temporal correlations in reaction time data

during a long experiment, there can be different sources of variability. for example, the participant can get sleepy, which influences measures like reaction times on a slower timescale. these slow drifts can then mask differences between experimental conditions. pic.twitter.com/kGiK78Yf02

behavioral and neuronal measures acquired over the course of an experiment display fluctuations on fast as well as slow scales. if one computes a correlation between two _independent_ sets of such measurements, very likely strong spurious correlations will be seen. pic.twitter.com/C2muytZDhF