Not just mind reading: improving the stability and scalability of brain-machine interfaces
Not just mind reading: improving the stability and scalability of brain-machine interfaces lead image
Brain-machine interfaces (BMIs) enable communication between the brain and electronic devices, but current BMIs have mechanical and geometrical mismatches with brain tissue, making them less accurate and stable than needed for medical applications. Lee et al. investigate the current state of BMI research from the lens of various science and engineering fields.
The review targets any researcher with an interest in BMI, focusing on the fundamentals and limitations of BMIs and how research on flexible and smart electronics can improve current devices.
“Flexible electronics provide us with an opportunity to stably interface in the long-term with the brain with single-neuron and millisecond resolution,” author Ariel Lee said. “Smart electronics can allow closed-loop feedback using multimodal recording and stimulation of neurons, wireless and low power operations, and on-chip smart processing of neural signals.”
Recent studies showed flexible, tissue-like electronics can stably record single-neuron signals in mice for their entire lifespans.
Some groups are working on integrating smart electronics with brains using neuromorphic computing and machine learning algorithms. Smart electronics show potential for BMIs because they can make real-time decisions and process a high number of neural recording data on-chip.
The team hopes future research can improve BMI so they can seamlessly interface with the brain for decades and be able to record and interpret signals from many neurons simultaneously on the chip. Ideally, this processing should consume little power.
“It would be a very promising direction if we could process the high-volume neural data fully on-chip in real time,” author Wang said.
Source: “Flexible and smart electronics for single-cell resolved brain-machine interfaces,” by Ariel J. Lee, Wenbo Wang, and Jia Liu, Applied Physics Reviews (2023). The article can be accessed at https://doi.org/10.1063/5.0115879 .
This paper is part of the Flexible and Smart Electronics Collection, learn more here .
