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.