Topic: closed-loop decoder adaptation

Brain-computer interfaces (BCIs) offer a unique method to study learning dynamics by defining a causal mapping between neural activity and movement. Examples include studying the acquisition of an arbitrary sensorimotor mapping or perturbing a learned mapping to study adaptation. Alternatively, the sensorimotor mapping (“decoder”) can be purposefully adapted in closed loop, as the subject controls the BCI, to improve performance. Beyond improving performance for applications, closed-loop decoder adaptation (CLDA) also allows the study of learning mechanisms under changing motor demands. Here,