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최영빈

Tchoe, Youngbin
Neural Interfaces and Semiconductor Optoelectronics Lab
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Neural Interface Technologies for High Resolution Intraoperative Brain Mapping

Author(s)
Tchoe, Youngbin
Issued Date
2025-02-10
URI
https://scholarworks.unist.ac.kr/handle/201301/89898
Citation
2025 Global Symposium on Multiscale Biohybrid Systems
Abstract
Electrophysiological devices are critical for mapping both healthy and pathological areas of the brain and facilitating therapeutic neuromodulation in medical practices. They are also extensively being developed for brain-machine interfaces, highlighting their critical role in both healthcare and research. However, current devices frequently fall short in terms of spatial resolution or the extent of cortical coverage they can provide. To address these limitations, we developed an advanced micro-electrocorticography (ECoG) grid, through the application of sophisticated nanofabrication methods and enhanced connectorization strategy. This thin-film neurophysiological recording electrode features thousands of channels and has been successfully applied to human brains in intraoperative settings. This micro-ECoG grid, enhanced by low impedance platinum-nanorods, offers excellent electrocorticography recording with unprecedented spatial resolution and cortical coverage. This technology enables precise delineation of motor and sensory cortices, detailed sensory mapping of human fingers, and visualization of the propagation dynamics of epileptiform activities.
Furthermore, to enable real-time feedback of brain signals recorded directly from the cortical surface during neurosurgery, we developed real-time brain signal mapping techniques and integrated a flexible micro-LED display with the micro-ECoG grid. This system not only captures intricate brain dynamics with high precision but also visualizes functional brain boundaries and epileptic discharges on the cortical surface. The integration of the micro-ECoG grid with the micro-LED array has the potential to advance current neurosurgical practices, enabling surgeons to perform procedures with greater precision and efficiency, supported by high-resolution functional brain mapping and real-time visual feedback on top of the cortical surface.
Publisher
UNIST

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