Visual perceptual learning generalizes to untrained effectors

Visual perceptual learning (VPL) is an improvement in visual function following training. Although the practical utility of VPL was once thought to be limited by its specificity to the precise stimuli used during training, more recent work has shown that such specificity can be overcome with appropriate training protocols. In contrast, relatively little is known about the extent to which VPL exhibits motor specificity. Previous studies have yielded mixed results. In this work, we have examined the effector specificity of VPL by training observers on a motion discrimination task that maintains the same visual stimulus (drifting grating) and task structure, but that requires different effectors to indicate the response (saccade vs. button press). We find that, in these conditions, VPL transfers fully between a manual and an oculomotor response. These results are consistent with the idea that VPL entails the learning of a decision rule that can generalize across effectors.


Figure S2
Data and model fitting for each observer in Experiment 1. Each row represents the two models for one observer. The dashed vertical line represents a change in the experimental phase (from saccade to manual response). Small black open circles represent the contrast threshold for each block (125 trials). Blue dots represent the contrast threshold for each training session (median threshold for 4 blocks). Error bars show the standard deviation from the mean contrast threshold for each training session. The red curve represents the model fitting curve in the transfer model (left) and the no transfer model (right). In 5

Transfer model
No transfer model

Transfer model
No transfer model

Transfer model
No transfer model of the observers, the transfer model significantly fit the data better than the no transfer model (∆BIC = 7.5,range [7,8]). The better model is shown in bold for each observer.

Figure S3
Learning curves for each observer (n = 6) in Experiment 2. The dashed line represents the change in experimental phase. In phase one (left of the dashed line), the observer reported the direction of the motion with a manual response (keyboard). In phase two (right of the dashed line), the observer reported the direction of the motion with a saccade. Small black open circles represent the contrast threshold for each block (125 trials). Blue dots represent the contrast threshold for each training session/day (median threshold for 4 blocks). Error bars show the standard deviation from the mean contrast threshold for each training session/day. Shaded regions represent the time periods for each threshold measurement. Baseline threshold (blue) was computed as the threshold during the first day of training with the manual response. The training threshold was computed as the threshold during the last five days of training with the manual response (green). The transfer threshold was computed as threshold during the five days of training with the saccade (pink). Due to the COVID-19 pandemic, two observers (bottom row) were unable to complete the five days of training in phase 2 in Experiment 2.

Figure S4
Data and model fitting for each observer in Experiment 2. Each row represents the two models for one observer. The dashed vertical line represents a change in the experimental phase (from manual response to saccade). Small black open circles represent the contrast threshold for each block (125 trials). Blue dots represent the contrast threshold for each training session (median threshold for 4 blocks). Error bars show the standard deviation from the mean contrast threshold for each training session. The red curve represents the model fitting curve in the transfer model (left) and the no transfer model (right). In 5 of the observers, the transfer model significantly fit the data better than the no transfer model (∆BIC = 7,

Transfer model
No transfer model

Transfer model
No transfer model

Transfer model
No transfer model range [4,8]). The better model is shown in bold for each observer. For the one observer whose data was better fitted by the no transfer model (top row), the performance in the second phase of the experiment improved, indicative of transfer. Due to the COVID-19 pandemic, two observers (bottom row) were unable to complete the five days of training in phase 2 in Experiment 2.