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Kingsbury, L.

Publications and source records attributed to Kingsbury, L..

2 recordsLinked to original sources

Context-specific configuration of orthogonal integrator dynamics for flexible foraging decisions

The capacity to adapt behavior and cognition across contexts is fundamental to intelligence. Context-dependent decision making is an exemplar of flexible cognition in animals, yet its biological basis remains poorly understood. At the neural level, a critical mechanistic question is whether context largely alters the inputs to a common decision process or reconfigures decision activity itself to create context-specific functional modes. To study this problem, we developed a patch foraging task in which mice forage in two environment contexts defined by distinct reward dynamics. Mice made patch leaving decisions across environments using different context-specific parameterizations of a drift-diffusion integrator process. Using high-density acute and chronic neural recordings, we find that foraging environments recruit separate activity subspaces which organize orthogonal coding of context-specific decision variables. Unlike the context-invariant decision coding used for perceptual choice problems, foraging decision variables were encoded in orthogonal population vectors within largely separate neural subpopulations - a subspace configuration mechanism which can support modular learning, independent readout, and flexible toggling of decision strategies across environments. In the dorsal frontal cortex, orthogonal integrators emerge with experience, are preserved across three distinct task settings, and are required for rapid and volitional strategy switching. Our findings establish orthogonal integrator dynamics as a general solution for context-dependent decision making and open a new avenue to investigate the cell- and circuit-level basis of flexible cognition in the mammalian brain.

neuroscience↗

Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics

Patch foraging presents a ubiquitous decision-making process in which animals decide when to abandon a resource patch of diminishing value to pursue an alternative. We developed a virtual foraging task in which mouse behavior varied systematically with patch value. Mouse behavior could be explained by a model integrating time and rewards antagonistically, scaled by a latent patience state. The model accounted for deviations from predictions of optimal foraging theory. Neural recordings throughout frontal areas revealed encoding of decision variables from the integrator model, most robustly in frontal cortex. Regression modeling followed by unsupervised clustering identified a subset of ramping neurons. These neurons firing rates ramped up gradually (up to tens of seconds), were inhibited by rewards, and were better described as a continuous ramp than a discrete stepping process. Together, these results identify integration via frontal cortex ramping dynamics as a candidate mechanism for solving patch foraging problems.

neuroscience↗