Urai AE, Braun A, Donner THD. (2017) Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nature Communications, 8: 14637.

This is the data to replicate all analyses from Urai AE, Braun A, Donner THD. (2017) Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nature Communications, 8: 14637.
See https://github.com/anne-urai/pupilUncertainty for the analysis code, including detailed instructions for replicating the figures from the manuscript.
You probably only want to use 2ifc_data_allsj.csv. Column names:
stim: generative stimulus identity, i.e. 'weaker' (-1) vs 'stronger' (+1)coherence: generative coherence difference from referenceNote: a column stim * coherence will get you the signed motion coherence, that is most useful for generating regular choice-based psychometric functions.difficulty: level of difficulty within the session; see 'Task and procedure' in the Methods section. motionstrength: the estimated motion energy in each generated video. Correlates highly with stim*coherence, as shown in Figure 2cresp: response of the subjectrt: reaction time, after offset of the second stimuluscorrect: feedback givencorrectM: feedback that should have been given, had the exact stimulus identity been based on the motion energy filtered values (rather than the generative values)trialnr within each blockblocknr within each sessionsessionnr within each sjsubjnr participant IDbaseline_pupil, decision_pupil, feedback_pupil, trialend_pupil, response_pupil: pupil dilation at various epochs during the trialint1motion, int2motion: filtered motion energy values during the reference and test interval. Their difference generates the motionstrength column.rtNorm: z-score(log(rt))

correctM: