As there is no agreed upon approach, we provide a small manyverse of approximations of extinction learning rates. We subtracted (1) the last extinction trial from the first extinction trial (i.e., for CS discrimination during the first and last trial, for CS+ and for CS−, respectively; LR EXT 1, columns 1–3), (2) the last two extinction trials from the first two extinction trials (LR EXT 2, columns 4–6), (3) the last quarter of trials from the first quarter of trials (i.e., four trials; LR EXT 4, columns 7–9), and (4) the last half from the first half of trials (i.e., seven trials; LR EXT H, columns 10–12). We acknowledge that learning rates have been inferred through different approaches in the literature (see e.g.,
Ney et al., 2020;
Ney et al., 2022) and are often calculated from model-based approaches such as Rescorla Wagner Model (
Seel, 2012) and hence our operationalizations are only four out of multiple equally justifiable options. Colored cells indicate statistical significance of standardized betas, non-colored cells indicate non-significance. Standardized betas are color coded for their direction and magnitude showing positive values from yellow to red and negative values from light blue to dark blue. Darker colors indicate higher betas. AVE = average, LOG = log-transformed data, LOG.RC = log-transformed and range corrected data, not ordinal = not ordinally ranked data, ordinal = ordinally ranked data.