Units were sorted offline via Offline Sorter Version 3.3 software (Plexon) using a template-matching algorithm and analyzed using Neuroexplorer Version 4 software (Plexon) and Matlab (Mathworks; 2018b). Activity was examined during two response epochs: during the period of time following presentation of the first cue light until port exit and the period of time following presentation of the second cue light until well entry (stop-change trials only). Activity in the population histograms was normalized by dividing by the maximal firing rate of each neuron; however, statistical procedures were conducted using raw firing rates. Unless otherwise specified, behavioral data were analyzed using a two-way ANOVA where each data point represents a session average. To capture activity that differentiated based on a previous trial, we examined firing rates on GO and STOP trials that followed either a GO or STOP trial. This analysis allows for the examination of sequence effects as well as comparisons between trials that were not preceded by a need to adapt behavior (i.e., when a STOP follows a GO) versus trials that were preceded by a need to
