Using gaze behavior to parcellate the explicit and implicit contributions to visuomotor learning

Abstract

Successful motor performance relies on our ability to adapt to changes in the environment by learning novel mappings between motor commands and sensory outcomes. Such adaptation is thought to involve two distinct mechanisms: an implicit, error-based component linked to slow learning and an explicit, strategic component linked to fast learning and savings (i.e., faster relearning). Because behavior, at any given moment, is the resultant combination of these two processes, it has remained a challenge to parcellate their relative contributions to performance. The explicit component to visuomotor rotation (VMR) learning has recently been measured by having participants verbally report their aiming strategy used to counteract the rotation. However, this procedure has been shown to magnify the explicit component. Here we tested whether task-specific eye movements, a natural component of reach planning, but poorly studied in motor learning tasks, can provide a direct readout of the state of the explicit component during VMR learning. We show, by placing targets on a visible ring and including a delay between target presentation and reach onset, that individual differences in gaze patterns during sensorimotor learning are linked to participants' rates of learning and their expression of savings. Specifically, we find that participants who, during reach planning, naturally fixate an aimpoint rotated away from the target location, show faster initial adaptation and readaptation 24 h later. Our results demonstrate that gaze behavior cannot only uniquely identify individuals who implement cognitive strategies during learning but also how their implementation is linked to differences in learning. NEW & NOTEWORTHY Although it is increasingly well appreciated that sensorimotor learning is driven by two separate components, an error-based process and a strategic process, it has remained a challenge to identify their relative contributions to performance. Here we demonstrate that task-specific eye movements provide a direct read-out of explicit strategies during sensorimotor learning in the presence of visual landmarks. We further show that individual differences in gaze behavior are linked to learning rate and savings.

Keywords: eye movements; motor adaptation; motor learning; reaching visuomotor rotation.

Fig. 1.

Experimental setup and procedures. A: experimental setup. Participants performed fast reaching movements by sliding a pen across a digitizing tablet, without vision of the hand. Visual stimuli and the cursor representing the hand position were presented on a monitor. B: task. A target was presented in 1 of 8 locations and flanked by a ring of landmark circles. Veridical cursor feedback was provided in the baseline and washout blocks. In the rotation block, participants were exposed to a 45° rotation of the cursor feedback. C: trial types. In no report trials, participants were given a 2-s preview of the target and landmarks before the response was cued. In report trials, participants reported their aiming direction via the numbered visual landmarks.

Fig. 2.

Gaze behavior in rotation trials. A: typical behavior in a no report trial in the rotation block. This participant first moved their gaze to the visual target, then in the direction of the hand target, and back to the visual target before executing the reach movement. B: time course of fixations (75–125% of target distance; purple), and hand movement (blue) during the target preview, hand reaction time (RT), and reach for the trial shown in A. C: probability of fixation in the start area (<75% of target distance; gray trace), target area (75–125% of target distance and <8.4° of the visual target; yellow trace), and aim area (75–125% of target distance and −8.4° to −45° from the visual target; orange trace) as a function of normalized within trial timing, averaged across the subgroup of aimpoint fixators in experiment 1 (n = 18). Shaded areas represent means ± SE. Separate graphs are shown for the 1st (left) and 2nd (right) half of the rotation block on day 1 (top) and day 2 (bottom). D: timing of fixation in the visual target area, following a fixation in the aimpoint area, in the rotation block of experiment 1 (51% of correct no report trials). The blue area indicates the mean duration of the reach. Inset: proportion of trials in which a fixation at the visual target started before the offset of the reach (blue dashed line), relative to the total number of selected trials. The dots indicate this proportion for each aimpoint fixator; the boxplot indicates the median and interquartile range across subjects. E: probability plots averaged across aimpoint fixators (n = 5) in experiment 3, organized and computed the same as in C. F: as in D, containing 21% of rotation trials, averaged across aimpoint fixators in experiment 3.

Fig. 3.

Raw data and experimental approach of classifying participants. Raw end point hand angles (blue), reported aim angles (orange) and fixation angles (purple) during the 2-s target preview period in no report trials of a representative participant in the intermittent report Experiment on day 1 (top) and day 2 (bottom). The gray background indicates when a 45° rotation was applied to the cursor feedback. Vertical dotted lines indicate the timing of 30 s breaks during the experiment. The darker purple dots show, for each trial, the selected fixation angle closest to the hand target, used to compute the group average aimpoint fixation angle. Rightmost column: histogram of all fixation angles in the rotation block. This participant was classified as an aimpoint fixator because their gaze distribution was well fit by a mixture of 2 Gaussian curves.

Fig. 4.

Results intermittent report experiment. A: end point hand angles (blue), reported aim angles (orange), implicit angles (green), and selected fixation angles (purple) on day 1 (top) and day 2 (bottom), averaged across aimpoint fixators (n = 18) in experiment 1. Each data point represents the average of a set of 8 trials, with error bars showing ± 1 SE across subjects. Purple bars at the top of each graph depict the number of participants contributing to the average selected fixation angle in each trial set. The gray background indicates when the 45° rotation was applied to the cursor feedback. Vertical dotted lines indicate the timing of 30-s breaks during the experiment. The rows of dots in between the top and bottom graphs show the results of uncorrected paired t-tests between each of the data points on days 1 and 2, with the color saturation indicating the significance level. B: relation between the reported aim angle and the selected fixation angle, averaged across the 2nd half of the rotation block of days 1 and 2. Dashed line indicates the unity line. C: relation between hand angle and selected fixation angle during early adaptation (trial sets 2–10 of the rotation block). R and P values in B and C show Pearson’s correlation coefficient and its significance value, respectively.

Fig. 5.

Results no report experiment. A: end point hand angles, implicit angles (estimated through subtraction of fixation angles from hand angles), and selected fixation angles, averaged across aimpoint fixators (Aim-Fix, n = 11), as well as end point hand angles averaged across target-only fixators (TO-Fix, n = 8) in experiment 2. Each data point represents the average of a set of eight trials, with error bars showing ± 1 SE across subjects. Purple bars at the top of each graph show the number of aimpoint fixators contributing to the average selected fixation angle. The gray background indicates when the 45° rotation was applied to the cursor feedback. Vertical dotted lines indicate the timing of 30 s breaks during the experiment. The row of dots at the bottom of each graph shows the result of unpaired t-tests between the aimpoint fixators and the target-only fixators. The rows of dots in between the top and bottom graphs show the results of uncorrected paired t-tests between each of the data points on days 1 and 2, with the color saturation indicating the significance level. B: relation between hand angle and selected fixation angle across aimpoint fixators during early adaptation (trial sets 2–10 of the rotation block). R and P values show Pearson’s correlation coefficient and its significance value, respectively.

Fig. 6.

Results no preview experiment. A and B: raw end point hand angles (blue), fixation angles during the hand reaction time interval (RT; purple), and hand reaction times (black) of 2 example participants in experiment 3. The gray background indicates when a 45° rotation was applied to the cursor feedback. Vertical dotted lines indicate the timing of 30 s breaks during the experiment. The darker purple dots show, for each trial, the selected fixation angle closest to the hand target. Rightmost column: the relation between selected fixation angles and hand reaction time. R and P values show Pearson’s correlation coefficient and its significance value, respectively. C: end point hand angles, implicit angles (estimated through subtraction of fixation angles from hand angles), and selected fixation angles, averaged across aimpoint fixators (Aim-Fix, n = 5), as well as end point hand angles averaged across target-only fixators (TO-Fix, n = 6) in experiment 3. Each data point represents the average of a set of 8 trials, with error bars showing ± 1 SE across subjects. Purple bars at the top of each graph show the number of aimpoint fixators contributing to the average selected fixation angle. The row of dots at the bottom of the graph shows the result of unpaired t-tests between the aimpoint fixators and the target-only fixators. Also shown in C, end point hand angles averaged across the subgroup of five aimpoint fixators and six target-only fixators. The participant shown in A was excluded from the group average because of the sudden change in hand angle. As in experiment 2, adaptation and washout were faster for the aimpoint fixators than for the target-only fixators.