A new technique is developed thanks to artificial intelligence to better measure whether a patient is conscious or not

By 17/03/2021 portal-3

Se desarrolla una nueva técnica gracias a la inteligencia artificial para medir mejor si un paciente está consciente o no

A small proportion of patients regain some consciousness during medical procedures, but a new study of brain activity could prevent that potential trauma. It could also help both people in comas and scientists trying to define which parts of the brain are key to the conscious mind.

Thanks to machine learning, now It is suggested that consciousness depends on the integration between the parietal cortex, the striatum and the thalamus.

Most important brain regions

Measures of integration, not just complexity, better detect changes in consciousness. Parietal/subcortical areas contribute more than frontal areas to decoding consciousness. And the integration of parietal and subcortical areas is a hallmark of conscious states.

Fx1

All of this was what UW-Madison researchers found when they recorded electrical activity in approximately 1,000 neurons surrounding each of the 100 sites in the brain of a pair of monkeys at the Wisconsin National Primate Research Center during various states of consciousness: under drug-induced anesthesia, light sleep, resting wakefulness, and awakening from anesthesia to a waking state through electrical stimulation of a deep point in the brain.

To select features that best indicate whether the monkeys were conscious or unconscious, the researchers they used machine learning, an artificial intelligence technique, supplying its large data set to a computer.

They then told him which state of consciousness had produced each pattern of brain activity and asked which brain areas and patterns of electrical activity corresponded most strongly to consciousness. The results pointed in the opposite direction to the frontal cortex, the part of the brain that is usually monitored to safely maintain general anesthesia in human patients and the part most likely to exhibit the slow waves of activity considered typical of unconsciousness.

As explained Michelle Redinbaugh, a graduate student in Saalman's lab and co-senior author from the study, published in the magazine Cell Systems:

With data on multiple brain regions and different states of consciousness, we could bring together all of these signs traditionally associated with consciousness, including how fast or slow brain rhythms are in different areas of the brain, with more computational metrics that describe how complex the brain is. are the signals and how the signals interact in different areas.


The news

A new technique is developed thanks to artificial intelligence to better measure whether a patient is conscious or not

was originally published in

Xataka Science

by
Sergio Parra

.