New technique uses blood vessels to access brain activity with unprecedented precision

Osaka, Japan – Researchers at The University of Osaka have developed a groundbreaking, minimally invasive method for recording brain activity through blood vessels. This technique could potentially transform the diagnosis and treatment of neurological conditions like epilepsy and paving the way for advanced brain-computer interfaces. It eliminates the need for invasive open-brain surgery, offering a safer and more accessible way to monitor and stimulate brain function.

Current methods for directly measuring brain activity require invasive procedures, either removing part of the skull to place electrodes on the brain surface or inserting electrodes directly into brain tissue. While non-invasive methods like EEG exist, they lack the precision needed for detailed analysis. This new method bridges the gap, offering high-fidelity recordings without the risks associated with traditional invasive approaches.

The research team, led by Professor Takufumi Yanagisawa used a catheter to insert ultra-thin wire electrodes into the cortical and deep veins of pig brains. They successfully recorded brainwaves from these vessels with accuracy comparable to traditional methods. Notably, they were able to capture activity from deep brain regions previously difficult to access non-invasively. Stimulating electrodes in the motor cortex also successfully evoked muscle responses in the face and shoulders.

Dr. Takamitsu Iwata, lead researcher, mentions, “This less invasive approach promises improved diagnoses and treatments for epilepsy and other neurological disorders. It also unlocks new possibilities for understanding deep brain functions and developing next-generation brain-computer interfaces, potentially allowing individuals with severe paralysis to communicate and control devices.”
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The article, “Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness,” will be published in Advanced Intelligent Systems at DOI: https://doi.org/10.1002/aisy.202500487