(a) Diagram illustrating sequence magnitude quantification. (b) Traces show the average response evoked by the sequence ABCD on day 1 (Baseline, gray) and after training (Day 5, blue) in the experimental group from Fig. 1c. (c) There is a significant effect of training (2–way RM ANOVA, P<0.001) and each sequence element, plotted individually, increases relative to baseline (P<0.001 for A,B and C, P<0.05 for D). (d) Training also has a significant effect on response latency (defined as the interval between stimulus onset and maximal negativity, 2–way RM ANOVA, P<0.001) and there is a decrease in response latency for each element (P<0.001). (e) Plots showing the power spectral density (PSD, estimated using Welch's method, transparent shading shows 95% confidence intervals around means indicated by solid lines) averaged across all animals in each group from Fig. 1c–d (Exp. n=6, Ctrl. n=4) during periods of active stimulus viewing (ABCD, DCBA, and ABCD 300 ) or during inter–stimulus gray screen periods (Gray). (f) To highlight difference between groups, spectral power is plotted as a percent of the average ABCD power at each frequency. In both experimental and scrambled control groups visual stimuli drive higher spectral powers than gray screen at frequencies up to approximately 100 Hz. In the experimental mice, spectral power is on average higher while viewing ABCD than DCBA at low frequencies but this relationship reverses in the high gamma range (note, data was recorded with a 60 Hz notch filter). In control mice the familiar and novel sequence spectrums overlap at both high and low frequencies. In both groups, sequences presented with familiar timing result in more spectral power than a sequence presented with novel timing. Although precise interpretation is difficult, these results are broadly consistent with the idea that familiar and novel sequence either elicit or are modulated by different attentional states.