Adaptation is the process that changes a neuron’s response based on recent inputs. In the traditional model, a neuron’s state of adaptation depends on the recent input to that neuron alone, whereas in a recently introduced model (Hebbian normalization), adaptation depends on the structure of neural correlated firing. In particular, increased response products between pairs of neurons leads to increased mutual suppression. We test a psychophysical prediction of this model: adaptation should depend on 2nd-order statistics of input stimuli. That is, if two stimuli excite two distinct sub-populations of neurons, then presenting those stimuli simultaneously during adaptation should strengthen mutual suppression between those subpopulations. We confirm this prediction in two experiments. In the first, pairing two gratings synchronously during adaptation (i.e., a plaid) rather than asynchronously (interleaving the two gratings in time) leads to increased effectiveness of one pattern for masking the other. In the second, pairing the gratings in a center-surround configuration results in reduced apparent contrast for the central grating when paired with the same surround (as compared with a condition in which the central grating appears with a different surround at test than during adaptation). These results are consistent with the prediction that an increase in response covariance leads to greater mutual suppression between neurons. This effect is detectable both at threshold (masking) and well above threshold (apparent contrast).
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