Brain-computer interfaces or BCIs hold immense potential for individuals with a wide range of neurological conditions, but the road to implementation is long and nuanced for both the invasive and noninvasive versions of the technology.
Scientists have now successfully integrated a novel focused ultrasound stimulation to realize bidirectional BCI that both encodes and decodes brain waves using machine learning in a study with 25 human subjects. This work opens up a new avenue to significantly enhance not only the signal quality, but also, overall nonivasive BCI performance by stimulating targeted neural circuits.
"This paper reports a breakthrough in noninvasive BCIs by integrating a novel focused ultrasound stimulation to realize bidirectional BCI functionality," explained Bin He, professor of biomedical engineering at Carnegie Mellon University."Using a communication prosthetic, 25 human subjects spelled out phrases like"Carnegie Mellon" using a BCI speller.
Following this discovery, the He lab is further investigating the merits and applications of focused ultrasound neuromodulation to the brain, beyond the visual system, to enhance noninvasive BCIs. They also aim to develop more compact-focused ultrasound neuromodulation device for better integration with EEG-based BCIs, and to integrate AI to continue to enhance the overall system performance.
Nervous System Psychology Research Brain-Computer Interfaces Neuroscience Learning Disorders Ultrasound Medical Technology Detectors
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