Code:
Functions used to analyze data using matlab. Descriptions of which variables constitute input/output are provided in the codes themselves. The main purpose of each code is described here. 

fit_gauss_func_Open:
Function used to fit a Gaussian curve to average probe trial response rate during probe trials. The primary data of interest are the peak times for each rat (first output for the output vector called basicstats).

BF_Open:
Function that computes bayes factors using an empirically-motivated prior for the alternative hypothesis that a peak-time shift occurred from training to testing. For example, in the 8-to-8 group of experiment 1, we wanted to assess evidence in favor of the null hypothesis that peak times did not change from training to test. To evaluate this, we used the percent change in peak times from training to test in the 8-to-8 group. The null prior (i.e., no change hypothesis) was constructed by linearly shifting these values to have a mean of zero. We compared this null hypothesis to the alternative hypothesis that the peak times shifted to the same degree as that seen in the 8-to-4 group. Therefore, we constructed an alternative prior using percent change in peak times in the 8-to-4 group. The test essentially outputs a bayes factor in favor of the null hypothesis (no-change) over the alternative hypothesis (8-to-8 peak times shifted equivalently to that seen in the 8-to-4 group). 

Incremental prior Bayesian analysis:
We also apply a similar approach to the code in BF_Open, yet using a flat or incremental alternative prior. This is credited to Randy Gallistel and can be found at http://ruccs.rutgers.edu/gallistel. This approach evaluates evidence in favor of the null hypothesis that no change in peak times occurred over the alternative hypothesis that a non-specified shift in peak times occurred (be it leftward or rightward)

