Visual cortical prostheses (VCPs) have the potential to restore visual function to patients with acquired blindness. Successful implementation of VCPs requires the ability to reliably map the location of the phosphene produced by stimulation of each implanted electrode.

To evaluate the efficacy of different approaches to phosphene mapping and propose simple improvements to mapping strategy.

We stimulated electrodes implanted in the visual cortex of five blind and fifteen sighted patients. We tested two fixation strategies, unimanual fixation, where subjects placed a single index finger on a tactile fixation point and bimanual fixation, where subjects overlaid their right index finger over their left on the tactile point. In addition, we compared absolute mapping in which a single electrode was stimulated on each trial, and relative mapping with sequences containing stimulation of three to five phosphenes on each trial. Trial-to-trial variability present in relative mapping sequences was quantified.

Phosphene mapping was less precise in blind subjects than in sighted subjects (2DRMS, 16 ± 2.9° vs. 1.9 ± 0.93°; t (18) = 18, p = <0.001). Within blind subjects, bimanual fixation resulted in more consistent phosphene localization than unimanual fixation (BS1: 4.0 ± 2.6° vs. 19 ± 4.7°, t (79) = 24, p < 0.001; BS2 4.1 ± 2.0° vs. 12 ± 2.7°, t (65) = 19, p < 0.001). Multi-point relative mapping had similar baseline precision to absolute mapping (BS1: 4.7 ± 2.6° vs. 3.9 ± 2.0°; BS2: 4.1 ± 2.0° vs. 3.2 ± 1.1°) but improved significantly when trial-to-trial translational variability was removed. Although multi-point mapping methods did reveal more of the functional organization expected in early visual cortex, subjects tended to artificially regularize the spacing between phosphenes. We attempt to address this issue by fitting a standard logarithmic map to relative multi-point sequences.

Relative mapping methods, combined with bimanual fixation, resulted in the most precise estimates of phosphene organization. These techniques, combined with use of a standard logarithmic model of visual cortex, may provide a practical way to improve the implementation of a VCP.