Mindtrix Announces World's First Functional Validation of Complex Shape and Multi-Color Visual Reconstruction via Implanted Brain-Computer Interface

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(Source: NetEase Technology Report)

On November 21, at the Beijing "AI + Brain-Computer" Industry Innovation Promotion Conference, Mindtrix officially announced the world's first achievement in dynamically parsing complex graphics and multiple colors, along with functional interaction validation. This research, relying on clinical epilepsy diagnosis and treatment surgeries, was conducted on human patients through high-throughput intracranial electroencephalogram recording and closed-loop electrical stimulation of the occipital visual cortex.

According to the introduction, the core technology of Mindtrix lies in its "bidirectional closed-loop" design. The system is not only capable of "reading" brain signals but also optimizing stimulation parameters in real time through a "brain-machine co-learning" framework, adapting synergistically with the patient’s brain to significantly enhance the stability of visual perception. Experimental data shows that the consistency of phosphenes generated reaches 95%, with a size variation coefficient of less than 15%.

It is reported that currently, this technology is inInnovative HealthcareThe device is currently in the investigator-initiated trial (IIT) phase and is planned to expand the trial scope by 2025, with the goal of entering the registration clinical trial by 2028 and launching the first product before 2030. In the future, the team will further enhance resolution by increasing electrode density and integrating AI algorithms, ultimately achieving functions that approximate natural vision, such as facial recognition and real-time video processing.

Dr. Liu Bing, CEO and founder of Mindtrix, stated: "The leap from ‘light spots’ to ‘patterns’ and ‘colors’ represents a qualitative breakthrough in vision restoration technology. We have proven that it is feasible to reconstruct more meaningful visual information through brain-computer interfaces. Our next step is to fully advance the clinical translation of this technology." (Yuan Ning)

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