Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain...

Area of Science:

• Neuroscience
• Robotics
• Biotechnology

Background:

• Brain-computer interfaces (BCIs) offer novel human-machine interaction methods.
• Controlling biological organisms with neural signals presents unique challenges and opportunities.

Purpose of the Study:

• To develop an all-chain-wireless brain-to-brain system (BTBS) for controlling a cyborg cockroach using human brain signals.
• To enhance the performance of a steady-state visual evoked potential (SSVEP) based BCI through an optimization algorithm.

Main Methods:

• Utilized a steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) to decode human motion intention.
• Integrated a portable microstimulator for invasive electrical nerve stimulation in cockroaches.
• Employed Bluetooth communication for transmitting BCI commands to the cyborg cockroach's nervous system.

Main Results:

• The optimization algorithm improved the online classification accuracy of the three-mode BCI from 72.86% to 78.56%.
• The cyborg cockroaches achieved a mean response accuracy of 89.5% when controlled by the BTBS.
• Successfully navigated cyborg cockroaches along an S-shape track with a 20% success rate, demonstrating functional human-to-cockroach brain information transfer.

Conclusions:

• The developed BTBS successfully established a functional information transfer pathway from the human brain to the cockroach brain.
• The proposed optimization algorithm enhances BCI performance for real-time control applications.
• This study demonstrates the feasibility of using BCI for controlling living organisms, paving the way for future biohybrid systems.