Consciousness research across healthy vigilance states and disorders of consciousness

The project has a bold ambition. It aims at investigating information processing across healthy and pathological consciousness states. While the first will be represented by the natural alteration between wakefulness and sleep in healthy, the latter will be represented by patients suffering from a Disorder of Consciousness (DOC, i.e., vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS)). A further focus will lie on the detailed evaluation of circadian rhythmicity and sleep in DOC. The reason for our quest is twofold. First, patients with altered states of consciousness continue to represent a major problem in terms of clinical assessment, treatment and daily management. Progress in coma science should eventually improve our ability to disentangle diagnostic and prognostic differences on the basis of underlying mechanisms and better guide therapeutic options in this challenging patient population. Second, data of that kind will provide further information about human consciousness and its neuronal foundation, probably one of the most exciting and unsolved mysteries today. The exploration of information processing across different consciousness states represents a unique lesional approach to the scientific study of consciousness and adds to the worldwide effort to identify the "neural correlates of consciousness". New scientific insights in this field will have major ethical, social and legal implications. The bedside clinical evaluation of consciousness in non-communicative patients is inherently difficult but remains the golden standard. Proposed examinations (electroencephalography [EEG], functional connectivity and polysomnography [PSG] during sleep) seek to herald superior diagnostic and possibly prognostic information for these patients. In the first place, auditory stimuli will be applied during healthy vigilance states (i.e.: waking, NREM N2, NREM N3, and REM sleep) as well as in DOC patients given earlier circadian assessment (temperature, melatonin, actigraphy, EEG). In addition, DOC patients will be assessed after habitual light conditions as well as after bright light stimulation which is geared to further enhance arousal and maximize EEG responses to the auditory stimuli and to assess the potential interventional benefit of bright light exposure on arousal and cognitive processing. Signal complexity (e.g. permutation entropy) and functional connectivity (e.g. transfer entropy, coherence, phase locking) measurements during resting states and the assessment of circadian rhythmicity as quantified by long-term PSG, actigraphy, videography as well as saliva melatonin and temperature will additionally return information about patients diagnostic state and presumably later prognosis. Furthermore, we believe that, if proven efficient, identifying arousal windows as well as stimulating by bright light exposure may represent a way to promote arousal and counteract misdiagnosis in patients during the course of recovery. In conclusion, the increasing use and refinement of EEG/PSG will improve our clinical characterization of VS/UWS and MCS patients, not only to potentially redefine their diagnosis and prognosis, but also to better differentiate patients in terms of treatment and end-of-life decisions. "Consciousness is the guarantor of all we hold to be human and precious" wrote Gerald Edelman. We hope our research will ultimately improve our care for brain damaged patients suffering from DOC and shed some light on the understanding of us as conscious human beings.

In our Y777 START grant "Consciousness research across healthy vigilance states and disorders of consciousness" we were interested to take a closer look at information processing across various states of awareness. More specifically, we wanted to focus on natural variation of awareness across wake to sleep, as well as on pathological variations such as in "Disorders of consciousness" (DOC; here, post-comatose states like unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)). For our first research aim, we presented auditory stimuli using in-ear headphones during wakefulness, light, deep, and REM sleep as well as in different DOC states. Specifically, we utilized "own name" tasks with salient and/or emotional stimuli that is the auditory presentation of nicknames spoken by a familiar voice such as a close relative or partner (fSON) or these names spoken in neutral vs. angry prosody (eSON). We published 8 papers on that topic. Our main findings were that the brain is still processing information to an extraordinary degree in full unconsciousness. Our findings suggest that emotional prosody and self-relevance draws more attentional resources and that an unfamiliar voice during the night is processed preferentially (with associated micro-arousals), probably as an evolutionary meaningful response to potentially dangerous stimuli in the environment. Self-relevant familiar voice stimuli as well as angry prosody also seemed to be more strongly processed by otherwise uncommunicative (post-comatose) patients with disorders of consciousness, which point to the residual cognitive capabilities in these patients and the need to use more complex and meaningful stimuli when working with such severely brain-injured patients. Another research aim was to better understand circadian rhythmicity and specifically in which way circadian rhythms are altered in DOC states and can be changed or re-entrained using bright light stimulation. Here, we published 9 papers in the course of the START grant. Interestingly we found that with wrist worn actigraphy (if carefully corrected for nursing activities) and even more so by using melatonin sampling from urine and/or continuous temperature measurements on the skin we can reliably evaluate circadian rhythms in these patients. Most excitingly, we found that the patients' temperature rhythms were closer to a natural 24h cycle if patients were stimulated for a week with artificial "dynamic daylight" (DDL) similar to natural illumination. Furthermore, the patients' rhythms were more pronounced, more stable, and less variable in that DDL condition and the patients tended to be more arousable. In a final aim we were interested in "spontaneous brain activity" and whether complex machine learning techniques can be used to classify complex sleep patterns in DOC patients as well as newborn babies. Interestingly, we could and now have AI techniques that can be applied to future datasets of that kind.