A general decoding strategy explains the relationship between behavior and correlated variability

Increases in perceptual performance correspond to decreases in the correlated variability of sensory neuron responses. No sensory information decoding mechanism has yet explained this relationship. We hypothesize that when observers must respond to a stimulus change of any magnitude, decoders prioritize generality: a single set of neuronal weights to decode any stimulus response. Our mechanistic circuit model supports that a general decoding strategy explains the inverse relationship between perceptual performance and V4 correlated variability observed in two rhesus monkeys performing a visual attention task. Further, based on the recorded V4 population responses, a monkey’s decoding mechanism was more closely matched the more broad the range of stimulus changes used to compute a sensory information decoder. These results support that observers use a general sensory information decoding strategy based on a single set of decoding weights, capable of decoding neuronal responses to the wide variety of stimuli encountered in natural vision.

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