkable manipulation of consciousness allows millions of people every year to undergo surgery safely most of the time. However, despite all the progress that has been made, we still lack a clear and comprehensive insight into the specific neurophysiological mechanisms of GA, from the molecular level to the global brain propagation. During the last decade, the exponential progress in neuroscience and neuro-imaging led to a significant step in the understanding of the neural correlates of consciousness, with direct consequences for clinical anesthesia. Far from shutting down all brain activity, anesthetics lead to a shift in the brain state to a distinct, highly specific and complex state, which is being increasingly characterized by modern neuro-imaging techniques. There are several clinical consequences and challenges that are arising from the current efforts to dissect GA mechanisms: the improvement of anesthetic depth monitoring, the characterization and avoidance of intra-operative awareness and post-anesthesia cognitive disorders, and the development of future generations of anesthetics.

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.

Language or music, mother or Mozart? Structural and environmental influences on infants' language networks.

Understanding how language emerged in our species calls for a detailed investigation of the initial specialization of the human brain for speech processing. Our earlier research demonstrated that an adult-like left-lateralized network of perisylvian areas is already active when infants listen to sentences in their native language, but did not address the issue of the specialization of this network for speech processing. Here we used fMRI to study the organization of brain activity in two-month-old infants when listening to speech or to music. We also explored how infants react to their mother's voice relative to an unknown voice. The results indicate that the well-known structural asymmetry already present in the infants' posterior temporal areas has a functional counterpart: there is a left-hemisphere advantage for speech relative to music at the level of the planum temporale. The posterior temporal regions are thus differently sensitive to the auditory environment very early on, channelling speech inputs preferentially to the left side. Furthermore, when listening to the mother's voice, activation was modulated in several areas, including areas involved in emotional processing (amygdala, orbito-frontal cortex), but also, crucially, a large extent of the left posterior temporal lobe, suggesting that the mother's voice plays a special role in the early shaping of posterior language areas. Both results underscore the joint contributions of genetic constraints and environmental inputs in the fast emergence of an efficient cortical network for language processing in humans.