Figure 2.

Illustration of serial-order decoding analysis. A, Each trial consisted of six produced intertap intervals (colored bars S1–C3) per duration. Monkeys performed five trials in each set. B, To decode serial order during the intertap interval, we divided each interval into equally spaced bins and collected observations at each bin across six intervals and five trials. Thus, at each bin, we obtained 30 observations. We used the patterns of activity of 352 cells to decode the serial order of each of the 30 observations. On each iteration of the decoding, we trained the decoder at one bin and used the resulting classification functions to decode serial order at all bins. We repeated this process using each bin as the training bin, providing one decoding time course for every bin. The proportion of observations correctly classified at each bin is an indication of how reliably patterns of activity across the population vary as a function of serial order. C, By training the decoder at a particular bin (dashed lines) and classifying at all other bins (solid lines), we were able to test whether the representation of serial order was static over time or dynamic. If patterns of neural activity that represent different serial orders remain the same across the intertap interval (Static representation, top), decoding accuracy should be consistent across all bins, no matter which bin was used to train the decoder. If serial order was represented by different patterns of activity at different times (Dynamic representation, bottom), then decoding should be highest at bins nearest the training bin.