Dynamic Coding for Cognitive Control in Prefrontal Cortex

Cognitive flexibility is fundamental to adaptive intelligent behavior. Prefrontal cortex has long been associated with flexible cognitive function, but the neurophysiological principles that enable prefrontal cells to adapt their response properties according to context-dependent rules remain poorly understood. Here, we use time-resolved population-level neural pattern analyses to explore how context is encoded and maintained in primate prefrontal cortex and used in flexible decision making. We show that an instruction cue triggers a rapid series of state transitions before settling into a stable low-activity state. The postcue state is differentially tuned according to the current task-relevant rule. During decision making, the response to a choice stimulus is characterized by an initial stimulus-specific population response but evolves to different final decision-related states depending on the current rule. These results demonstrate how neural tuning profiles in prefrontal cortex adapt to accommodate changes in behavioral context. Highly flexible tuning could be mediated via short-term synaptic plasticity. ► Task instruction triggers a dynamic trajectory in a population of prefrontal neurons ► Task rules are maintained in a stable low-activity state that differentiates context ► The prefrontal network is temporarily tuned by the cue for flexible decision making ► Population dynamics are flexibly routed through state space for adaptive behavior Stokes et al. use dynamic pattern analysis to characterize how prefrontal cortex establishes, maintains, and uses flexible neural states for task-dependent behavior. Changes in decision rule trigger a dynamic population response that temporarily configures the network for flexible decision making.