Topic: high-density intracranial electrocorticography

Finding a low-dimensional manifold of neural signals is crucial for understanding neural computation and developing a robust brain-computer interface (BCI). Latent variable models have been proposed to find such manifolds, and proved to be successful in various cognitive and behavioral tasks. However, natural speaking is a complex coordination of multiple motor tasks, and due to such complex nature, it has been challenging to find a low-dimensional and behaviorally relevant manifold of the speech cortex. We hypothesize that contents represented on the manifold should be consistent across repea