The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our everyday visual environment. It remains unclear how V1 adapts to the highly volatile distributions of orientations found in natural images. We used naturalistic stimuli and measured the response of V1 neurons to orientation distributions of varying bandwidth. Although broad distributions decreased single neuron tuning, a neurally plausible decoder could robustly retrieve the orientations of stimuli from the population activity at all bandwidths. This decoder demonstrates that V1 population co-encodes orientation and its precision, enhancing population decoding performances compared to sole orientation decoding. This internal representation is mediated by temporally distinct neural dynamics and supports a precision-weighted description of neuronal message passing in the visual cortex, in line with predictive processing theories.
Interested in understanding how the precision of visual features may be encoded in the brain?— laurentperrinet (@laurentperrinet) November 8, 2021
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