Attention Cueing in Rivalry: Insights from Pupillometry

The dataset holds a Matlab structure m, described as follows, with all the data published in Acquafredda et al., eNeuro 2022.

m = structure containing average data for generating the analyses and figures reported in the manuscript. It contains separate fields for the different conditions where the variables below were measured: main and control experiments; three stimulus types simulation, binocular rivalry (BINriv) and interocular grouping rivalry (IOGriv) and three cueing conditions no cue, att2dark (dark stimulus was cued) and att2bright (bright stimulus was cued). For the control experiments values are reported for four contrast conditions (instead of cueing conditions): brigthcont0 brigthcont25 brigthcont50 brigthcont100 and brigthcont150 plus one cueing condition (att2brigth).

Each of these fields has subfields containing the information detailed below, coded with the format (N x M) with N = number of participants and M = 1 for most variables, or M = 801 corresponding to the timepoints where the pupil timecourse was measured. 

Variables reported in the structure:

time: [1x801 double] % time from -4 sec to +4 secs from a perceptual switch

pupil: [10x801 double] % timecourse of baseline-corrected pupil size 

pupilbin: [10x1 double] % average baseline-corrected pupil size in the [-0.5 1] s interval around the perceptual switch 

pupil_nobslcorr: [10x1 double] % average NON baseline-corrected pupil size in the [-0.5 1] s interval around the perceptual switch 

prop: [10x1 double] % proportion of time spent reporting one of the three possibile percepts (white, black, mixed).