Population analyses to investigate stimulus specificity. a) Dissimilarity matrices of firing rate vectors across trials. The distance between firing rate vectors was computed using Euclidean distances. For visualization purposes, the diagonal shows the maximum value. StGr: Stationary grating (classical condition). DrGr: Drifting grating (classical condition). StGcGr indicates a gray-center/gratings surround with a stationary grating (i.e. patch condition). b) Mean distances between protocols based on dissimilarity matrices. Black lines show the (i.e., SEM), where n is the number of samples (i.e., distances). St-GcSt indicates the distance between stationary grating (classical) and gray-center/stationary-grating (patch) conditions. For gratings with a circular gray patch during early periods, only (St-GcSt, St-GcDr) were not distinguishable (p-val equals 0.396). For late periods, all the distances were statistically distinguishable. For Gratings with rectangular patch during early periods, (St-GcSt, Dr-GcSt), (St-GcSt, Dr-GcDr), and (Dr-GcSt, Dr-GcDr) were not significant distinguishable (p-values equal to 0.4585, 0.9402, 0.9478, respectively). For late periods, all the comparison yielded significance. Finally, for B&W, all the comparisons were statistically significant except for the distances between (BcGs-GcWs, GcBs-GcWs) (p-val = 0.0247) for early periods. For late periods, the comparisons (BcGs-GcBs, BcGs-WcGs) and (GcBs-GcWs, GcBs-WcGs) were not significantly distinct (p-values 0.0338 and 0.0308, respectively). c) 2D t-SNE embedding based on dissimilarity matrices shown in a). d) Support Vector Classifier (SVC) based on matrices in a). Classification score across 20 repetitions. 40% of trials were used for training and 60% for testing.