Prefrontal cortex exhibits multidimensional dynamic encoding during decision-making

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Recent work has suggested that the prefrontal cortex (PFC) plays a key role in context-dependent perceptual decision-making. In this study, we addressed that role using a new method for identifying task-relevant dimensions of neural population activity. Specifically, we show that the PFC has a multidimensional code for context, decisions and both relevant and irrelevant sensory information. Moreover, these representations evolve in time, with an early linear accumulation phase followed by a phase with rotational dynamics. We identify the dimensions of neural activity associated with these phases and show that they do not arise from distinct populations but from a single population with broad tuning characteristics. Finally, we use model-based decod- ing to show that the transition from linear to rotational dynamics coincides with a plateau in decoding accuracy, revealing that rotational dynamics in the PFC preserve sensory choice information for the duration of the stimulus integration period.