Perceptual inference predicts contextual modulations of sensory responses.

Sensory receptive fields (RFs) vary as a function of stimulus properties and measurement methods. Previous stimuli or surrounding stimuli facilitate, suppress, or change the selectivity of sensory neurons' responses. Here, we propose that these spatiotemporal contextual dependencies are signatures of efficient perceptual inference and can be explained by a single neural mechanism, input targeted divisive inhibition. To respond both selectively and reliably, sensory neurons should behave as active predictors rather than passive filters. In particular, they should remove input they can predict ("explain away") from the synaptic inputs to all other neurons. This implies that RFs are constantly and dynamically reshaped by the spatial and temporal context, while the true selectivity of sensory neurons resides in their "predictive field." This approach motivates a reinvestigation of sensory representations and particularly the role and specificity of surround suppression and adaptation in sensory areas.