Wireless Neural Implant to Study Natural Behavior with Saehyuck Oh & Janghwan Jekal
How can we record brain activity during natural behavior without bulky, restrictive devices? This question has challenged neuroscientists for years, but Saehyuck Oh and Janghwan Jekal from the Daegu Gyeongbuk Institute of Science and Technology (DGIST) have devised an innovative solution!
In this episode of the BCI Award Neurocareers podcast series, we dive into the world of stealthy neural recording with their project, "Behavior to Byte: Stealthy Neural Recorder." The team has developed a fully wireless, battery-free, and implantable neural interface designed for primates, allowing researchers to study brain activity during natural behavior without interrupting the subject. This groundbreaking device combines soft bioelectronics for long-term implantation, enabling it to be safely placed deep within the brain for precise neural recording.
Join us as Saehyuck and Janghwan share how their research tackles the challenges of developing implantable devices for primates—devices that must be durable, soft, and operate entirely without batteries. They’ll also discuss the potential for this technology to revolutionize neurobehavioral research and offer valuable advice for anyone aspiring to submit a successful project for the BCI Award!
Tune in to hear how their stealthy neural recorder is paving the way for more effective brain-behavior studies and changing the future of neural interfaces!
About the Podcast Guests:
Biography
Saehyuck Oh received his B.E. degree in biomedical engineering from Yonsei University in 2019 and a M.S. degree in robotics engineering from Daegu Gyeongbuk Institute of Science and Technology (DGIST) in 2021. He is currently a Ph.D. candidate under the supervision of Prof. Kyung-In Jang in robotics and mechatronics engineering at DGIST, where research focuses on soft bioelectronics. His work focuses on developing wearable and implantable biomedical devices that can interface with biological systems for biomedical applications.
Janghwan Jekal received his B.E. degree in School of Undergraduate Studies from Daegu Gyeongbuk Institute of Science and Technology (DGIST) in 2019. He is currently doing his Ph.D. degree under the supervision of Prof. Kyung-In Jang from robotics and mechatronics engineering at DGIST. His research focuses on implantable and wearable biomedical devices.
Research work
Activities such as exercising like riding a bicycle, taking deep breaths, eating, sleeping, experiencing sensations, controlling our weight, expending energy, and performing instinctive actions are all regulated by the brain. Each part of the brain is intricately connected, and the behaviors are the result of these complex processes. Therefore, to truly understand the origins of behavior, it is essential to measure and study brain neural activity.
So, which animal model is most appropriate for studying the brain neural activity underlying natural behavior? Among the various experimental subjects, ranging from fish to humans, primates are the most suitable. Primates are genetically and anatomically similar to humans and possess high cognitive behavioral functions sililar to humans.
So, what engineering elements are needed in a device to study the primate brain?
Firstly, since monkeys can freely use their arms and legs and might can break the device, so it must be completely implanted. This necessitates the device to operate entirely wireless and without batteries, as it is impractical to charge or replace batteries in a monkey.
Additionally, for long-term implantation, the neural probe must be soft to match the mechanical properties of living tissues. Since, brain regions associated with natural behaviors are located in the deep brain region, so the neural probe must be inserted into these deep brain regions.
Also, the signals measured using these devices must undergo signal processing and artificial intelligence analysis to effectively
Information
- Show
- FrequencyWeekly Series
- PublishedNovember 29, 2024 at 8:26 PM UTC
- Length51 min
- Season2
- Episode103
- RatingClean