In a proof-of-concept experiment, a new brain–computer interface was able to identify and strengthen weak electrical signals often seen in the brains of older individuals. In the future, the team hopes that such a tool could help reverse cognitive signs of aging.
“By leveraging quantum topological insulators — materials with unique electrical properties that allow for low-power consumption and high-speed data processing — we’re pushing the boundaries of what’s possible,” wrote Dani Assi, a researcher at the Hong Kong Metropolitan University, China, in an email to Advanced Science News. “Our device doesn’t just listen to the brain; it speaks the brain’s language, mimicking the neural processes of synapses to modulate brain signals more effectively.”
In recent years, brain–computer interfaces have been developed to serve as bridges between the human brain and external devices. However, neuromodulation — the regulation of neural activity by electrical, chemical, genetic, light, or other stimuli — faces numerous challenges and ethical concerns.
One technological hurdle that still needs addressing, according to Assi, is the lack of harmony between biological and artificial neural connections, which are necessary for quick processing and low latency response times.
Mimicking synapses for better brain–computer interfaces
To solve this, Assi and his team crafted a new device using a semiconductor material called bismuth selenide telluride designed to mimic natural brain connections called synapses — junctions where neurons meet.
“In terms of its architecture, our device is inspired by the intricate workings of biological synapses, aiming to closely emulate their function and efficiency,” said Assi. “This is achieved through the configuration of its components, where a silver top electrode emulates the role of the presynaptic neuron, and a fluorine-doped tin oxide coated glass bottom electrode represents the postsynaptic neuron.”
The bismuth selenide telluride layer is sandwiched between the two synapse-like sections. They chose the material as it was suitable for a neuroelectronic setup with low power consumption and high switching speed.
“Our device is equipped to detect […] weakened signals, interpret them, and then modulate them back to their healthy, normal levels, offering a promising approach to potentially reverse cognitive impairments that come with aging,” said Assi. He compared it to a radio signal that needs to be tuned and enhanced to hear the music loud and clear.
Proof-of-concept tests show promise, but we’re not there yet
After creating the device, the researchers conducted a set of electrical experiments to characterize its processing power. Once these tests were complete, they moved on to neuromodulation experiments to determine whether the device could indeed effectively influence neural activity.
To do this, they tested the device’s ability to neuromodulate aging-related changes in event-related potentials (ERP). An ERP is a mark of voltage change in the brain in response to a specific stimulus, be it a sensory, cognitive, or motor event.
These signals are isolated from an electroencephalogram (EEG) test, which is a composite measure of all electrical activity in the brain at a given time. Altered ERPs are a strong indication of cognitive difficulties following aging in the brain.
The researchers used EEG data from free and publicly available database OpenNeuro for an auditory cue reaction time task, wherein the reaction time of an individual to a particular auditory stimulus is recorded.
The team extracted ERPs from the database for 39 people between the ages of 55 and 75 years, and used an ERP from a healthy young individual as a reference point. These ERPs were then fed into the neuromodulator device and regulated to more closely to resemble the reference ERP.
As the device was not tested in humans or tissue samples, its safety and efficacy in living participants and larger sample populations needs to be validated. Moreover, several ethical issues and controversies surround the use of brain–computer interfaces, including the manipulation of agency, privacy concerns around neural data, and the long-term effect of these devices.
“Looking ahead, our device holds the potential for widespread application in therapeutic and rehabilitation settings, targeting conditions that impair cognitive functions and offering a new avenue for recovery and enhancement,” added Assi.
Reference: Dani S. Assi, et al., Topological Quantum Switching enabled Neuroelectronic Synaptic Modulators for Brain Computer Interface, Advanced Materials (2024). DOI: https://doi.org/10.1002/adma.202306254
Feature image credit: Mike Uderevsky on Unsplash
