Innovative Blood Vessel-Based Brainwave Recording Achieves Unprecedented Precision with Minimal Invasiveness

Researchers at the University of Osaka have pioneered a groundbreaking approach to monitor brain activity by accessing blood vessels rather than traditional brain tissue. This novel method, detailed in their publication "Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness," allows for highly accurate brain signal recordings without the need for invasive surgery.

Unlike conventional techniques such as intracranial EEG, which require opening the skull and placing electrodes directly onto or into the brain tissue, this new technique involves inserting ultra-thin wire electrodes into cortical and deep brain veins via a catheter. This approach significantly reduces the risks associated with invasive brain procedures.

In their study, the team successfully recorded detailed neural activity from pig brains by inserting electrodes into these blood vessels, capturing signals from regions that were previously difficult to access noninvasively. Notably, stimulation of electrodes in the motor cortex elicited muscle responses in the face and shoulders, demonstrating functional connectivity and potential for therapeutic applications.

According to lead researcher Dr. Takamitsu Iwata, this less invasive method could revolutionize the diagnosis and treatment of neurological disorders like epilepsy. It offers a safer, more accessible way to monitor brain function, paving the way for advanced brain-computer interfaces especially beneficial for individuals with paralysis who seek to communicate or control devices.

This innovative approach bridges the gap between noninvasive methods like EEG and traditional invasive recordings, providing high-fidelity data essential for both clinical diagnostics and research. Ultimately, it opens new pathways for understanding deep brain functions and developing next-generation neural technologies.

For more details, see the publication in Advanced Intelligent Systems (2025). Source: Medical Xpress.