An international study involving physicists from Monash University confirmed a new approach to measure the consciousness, potentially changing our understanding of complex neurological problems.
The study published last June 6 in Physical Review Research describes how the tools of physics and complexity theory were used to determine the level of consciousness in fruit flies.
The study’s author, Dr. Kavan Modi, from the School of Physics and Astronomy at Monash University, said:
This is a major problem in neuroscience, where it is crucial to differentiate between vegetative patients who do not respond and those who suffer from a condition in which a patient is aware, but cannot move or communicate verbally due to complete paralysis of almost all muscles volunteers from the body.
The research team, which includes Dr. Modi, PhD candidate Roberto Muñoz, also from the School of Physics and Astronomy, and Monash’s associate professor of psychology, Nao Tsuchiya, found a way to measure the level of conscious flies’ arousal of the fruit using complex signals produced by the brain.
Dr. Modi said:
Our technique allows us to distinguish between anesthetized and non-anesthetized flies, calculating the complexity of the signal time.
The study is significant because it highlights an objective way to measure conscious arousal, based on well-established ideas from complexity theory.
It is potentially applicable to humans – and reflects a growing interest in new theories of consciousness that are experimentally testable.
The research team studied the brain signals produced by 13 fruit flies when they were awake and anesthetized. The scientists then analyzed the signals to see how complex they were.
Modi also reported:
We found that statistical complexity is greater when a fly is awake than when the same fly is anesthetized.
This is important because it suggests a reliable way to determine the level of conscious arousal by touching a small region of the brain, rather than many parts of the brain.
This also suggests that there is a clear marker of conscious arousal that does not depend on specific external stimuli.
The researchers concluded that applying similar analysis to other data sets, in particular human EEG data, could lead to new discoveries about the relationship between consciousness and complexity.
