Mechanisms of Loss, Recovery and Disorders of Consciousness

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PROJECT SUMMARY The long-term objective of this proposal is to understand cortical mechanisms underlying loss, recovery, and disorders of consciousness. We have previously characterized neural activity associated with different stages of general anesthesia and sleep. Each of these stages is composed of distinct states of arousal and awareness, such as fluctuations between dreaming and unconsciousness. Finding neural underpinnings of these processes is necessary for understanding the neural basis of consciousness. This proposal takes advantage of the unique opportunity to directly record from the human brain in neurosurgical epilepsy patients. We will use intracranial electroencephalography (iEEG) to identify signatures of unconsciousness and distinguish it from three different states of consciousness: waking consciousness, drowsiness, and dreaming. The scientific premise of this project is that the biomarkers of clinically relevant changes in arousal and awareness share common features, generalizing beyond specific conditions that cause them. Our work to date has identified putative biomarkers that show promise for distinguishing states of arousal and awareness. These biomarkers include region-specific changes in cortical responses to unexpected sounds and speech, and in patterns of cortical connectivity. Using innovative computational approaches applied to data obtained using electrical stimulation and recording of ongoing brain activity at rest, we will track rapid transitions in cortical network configurations. Characterizing these rapid transitions will enable us to identify clinically relevant changes in arousal and awareness. Our multimodal approach combines high resolution iEEG with computational modeling, electrical stimulation tract tracing, conventional scalp-recorded EEG, and magnetic resonance imaging in overlapping sets of human subjects. We will find reliable biomarkers that can identify distinct states of consciousness that occur during induction of and emergence from general anesthesia (Specific Aim 1) and different stages of sleep (Specific Aim 2). We will then leverage these biomarkers to understand mechanisms of delirium, which can occur in neurosurgical patients during recovery from surgery and following seizures (Specific Aim 3). Identifying biomarkers of consciousness has broad clinical relevance to development of novel algorithms for monitoring depth of anesthesia. Knowledge gained from this project will contribute to improved diagnosis, management and prognosis of pathologic states of consciousness including central sleep disorders, delirium, vegetative or minimally conscious states, and coma.