Goal-directed state equation for tracking reaching movements using neural signals

This paper addresses the problem of estimating reaching movements. We derive a Bayesian-optimal discrete-time state equation to support real-time filters that incorporate observations about the target position and arm trajectory. The resulting algorithm is compatible with any filtering method, such as point process or Kalman filters, and any recording modality, such as multielectrode arrays, intracortical EEG, or eye trackers