CTN: Mehrdad Jazayeri

Title: Adaptive problem solving in the primate frontal cortex

Abstract: Humans excel at solving problems adaptively. When missing the bus to an appointment, for instance, we might wait for the next one, call a taxi, cancel, or reschedule, depending on the situation. This ability to assess context and choose a suitable strategy is central to intelligence, yet its neural and computational foundations remain poorly understood. To address this gap, we trained monkeys on a challenging decision-making task that could be solved using multiple strategies, providing a controlled setting to study strategic flexibility. Behaviorally, the animals performed accurately and generalized to new conditions, but their choices were inconsistent with any single policy, suggesting the use of internally generated strategies. Large-scale electrophysiological recordings from the dorsomedial frontal cortex revealed that population activity unfolded along distinct neural trajectories corresponding to different strategies. The structure of these trajectories—set by the organization of initial neural states and their subsequent evolution—showed that animals assessed the problem and engaged distinct, rationally structured computational algorithms. A latent behavioral model grounded in these neural dynamics predicted the animals’ choices more accurately than any fixed-strategy model, providing a direct link between cortical population activity and adaptive decision-making. Together, these findings reveal a neurophysiological mechanism for strategic decision-making and offer a mechanistic understanding of the neural basis of adaptive problem solving.