Intracortical Decoding
Team members
Our goal is to decode intracortical neuronal population activity to better understand brain function. It has been emphasized that neuronal populations are key to understanding the mechanisms controlling various brain functions, ever since the development of multi-unit recording techniques. The complex multivariate patterns of neural signals make analyzing these population signals challenging. By leveraging machine learning and deep learning techniques, we are investigating cognition and movement in both human and non-human primates.
If you allow a monkey to choose between them, what do you think will happen in the monkey's brain? Considering the neurophysiological differences between brain regions, it becomes remarkably difficult to understand the transition from decision-making to movement execution. We are eager to elucidate this transition by analyzing neuronal signals from the monkey’s M1 and DLPFC regions.
Ever since Neuralink announced the FDA approval of their system, the BCI era has moved one step closer. However, current BCI technology primarily leverages kinematic information, rather than more complex and higher brain functions such as cognition. Our team is currently exploring the feasibility of leveraging cognitive information from the DLPFC region.
ECoG is less invasive compared to direct recordings of neuronal spikes. However, the placement of ECoG electrodes varies among epilepsy patients. Our goal is to develop a location-independent feature extraction technique for stable decoding performance.
If you allow a monkey to choose between them, what do you think will happen in the monkey's brain? Considering the neurophysiological differences between brain regions, it becomes remarkably difficult to understand the transition from decision-making to movement execution. We are eager to elucidate this transition by analyzing neuronal signals from the monkey’s M1 and DLPFC regions.