Adaptive Motor Control During Experiments With Brain Machine Interfaces

Recent experiments with Brain Machine Interfaces indicate that the extent of neural modulations increases abruptly upon starting to operate the interface. In contrast, neural modulations due to the trajectory profile remain relatively unchanged. Furthermore, the enhanced modulations subside with further training, mirroring the trend in task performance, which degraded upon starting to operate the interface and improved gradually with training. Here we investigate the hypothesis that the enhanced modulations reflect internal representation of trajectory errors, which results in corrective commands in the short term and adaptive modifications of internal models in the long term. A simplified uni-dimensional model is analyzed to demonstrate the observed transient enhancement in neural modulations during the operation of Brain machine Interfaces. Identifying the source of the transient enhancement in neural modulation would provide insight into adaptive motor control and facilitate the improvement of future Brain Machine Interfaces.