Opposing plasticity mechanisms in single neurons shape visual saliency assignment

To navigate complex environments, the visual system must prioritize unexpected inputs or omissions over predictable sensory backgrounds. This saliency assignment is a hallmark of visual processing and depends on comparing visual feedforward inputs with learned contextual surrounds, a process often conceptualized as a difference computation. However, cortical circuitry poses fundamental challenges: visual contextual feedback is predominantly amplifying, and feedback-driven inhibitory neurons necessary for subtractive computations are relatively sparse. How then can complex contextual feedback be selectively compared with feedforward input at the level of individual neurons? Here, we show that divergent plasticity rules within single pyramidal neurons provide a solution to this problem. Using two-photon calcium imaging, we recorded layer 2/3 pyramidal cell responses in mouse primary visual cortex before and after visual familiarization. We dissociated feedforward and contextual signals by comparing responses to stimuli with and without an occluded sector. Repeated feedforward responses selectively weakened through adaptation and surround suppression, whereas contextual responses strengthened and generalized across scenes. These strengthened contextual inputs amplified non-adapted responses to novel images and drove neuronal activity when occlusion of feedforward input prevented surround suppression. This produced a conserved structure of feedforward and contextual responses across mice, monkeys, and humans. Ultimately, these results reveal a cellular mechanism for saliency assignment that does not require feedback-driven inhibition. Pyramidal neurons autonomously learn the generalized statistical structure of familiar contexts, allowing them to selectively amplify improbable inputs or omissions.