Data from: Precise control of neural activity using dynamically optimized electrical stimulation

Neural implants have the potential to restore lost sensory function by
electrically evoking the complex naturalistic activity patterns of neural
populations. However, it can be difficult to predict and control evoked
neural responses to simultaneous multi-electrode stimulation due to
nonlinearity of the responses. We present a solution to this problem and
demonstrate its utility in the context of a bi-directional retinal implant
for restoring vision. A dynamically optimized stimulation approach encodes
incoming visual stimuli into a rapid, greedily chosen, temporally dithered
and spatially multiplexed sequence of simple stimulation patterns. Stimuli
are selected to optimize the reconstruction of the visual stimulus from
the evoked responses. Temporal dithering exploits the slow time scales of
downstream neural processing, and spatial multiplexing exploits the
independence of responses generated by distant electrodes. The approach
was evaluated using an experimental laboratory prototype of a retinal
implant: large-scale, high-resolution multi-electrode stimulation and
recording of macaque and rat retinal ganglion cells ex vivo. The
dynamically optimized stimulation approach substantially enhanced
performance compared to existing approaches based on static mapping
between visual stimulus intensity and current amplitude. The modular
framework enabled parallel extensions to naturalistic viewing conditions,
incorporation of perceptual similarity measures, and efficient
implementation for an implantable device. A direct closed-loop test of the
approach supported its potential use in vision restoration.