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Abstract During visually guided behavior, the prefrontal cortex plays a pivotal role in mapping sensory inputs onto appropriate motor plans. When the sensory input is ambiguous, this involves deliberation. It is not known whether the deliberation is implemented as a competition between possible stimulus interpretations or between possible motor plans. Here we study neural population activity in the prefrontal cortex of macaque monkeys trained to flexibly report perceptual judgments of ambiguous visual stimuli. We find that the population activity initially represents the formation of a perceptual choice before transitioning into the representation of the motor plan. Stimulus strength and prior expectations both bear on the formation of the perceptual choice, but not on the formation of the action plan. These results suggest that prefrontal circuits involved in action selection are also used for the deliberation of abstract propositions divorced from a specific motor plan, thus providing a crucial mechanism for abstract reasoning. 

Sub-additivity and variability are ubiquitous response motifs in primary visual cortex (V1). Response sub-additivity provides a sign of the brain processes that enable us to construct useful interpretations of the visual environment (i.e., nonlinear input transformations), while response variability provides a sign of the brain processes that limit the precision with which we can do this (i.e., neural information loss). Historically, these two motifs have been studied independently of each other. Yet, there is increasing evidence that experimen- tal manipulations that elicit response sub-additivity often also quench response variability. Here we provide a unifying review of these phenomena, suggesting that response sub-additivity and variability quenching may have a common origin. We review empirical findings as well as recent model-based insights into the functional operations, computational objectives, and circuit mechanisms underlying V1 activity. Although these model- ing approaches address different aspects of cortical activity, they all predict that response sub-additivity and variability quenching will often co-occur. Response sub-additivity and variability quenching are not limited to V1 but are widespread cortical phenomena. Many of the insights we review generalize to other cortical areas, suggesting that the connection between response sub-additivity and variability quenching may be a canonical motif across cortex. 

To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer’s continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.