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. 2021 Jul 22;12:4473. doi: 10.1038/s41467-021-24629-0

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Fig. 4 — a The encoding model predicts the spike count in a trial from the stimulus-driven response based on its disparity tuning curve and the disparities presented in that trial (left), the choice during that trial (middle), and a drift term to fit any non-stationarity in the recording over time (right). b The stimulus- or choice-driven patterns of neural activity across the recorded neurons can be represented as population vector, with each dimension corresponding to a given neuron’s stimulus- or choice-driven weight estimated from the encoding model. The patterns of activity can then be compared as an angle between the population vectors. c, d Results for populations in V2 and V3/V3a. Top: The population vectors for the relevant and irrelevant stimulus are well aligned across sessions. Middle: the population vectors for the choices when the stimulus was relevant or irrelevant are broadly aligned. Bottom: The angles between the population vectors for the relevant stimulus (v-stimr) and choice (v-choicer or v-choicei) are correlated (r = 0.86, p = 10⁻¹⁰, n = 37 sessions for V2; r = 0.51, p = 0.01, n = 23 sessions for V3/V3a, two-sided Spearman’s rank correlation; error bars are 90% confidence intervals around the median angle, by resampling).