The population signal predictive of choice and RT is approximately one-dimensional.
Two binary decoders were trained to predict the choice (What-decoder) and its time (When-decoder) using the population responses in each session. The When-decoder predicts whether a saccadic response to the contralateral target will occur in the next 150 ms, but critically, its accuracy is evaluated based on its ability to predict choice. a, Choice decoding accuracy plotted as a function of time from motion onset (left) and time to saccadic choice (right). Values are averages across sessions. The What-decoder is either trained at the time point at which it is evaluated (time-dependent decoder, orange) or at the single time point indicated by the red arrow (t = 450 ms after motion onset; fixed training-time decoder, red). Both training procedures achieve high levels of accuracy. The When-decoder is trained to capture the time of response only on trials terminating with a left (contraversive) choice. The coding direction identified by this approach nonetheless predicts choice (green) nearly as well as the fixed training-time What-decoder. The black trace shows the accuracy of a What-decoder trained on simulated signals using a drift-diffusion model that approximates the behavioral data in Fig. 1. Error bars signify s.e.m. across sessions. The gray bar shows the epoch depicted in the next panel. b, The heat map shows the accuracy of a decoder trained at times along the abscissa and tested at times along the ordinate. Time is relative to motion onset (gray shading in a). In addition to training at t = 450 ms, the decoder can be trained at any time from 300 < t < 500 ms (dashed box) and achieve the same level of accuracy when tested at any single test time. The orange and red traces in a correspond to the main diagonal (x = y) and the column marked by the red arrow, respectively. c, Trial-averaged activity rendered by the projection of the population responses along the When coding direction, SWhen. Same conventions as in Fig. 2. d, Cosine similarity of five coding directions. The heatmap shows the mean values across the sessions, arranged like the lower triangular portion of a correlation matrix. Cosine similarities are significantly greater than zero for all comparisons (all p < 0.001, t-test). e, Correlation of single-trial diffusion traces. The Pearson correlations are calculated from ordered pairs of , where Si(t) are the detrended signals rendered by coding directions, x and y, on trial i. The detrending removes trial-averaged means for each signed coherence, leaving only the diffusion component. Reported correlations are significantly greater than zero for all pairs of coding directions and sessions (all p < 10−23, t-test, see Methods). The variability in cosine similarity and within-trial correlation across sessions is portrayed in Fig. S8.