I. Introduction
Brain-Computer interfaces (BCIs) are devices that estimate a user's movement intention from neural activity from the brain to guide an assistive device such as a prosthetic arm or a computer cursor. They aim to help people with motor impairment (e.g., due to amyotrophic lateral sclerosis, brainstem stroke, or cervical spinal cord injury) in the ability to communicate (e.g., controlling a cursor to type and use a computer) or through restored mobility. BCIs typically record neural activity through different modalities such as electroencephalography (EEG) [1]–[4], electrocorticography (ECoG) [5]– [9] or intracortical multielectrode arrays, which are typically chronically implanted in the motor cortex [10] –[24]. Intracortical BCIs (iBCI) have shown promising results in pilot clinical trials and are the highest-performing BCI systems to date, making them prime candidates for serving as an assistive technology for people with paralysis [25]– [28]. Although the performance of iBCI systems has markedly improved in the last two decades, errors – such as selecting the wrong key during typing as a result of decoder or user error – still occur. The errors can be due to either user's mistake or BCI misinterpretation of user intention. Nevertheless, they decrease the performance.