The code in this repository accompanies the following publication:

Mihali, A, Young, AG, Adler, L, Halassa, MM, Ma, WJ. A low-level perceptual correlate of behavioral and clinical deficits in ADHD. 2018, Computational Psychiatry

The experiment code yields '.mat' files containing 'data', 'settings' and the Psybayes output 'post' and 'outputs', which are processed with the script analysis_raw.m and combined into alldata.mat.

The last fields represent structs with all the trials in each of the 4 possible conditions (each itself a struct):

• cond_Ori
• cond_OriS
• cond_Col
• cond_ColS

• analysis_all_plots.m takes in alldata.mat and the psychometric curve parameters params_all.mat, calls the plotting functions from data_analysis_and_plots and return the figures in the manuscript.
• The psychometric curve parameters in params_all.mat are the output of psych_curves_pars_fit.m, loglike.m and function_psi.m from model_fitting. psych_curves_pars_fit.m uses a grid search to find the parameters that maximize the loglikelihood, which is computationally intensive, so it was run on the NYU HPC cluster. While Psybayes also estimated the psychometric curve parameters for each condition individually, this offline fitting was necessary since our main model assumed shared parameters across conditions.