Figure 4.

Relating spontaneous activity in darkness to sampling from the prior, based on the encoding of brightness in the primary visual cortex. (a) A statistically more efficient toy model of the early visual system [47,99] (Figure 3b). An additional feature variable, b, has a multiplicative effect on other features, effectively corresponding to the overall luminance. Explaining away this information removes redundant correlations thus improving statistical efficiency. (b–c) Probabilistic inference in such a model results in a luminance-invariant behavior of the other features, as observed neurally [100] as well as perceptually [101]: when the same image is presented at different global luminance levels (left), this difference is captured by the posterior distribution of the “brightness” variable, b (center), whereas the posterior for other features, such as y₁ and y₂, remains relatively unaffected (right). (d) In the limit of total darkness (left), the same luminance-invariant mechanism results in the posterior over y₁ and y₂ collapsing to the prior (right). In this case, the inferred brightness, b, is zero (center) and as b explains all of the image content, there is no constraint left for the other feature variables, y₁ and y₂ (the identity in a becomes 0 = 0 (y₁·w₁ + y₂·w₂), which is fulfilled for every value of y₁ and y₂).