by Béatrice St-Cyr-Leroux, University of Montreal

Workshop 3 in the sound design process of Resonance, where a therapeutic clown duo (Dr. Fifi and Dr. Tcheksa) interacted with the real-time sonified EEG of an individual in a simulated medical environment. Credit: Stefanie Blain-Moraes. Photo by Diane Lynn Weidner. From Leonardo (2024). DOI: 10.1162/leon_a_02547

Whether due to a head injury or a disorder such as a brain tumor, a growing number of people find themselves immersed in altered states of consciousness, being barely able to communicate or completely unresponsive to outside stimuli.

Evaluating the level of consciousness of persons in comas or in unresponsive states of wakefulness remains a daunting challenge but one that is essential for care-related decision-making, doctors believe.

Now a Montreal-based research team has designed a new clinical protocol called Resonance to detect and increase expressions of consciousness in minimally communicative patients. It involves three steps: electroencephalograms (EEGs), sound generators and "therapy clowns."

• First, the clowns try to elicit reactions from the patient, using multi-sensory improvisation.

• Next, an electroencephalogram measures the electrical signals generated by the patient's brain.

• Finally, these data, which provide information on the patient's level of consciousness, are extracted and sent to a sound generator.

The work is published in the journal Leonardo.

Seven EEG characteristics—that is, seven ways in which neurons communicate with each other—are associated with different musical instruments and roles. For instance, fronto-parietal functional connectivity is represented by woodwind sounds, which become louder or softer as the signal increases or decreases. The relationship between alpha and theta waves produces piano and harp sounds, while that between beta and alpha waves creates synthesizer sounds.

Doctors can either focus on a specific aspect of the "music" to determine the status of a given EEG characteristic in a patient or assess the general state of their brain by listening to the soundscape that's produced.

'A very human approach'

"It's a very human, even artistic approach, in which the brain's electrical activity is converted into sound; the rhythm of the music changes with fluctuations in the state of consciousness," said Dr. Francis Bernard, an Université de Montréal medical and neurointensivist at Hôpital du Sacré-Cœur-de-Montréal who worked on the Resonance project.

Its soundscape is designed to improve interactions between minimally communicative individuals and their caregivers in order to optimize their care, said Bernard, who specializes in neurological intensive care.

"Even when patients are in what used to be known as a vegetative state, even when there may be no signs of wakefulness, there are occasional flickers of consciousness. By quantifying those moments, we can guide our approach to their care and target patients who have recovery potential or are relevant subjects for clinical studies.

"While these data may be helpful to families grappling with future decisions such as withdrawing care, they can also provide information on when their loved ones are experiencing wakeful moments. Families often say, 'I know he's more present,' and thanks to this technique, their perception can be made real.

"As the person's level of consciousness becomes audible, families know that's the best time to interact with them. The brain only lights up for a few minutes each day, so that contact becomes more meaningful."

So far, the technique has only been tested on two non-verbal patients with severe brain damage. Further clinical research should be conducted to verify the technique's efficacy in the patients' recovery process, Bernard said. "The potential is enormous. It's an innovative way to make care more democratic and more human, particularly since the procedure can be carried out at home."

More information: Stefanie Blain-Moraes et al, Resonance: A Brain-Computer Interface Assemblage of EEG, Sound, and Therapeutic Clowns for the Detection of Consciousness, Leonardo (2024). DOI: 10.1162/leon_a_02547

Provided by University of Montreal