Psychometric functions
We used the results from the flash-fusion task to create a psychometric function for each participant, using the Palamedes toolbox (Prins, N. & Kingdom, F.A.A., 2018) for MATLAB (The Mathworks Inc., 2022). Following the methods used in Samaha & Postle (2015), we employed a logistic function with four parameters: “guess rate,” “threshold,” “slope” and “lapse rate” to estimate the correct response rate for the different stimulus conditions. Guess rate was fixed at 0.5. The other three parameters were estimated for each participant. Lapse rate was set to the limits of 0 – 0.06. We used goodness-of-fit testing to compare the deviance of the fit to the real data with deviance of the fit to 1,000 simulated datasets for each participant. No participant’s fit exceeded the 95th percentile, indicating that all created psychometric functions fell within the expected range for the type of data and no function was deemed an outlier.