Human Vicarious Trial and Error Is Predictive of Spatial Navigation Performance

Abstract

When learning new environments, rats often pause at decision points and look back and forth over their possible trajectories as if they were imagining the future outcome of their actions, a behavior termed "Vicarious trial and error" (VTE). As the animal learns the environmental configuration, rats change from deliberative to habitual behavior, and VTE tends to disappear, suggesting a functional relevance in the early stages of learning. Despite the extensive research on spatial navigation, learning and VTE in the rat model, fewer studies have focused on humans. Here, we tested whether head-scanning behaviors that humans typically exhibit during spatial navigation are as predictive of spatial learning as in the rat. Subjects performed a goal-oriented virtual navigation task in a symmetric environment. Spatial learning was assessed through the analysis of trajectories, timings, and head orientations, under habitual and deliberative spatial navigation conditions. As expected, we found that trajectory length and duration decreased with the trial number, implying that subjects learned the spatial configuration of the environment over trials. Interestingly, IdPhi (a standard metric of VTE) also decreased with the trial number, suggesting that humans benefit from the same head-orientation scanning behavior as rats at spatial decision-points. Moreover, IdPhi captured exclusively at the first decision-point of each trial, was correlated with trial trajectory duration and length. Our findings demonstrate that in VTE is a signature of the stage of spatial learning in humans, and can be used to predict performance in navigation tasks with high accuracy.

Keywords: deliberation; habitual; hippocampus; navigation; spatial decision-making.

Figure 1

(A) Left: Virtual maze layout. S1,S2 and T1,T2 denote the possible starting and target locations, respectively. Two exmaple of starting-target combinations with respectively optimal (blue) and erratic (red) trajectories schematics. (B) Screenshots of the environment through first-person perspective. (C) Example of an early (Left) and a late (Right) trial trajectories from one subject.

Figure 2

(A) Example of trajectories from one participant in the high frequency condition. Numbers correspond to trial number. Red and gray dots represent the starting and end of the trial, respectively. (B) Mean and standard error of trial duration (left) and length (right) for the first 14 trials of each condition (high/low). (C) Route difference between every trajectory pair in each condition, averaged across subjects.

Figure 3

Navigational measures at high and low frequency conditions. Trajectory duration, length and IdPhi were smaller for the high condition when compared to the low frequency condition (t-test: duration p < 0.05, length p < 0.05, IdPhi p < 0.01). Gray lines represent the mean of each subject in a given condition. Condition level description depicted by box-plots median (horizontal orange line) and lower and upper quartile values of the data (horizontal black lines).

Figure 4

Navigational measures along the first 14 trials of each participant at each frequency conditions. Trajectory duration (mean ± sem). Duration, length and IdPhi strongly decreased on the first three trials of each condition. High frequency trials were maintained on negative standard deviation throughout the experiment, while low frequency trials oscillated around zero.

Figure 5

Head-orientation and decision-making duration. (A) Participant's rate maps were aligned (rotated 180 deg) when necessary so that starting location would match across participants and conditions. Rate maps of low (left) and high (center) frequency conditions, as well as their difference (right) are shown. Shown rate maps represent the mean across participants. (B) Cluster-level statistical permutation test for head-orientation in the low and high conditions. Colored bins are locations that survived multiple comparisons correction with p-value < 0.05. Note the strong cluster at the first decision-point (dashed pink line, zoomed on the right) suggesting a greater head-orientation variance for the low frequency condition. (C) Time spent from trial onset until entrance in one of the possible maze alleys (averaged across participants).

Figure 6

IdPhi at first decision-point correlates with navigational aspects (Top) Relation between length and duration of each trial for all subjects (left) is highly correlated (Spearman test r = 0.942, p = 0). Correlations for individuals are shown on the right column. (Middle) Correlation between length and IdPhi (Spearman test r = 0.431, p < 0.001). (Bottom) Correlation between duration and IdPhi (Spearman test r = 0.5015, p < 0.001).