Model predictions of behavioral responses in the change detection task.

(A) Same as in Fig 5E (main text), but showing response proportions predicted with the baseline model (y-axis) versus observed (true) response proportions (x-axis) in the change detection task. (B) Same as in Fig 5E (main text), but showing response proportions predicted with the perceptual bias model (y-axis) versus observed (true) response proportions (x-axis) in the change detection task. (A, B) Other conventions are the same as in Fig 5E. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. (TIF)</p

Perceptual and choice biases contribute to presaccadic selection’s effects on orientation change detection.

(A) Schematic of the variable precision model for a change detection and localization task. (Left box) Internal measurements of the initial (θi) and final (θf) Gabor stimuli are represented by latent vectors (x and y, respectively) that follow von Mises distributions, with concentration parameters, κ. The encoding precision (J, directly related to κ) is variable across items and trials. (Middle box) F(l), the decision variable at each location, l, is proportion to the posterior odds ratio of probability of change (C) at that location to the probability of no change (N). The Bayesian ideal observer localizes the change to the location at which the decision variable F(l) exceeds the decision threshold ηl by the highest margin. If the decision variable does not exceed the decision threshold at any location, the observer reports “no change.” Perceptual bias model: The “baseline” VP model was modified to incorporate a “perceptual bias,” i.e., an attractive recency bias parameter, B, at the ST location (red text). Choice bias model: The “baseline” VP model was modified to incorporate unequal decision threshold parameters, ηl, at the ST and SA locations (green text). Both biases model: Both perceptual bias and unequal decision threshold parameters were incorporated into the VP model (blue text). (B) (Left) Model comparison with the AICc, for the 4 VP models. Gray/black: baseline model, red: perceptual bias model, green: choice bias model, blue: both biases model. Box-and-whisker plot conventions are the same as in Fig 1E. (Right) Same as in the left panel, but showing the cross-validated data likelihoods for the 4 models. Other conventions are the same as in the left panel. (C) Same as in Fig 1E, but showing the decision threshold, η, estimated for the ST and SA locations with the “both biases” model. Other conventions are the same as in Fig 1E. (D) Response proportions predicted with the both biases model (y-axis) versus observed (true) response proportions (x-axis) in the change detection task. Circles: hits, upward triangles: FAs, downward triangles: misses, squares: correct rejections (CRs). Other conventions are the same as in panel C. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. AICc, corrected Akaike information criterion; CR, correct rejection; CV, cross-validated; FA, false alarm; SA, Saccade Away; ST, Saccade Toward; VP, variable precision.</p

Evidence for a presaccadic recency bias in orientation estimation.

(A) Schematic showing an attractive bias (bottom, left), a repulsive bias (bottom, right), and no bias (top). In the case of an attractive bias, orientation estimates (gray) of the actual stimulus (red) are biased toward the orientation of the biasing stimulus (blue). In the case of the repulsive bias, orientation estimates are biased away from the biasing stimulus. (B, C) Recency bias: the bias in the orientation estimate of the initial stimulus induced by the final stimulus. (B) Estimation error for the initial stimulus (y-axis) plotted against the difference between orientations of the final and initial stimuli (x-axis), at the ST (purple) and the SA (orange) locations. Dashed horizontal and vertical lines: zero estimation error and zero orientation difference, respectively. Thick, solid lines: Cubic spline fits. (C) Recency bias at the ST (left, purple) and SA (right, orange) locations in the double set trials, quantified using the signed area under the curve, from panel B (Methods). Positive and negative values denote an attractive or a repulsive bias, respectively. Other conventions are the same as in Fig 1E. (D, E) Primacy bias: the bias in the orientation estimate of the final stimulus induced by the initial stimulus. (D) Same as in panel B, but showing the estimation error for the final stimulus (y-axis) plotted against the difference between orientations of the initial and final stimuli (x-axis). Other conventions are the same as in panel B. (E) Same as in panel C, but showing primacy bias. Other conventions are the same as in panel C. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. SA, Saccade Away; ST, Saccade Toward.</p

Effects of presaccadic selection on precision of orientation estimates.

(A) Dual task paradigm for presaccadic orientation estimation, with 3 different trial types: (yellow outline, upper row) single set trials, (yellow outline, middle row) double set trials, and (yellow outline, lower row) noise mask trials. Participants estimated the orientation of either the initial or the final set of Gabor stimuli in distinct blocks of trials, while also planning a saccade toward the cued location (see text for details). (B) (Top) Distribution of estimation errors at the Saccade Toward (left, purple) and Away (right, orange) locations for single set trials. Lines: von Mises fits. (Bottom) MAE of orientation estimates at the ST (left) and SA (right) locations, for the initial stimulus of single set trials (n = 5 participants). (C) Same as in panel B, but showing error distributions and MAE for the initial stimulus of double set trials. (D) Same as in panel B, but showing error distributions and MAE for the final stimulus of double set trials. (E) Same as in panel B, but showing error distributions and MAE for the initial stimulus of noise mask trials. (B–E) Other conventions are the same as in Fig 1E. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. MAE, Mean absolute error; SA, Saccade Away; ST, Saccade Toward.</p

Control analyses for temporal order reversal effects.

(A) Same as in Fig 3C (main text), but showing recency bias at the Saccade Toward and Saccade Away locations, following exclusion of trials in which the saccade onset occurred (B) Same as in panel A, but showing primacy bias at the Saccade Toward and Saccade Away locations. (A, B) Other conventions are the same as in Fig 3C. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. (TIF)</p

Transient-locked saccade onset times.

(A) Same as in Fig 1C, but showing the distribution of saccade onset times locked to the time of transient (blank onset), pooled across participants, in the orientation change detection task. Annotation: p-values for Hartigan’s dip test of unimodality. Other conventions are the same as in Fig 1C. (B) Same as in panel A, but showing the distribution of saccade onset times locked to the time of transient for each participant (distinct plots). Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. (TIF)</p

Variable precision model fits presaccadic selection’s effects on orientation estimation.

(A) Schematic of the variable precision (VP) model for orientation estimation. (Top row) On each trial, internal measurement, x, of a stimulus with orientation, θ, follows a von Mises distribution, with a concentration parameter κ determined by precision parameter J. (Middle row) Across trials the precision is gamma distributed, with a mean and scale parameter τ. (Bottom row) The distribution of the internal measurement x across trials is a mixture of von Mises distributions, marginalized across precision values. (B) Log likelihood (log (L)) landscape as a function of precision for the final stimulus at the ST location () and scale, τ; although log likelihood is a function of all model parameters, these 2 parameters were chosen for illustrative purposes. Warmer colors indicate higher likelihoods. Red asterisk: Parameters corresponding to maximum log likelihood. Gray lines: contours of iso-log likelihood. (C) Left to right: Fits of the variable precision model (solid red lines) to the observed responses (light red histograms) for the initial ST, final ST and SA (pooled) stimuli, respectively, obtained with maximum likelihood estimation, based on the parameters in panel B. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. SA, Saccade Away; ST, Saccade Toward.</p

Bayesian Sequential Analysis robustness check.

(A) Bayesian Sequential Analysis based on a paired sample t test, as a function of sample size, for d’ difference between the Saccade Toward (ST) and Saccade Away (SA) locations in the change detection tasks. Samples are pooled over the orientation change (n = 10) and contrast change (n = 7) detection experiments to yield a total sample size of n = 17. Here, H0 is the hypothesis that d’ is not different between the ST and SA locations while H1 is the alternative hypothesis that d’ is different across these locations. The x-axis represents the sequential sample sizes (from n = 1 to n = 17 participants), the left y-axis indicates the Bayesian Factor supporting H1 over H0 (BF10), and the right y-axis provides labels for different BF levels. Similarly, BF01 quantifies the evidence supporting H0 over H1. (Inset top-center) Pie chart indicates the data likelihoods under the 2 hypotheses (white: H0 and red: H1). (B) Same as in panel (A) but for criterion difference between the ST and SA locations in the change detection tasks. Other conventions are the same as in panel A. (C) Same as in panel (A) but for a difference in initial stimulus precision between the ST and SA locations, in “double set” trials, in the orientation estimation task (n = 10). (D) Same as in panel (C) but for a difference in final stimulus precision between the ST and SA locations, in “double set” trials, in the orientation estimation task (n = 10). (E) Same as in panel (A) but for recency bias at the ST location in the orientation estimation task (n = 10). (F) Same as in panel (E) but for primacy bias at the ST location in the orientation estimation task (n = 10). (B–F) Other conventions are the same as in panel A. (TIF)</p

Effects of presaccadic selection on visual change detection sensitivity and criterion.

(A) Dual task paradigm for quantifying presaccadic change detection performance in multialternative orientation change detection (top row) and contrast change detection (bottom row) tasks. Participants detected and localized changes in Gabor orientation (top) or contrast (bottom) while also planning a saccade to the cued location (see text for details). Rightmost panel: Response box configuration. UR, upper right; UL, upper left; LL, lower left; LR, lower right; NC, no change. (B) Distribution (filled histogram) of the interval between saccade cue onset and saccade onset, across trials, for a representative (median) participant. Fit: kernel density estimate. (C) Distribution (open histogram) of the interval between the final stimulus offset and saccade onset, for the same participant as in panel B. Other conventions are the same as in panel B. (D) (Left) Stimulus-response contingency table for a multialternative change detection and localization (4-ADC) task. Rows: stimulus events, columns: response types. H, hits; M, misses; ML, mislocalizations; FA, false alarms; CR, correct rejections (see Methods for more details). ST, Saccade Toward; SA, Saccade Away; ip, ipsilateral; op, opposite; co, contralateral (all relative to the Saccade Toward location); NC, no change. (Right) Multidimensional signal detection model for estimating criterion and sensitivity at each location (see Methods for details). Change-ST: change at saccade target location (purple distribution and decision zone); Change-SA: change at saccade away location (orange distribution and decision zone); No change: no change at either location (black/gray distribution and decision zone). (E) Sensitivity for orientation change detection reports at the saccade target (Toward) and non-saccade target (Away) locations (n = 10 participants). Violin: rotated kernel density estimates; center line: median; box limits: upper and lower quartiles; whiskers: 1.5× interquartile range. All data points are shown. Purple: Saccade Toward (ST) location. Orange: Saccade Away (SA) location. (F) Same as in panel E, but showing criterion for orientation change detection and localization. (G) Same as in panel E, but showing the time course of sensitivity at ST and SA locations, locked to the saccade onset (dashed vertical line). Shaded gray zone: saccadic suppression epoch. (H) Same as in panel G, but showing the time course of criterion at ST and SA locations, locked to the saccade onset. (I) Time course of sensitivity modulation—difference in sensitivity at the Saccade Toward and Away locations—locked to saccade onset (dashed vertical line). Δ = Toward–Away. (J) Same as in panel I, but showing time course of criterion modulation—difference in criterion at the Saccade Toward and Away locations—locked to saccade onset. (H–J) Other conventions are the same as in panel G. (K) Same as in panel E, but showing sensitivity at the Saccade Toward and Away locations (n = 7 participants) for the contrast change detection task. (L) Same as in panel F, but showing criterion for contrast change detection task. All panels. Asterisks: significance levels (* p p p (F–L) Other conventions are the same as in panel E. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002.</p

Presaccadic selection effects in different time windows and for different stimulus strengths.

(A) Relationship between estimated criterion (y-axis) plotted against proportion of hits and false alarms (x-axis), at the Saccade Toward (purple) and the Saccade Away (orange) locations. Distinct symbols denote distinct time bins prior to saccade onset. Circle: –300 to –200 ms, triangle: –200 to –100 ms, square: –100 to 0 ms. Each point denotes 1 time bin per participant. (B) (Top) Temporal dynamics of the sum of hit and false alarm rates at the Saccade Toward (purple) and Away (orange) locations locked to saccade onset (dashed vertical line). (Bottom) Presaccadic modulation of hit and false alarm rates locked to saccade onset (Δ = Toward–Away). Solid line: Mean values across participants, shaded error bars: SEM. Shaded gray zone: saccadic suppression epoch. Red horizontal line: cluster of significant differences. Other conventions are the same as in Fig 1E. (C) Criterion (top) and sensitivity (bottom) for orientation change detection reports at the Saccade Toward and Saccade Away locations, for trials with change onset Fig 1E. (D) Same as in panel C, but showing criterion and sensitivity for trials with blank onset (E) Same as in panel C, but showing criterion and sensitivity for trials with change offset (F) Psychometric function of sensitivity at the Saccade Toward and Saccade Away locations for orientation change detection and localization with multiple change angles (10°, 25°, 40°, and 55°). Error bars: SEM (n = 5 participants). (G) Same as in Fig 1I, but showing temporal dynamics of difference in sensitivity at the Saccade Toward and Away locations for the contrast change detection task. (H) Same as in Fig 1J, but showing temporal dynamics of difference in criterion at the Saccade Toward and Away locations for the contrast change detection task. Data are available at https://dx.doi.org/10.6084/m9.figshare.21792002. (TIF)</p