Flaws in Data Binning for Population Receptive Field Analyses

Abstract

AbstractData binning can cope with overplotting and noise, making it a versatile tool for comparing many observations. However, it goes awry if the same observations are used for binning and contrasting. This creates an inherent circularity, leaving noise and regression to the mean insufficiently controlled. Here, we use population receptive field analyses – where data binning is commonplace – as an example to expose this flaw through simulations and empirical repeat data.