Materials and Methods
Participants We tested 48 participants (29 Female, 19 Male, Age M=22.1, SD= 3.9, IQR = {19,23}) recruited by opportunity sampling at Bournemouth University. Participants received £5 for their time. The study was approved by the Research Ethics Committee of Bournemouth University and was carried out in accordance with the principles of the Declaration of Helsinki. Participant numbers could not be determined by standard power calculation. Similar eye-tracking tasks require 6 to 10 participants (e.g. Meso, Montagnini, Bell, & Masson, 2016; Meso, Gekas, Mamassian, & Masson, 2022), so trait inventory requirements determined numbers. Previous power estimates suggested 45 participants (Meso, De Vai, Mahabeer, & Hills, 2020), as did a recent reliability and replicability study on SPEM and traits (Schröder, Baumert, & Ettinger, 2021).
Stimulus and Materials
Stimuli were generated on a Windows 7 PC running bespoke Matlab (Mathworks) routines in Psychtoolbox (Brainard, 1997; Pelli, 1997). Presentation was on a Cambridge Research Systems 32’ Display++ Monitor with 1920 x 1080-pixel resolution and 100Hz refresh rate. The monitor was placed 80cm from participants. Eye movements were recorded from the right eye using an SR Eyelink Video eye tracker operating at 1000Hz with movement restricted by a head/chinrest. The stimulus was based on Meso et al., (2020), with sizes scaled to an on-screen virtual square with sides of 900pix containing the stimulus presentation area of 23.4 degrees of visual angle (°). The black ball had 0.21° diameter with motion characterised by Equations (1) to (4).
Vx(t ) = d ∙Sx (1)
Px(t ) = X0 +d ∙Sxt (2)
Vx in Equation (1) is the constant horizontal component of the speed with Sx set from {4, 16} °/s for fast/slow and direction d set from {-1,1} for left/right. The time-varying horizontal position Px in Equation (2) depended on Sx starting at the centre of the screen, X0.
Vy(t ) = Sy + ε +gt (3)
Py (t) = Y0 + (Sy + ε)t + (gt 2)/2 (4)
Vy in Equation (3) is the vertical speed component initiated as Sy = 2°/s and ε is a number from a flat continuous distribution of ± {0 to 0.5}°/s away from the direction of acceleration g , which is ±9.81°/s2 for the gravity (+) and antigravity (-) conditions. The position Py in Equation (4) incorporates the initial position at the centre of the screen Y0 and the integration of Equation (3) for position. The resulting motion is that expected for a ball just smaller than a professional soccer ball.
Procedure Participants were screened for normal or corrected-to-normal vision with a visual acuity letter chart. Bespoke Matlab programs were used for trait inventories with mouse clicks to record responses. The 74-item Schizotypal Personality Questionnaire – SPQ (Raine, 1991) and 24-item, 5-point Subthreshold Autism Trait Questionnaire – SATQ (Kanne, Wang, & Christ, 2012) were used. The tracking task was separated into three blocks of Gravity, Antigravity and Control. In the control condition, stimulus orientation was rotated by 90 degrees from the gravity condition so that vertical motion was defined by Equations (1) and (2) and horizontal by (3) and (4) and gravity acted rightwards. Each block had 160 trials of 1.25s duration with participant-initiated button presses to proceed. Trials started with a 500ms central dark grey fixation circle which disappeared at trial onset and the stimulus was followed by a grey screen. Participants were instructed to fixate on the central spot and track the ball as well as they could. Blocks contained 80 fast and 80 slow trials and lasted approximately 10 minutes. The task interleaved the inventories with the conditions fixed in the same order i.e. SPQ, gravity, SATQ, antigravity and control, with breaks in between so that it lasted about 40 minutes. Changes from the procedure of Meso et al., (2020), were that participants always started on the gravity condition, trials were shorter (1.25s not 2s), tasks included the control condition and we used a higher precision psychophysics screen, the CRS Display++.
Design and data analysis
We used a multivariate within-participants design. The Independent Variables were Gravity direction with three levels: Gravity (G) – downwards acceleration, Antigravity (AG) – upwards and Control (C) - rightwards; ball Speed with two levels: Slow (4°/s) and Fast (16°/s). The key measures were the two inventories: the SPQ and SATQ, RMSE (Root Mean Square Error between dynamic eye position and ball position), and Saccades (rates and sizes). We also recorded participant age and sex. Data pre-processing to extract the RMSE and Saccades is detailed in Meso et al., (2020). We reduced the RMSE responses to 25 samples, each covering a 20ms window from onset at 0ms to 500ms. RMSE was measured for the x-direction capturing responses to the motion component at aconstant speed for conditions G and AG, and for the y-direction capturing responses subject to acceleration due to simulated rightward gravity . We quantified learning as performance improvement during a block of 80 trials, by subtracting averaged RMSE value for the last 20 trials from that of the first 20 trials under the same speed condition. Learning was positive if there was improvement. We analysed the trait responses and a restricted subset of eye movement measures focusing on (i) the relationship between SPQ and SATQ, (ii) the relationship between the inventories and RMSE measures, (iii) the relationship between the inventories and the saccades, and (iv) dynamic changes in the relationships between both RMSE and saccades under the G and AG conditions. For each of the four, we ran correlations with alpha adjusted for the number of comparisons undertaken. (v) We also ran mean comparisons between gravity conditions for RMSE, Saccades and RMSE-learning. These were done using a Wilcoxon signed rank test because of the deviations from normality. Finally, we ran a correlation type Principal Components Analysis (Joliffe, 2002) to unpack the relationship between a restricted set of 21 measures. These variables were selected to cover sub-traits of the SPQ and SATQ, Saccade rates and amplitudes and RMSE measures, both at stimulus onset (0ms) and during the open loop of response (~160ms). Meaningful components were identified using parallels analysis of the variance (Joliffe and Cadima, 2016). For simplicity, we focused analysis on the slow speed condition which showed similar patterns to the faster condition but was an easier tracking task.