Less is more: selection from a small set of options improves BCI velocity control

We designed the discrete direction selection (DDS) decoder for
intracortical brain computer interface (iBCI) cursor control and showed
that it outperformed currently used decoders in a human-operated real-time
iBCI simulator and in monkey iBCI use. Unlike virtually all existing
decoders that map between neural activity and continuous velocity
commands, DDS uses neural activity to select among a small menu of preset
cursor velocities. We compared closed-loop cursor control across four
visits by each of 48 naïve, able-bodied human subjects using either DDS or
one of three common continuous velocity decoders: direct regression with
assist (an affine map from neural activity to cursor velocity), ReFIT, and
the velocity Kalman Filter. DDS outperformed all three by a substantial
margin. Subsequently, a monkey using an iBCI also had substantially better
performance with DDS than with the Wiener filter decoder (direct
regression decoder that includes time history). Discretizing the decoded
velocity with DDS effectively traded high resolution velocity commands for
less tortuous and lower noise trajectories, highlighting the potential
benefits of simplifying online iBCI control.