Brain-state diagnostics improve, and machine learning overcomes individual patient variability to assist in prognosis and guide rehabilitation. Specific tests reliably detect early onset of diseases that disrupt consciousness. Better computational models improve our understanding of the systems biology that contributes to conscious states.
An agreed set of international guidelines (effectively a standard scale) standardises assessment of human consciousness. Improved imaging, combined with AI pattern recognition, leads to more reliable prediction of which patients are aware, which will respond to stimulation and which will require implants to communicate from their vegetative state. Neuroscientific tools give a rudimentary ability to decode the content of dreams in sleeping humans, as well as other contents of conscious experience.
Understanding the difference between these various types of human consciousness will be a vital part of the effort to treat injury and disease, and to understand various aspects of human-rights issues associated with consciousness. Research efforts are aiming to do this, with some success in the application of diagnostic tools that can differentiate between a vegetative state and a minimally conscious state, for instance.10 Functional MRI and EEG can be used to demonstrate performance of cognitive tasks in some comatose patients who do not follow verbal commands.11 Intervention in coma patients, aiming at recovery, is becoming a realistic, if long-term, prospect.12,13 There is hope that better understanding will help detect and assess early memory loss in ageing and in Alzheimer’s disease, and guide treatment and care.14At the other end of life the need to assess consciousness “in the cradle”, in the prenatal and infant stages, is becoming an issue with medical, educational, legal and ethical implications.15
Neurosurgical research demonstrates that specific neuronal activity underlies the emergence of concepts, memories and intentions in human consciousness. Recent work involving direct recordings from the human brain has highlighted the role of specific regions of the thalamus in mediating conscious perception, showing flow of involved information from these thalamic nuclei to the prefrontal cortex.16 Further exploration here, with emerging brain-recording and stimulation tools, partnered with AI-based analysis, could help decode conscious and preconscious states.17,18 Interaction with sleeping humans can also help to explore the space between the conscious and unconscious brain.19
Such work could also help with fundamental science, such as developing theoretical understanding of consciousness by identifying areas of interest for probing the neural correlates of consciousness, and contribute to the quantification and classification of consciousness in humans.
The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:
This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.
