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Brain implant translates thoughts into words

14.11.2023

Scientists from Duke University have developed an innovative brain implant that can translate thoughts into words and enable communication based on brain activity. This device is aimed at helping people who suffer from language disorders or who are unable to communicate verbally for various reasons. The first experiments showed the promise of this area of research.

Experiments to convert brain activity into text and voice communication, carried out by scanning patients' brain signals, now make it possible to transmit "thoughts" into words at speeds of up to 78 words per minute. This is comparable to listening to an audiobook at half the speed, according to the study authors. Typically, a person speaks up to 160 words per minute, which makes communication lively and natural. However, for people with speech disorders, more accurate sensors of brain activity are needed.

A team of scientists from Duke University, in collaboration with the university's biomedical engineering laboratory, created a brain activity sensor with 256 sensors on a piece of plastic the size of a postage stamp. This new sensor is capable of recording signals from individual neurons with high accuracy.

Scientists did not plan to read minds directly. However, by using complex signals from the muscles of the tongue apparatus, such as the tongue, larynx and facial muscles, they were able to accurately determine the unspoken opinions of patients (the tongue apparatus is controlled by up to 100 muscles, the signals from which must be monitored). In this way, a phrase spoken mentally could be transmitted into muscle signals, and from this data read from the brain, the computer could reproduce whatever the patient intended to say. For patients with a speech disorder, thoughts could remain in the cerebral cortex, but thanks to the sensor they were able to be spoken by a computer.

An experiment with four patients showed that the average accuracy of recognizing thoughts into words was 40%, and the maximum was 84%. The recognition algorithm was learned using the “listen and repeat” method. The patient uttered short, awkward combinations of letters, in which the algorithm learned to recognize brain activity in various combinations of sounds.

Despite the relatively low percentage of sound recognition, the team of scientists says the experiment was successful. The algorithm learned for only 90 seconds during a 15-minute test. Exactly this amount of time was allocated to the experimenters with each patient. This happened during planned brain surgeries on patients. At the end of the operation, the neurosurgeons gave the scientists 15 minutes to work with the patients on their program. Without access to the open brain, on a specific part of the cortex of which the sensor was installed, this study would have been impossible to conduct.

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