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 velo..., Data were collected from 48 able-bodied human participants on four separate lab visits each using the protocol for the real-time, human-in-the-loop, invasive brain-computer interface model called the jaBCI (published model details at DOI 10.1088/1741-2552/ac97c3). 
Briefly, a subject wears a CyberGlove III that monitors the relative excursions of 19 different hand and finger joint angles. The same pre-trained artificial neural network used in the jaBCI validation study computes a set of emulated neural firing rates based on the preceeding 100ms of joint angle input data. To align with contemporary firing rate integration bin widths used in iBCI studies, we set the emulator to emit neural firing rates every 50 ms. At each time bin the subject’s neural decoder uses the emulated neural activity to compute the velocity of the computer cursor and the graphical display is updated accordingly. The joint angle tracking, neural emulation, and decoding all run in real-time. To mimic the phenomeno..., , # Less is more: selection from a small set of options improves BCI velocity control

Link to BioRxiv post of study describing the full study for which these data were collected: [https://doi.org/10.1101/2024.06.03.596241](https://doi.org/10.1101/2024.06.03.596241)

Healthy human subjects operated an invasive brain-computer interface (**BCI**) simulator (see DOI 10.1088/1741-2552/ac97c3 for technical details), wherein their finger movements were used to computationally synthesize a simulation of cortical neural firing rates. The synthetic firing rates were processed by different neural decoding algorithms (depending on the experiment group to which the subject belonged) to generate the velocity of a computer cursor, as is typical in invasive brain-computer interface studies. Subjects performed a center-out target acquisition task using the BCI simulator where they attempted to piloted the cursor to and stay within the a displayed target to register a successful hit, before returning to t...