Figure 7.

Conditional variance. A, Joint histogram of the linear responses of two neurons, R₁ and R₂, out of a population of 40 similar neurons. Brightness indicates the frequency of a particular pair of responses. B, Joint histogram of linear responses R₁ and R₂ after the introduction of a conditional-variance dependency between R₁ and R₂. C, Expected product of normalized responses N₁ and N₂ as a function of the slope of the conditional-variance dependence relationship (α = 0.75 corresponds to B). D, Conditional variance of R₂ as a function of R₁². Gray curve represents the independent neural responses shown in A; conditional variance was constant. Black curve represents the bowtie distribution shown in B; conditional variance increased with R₁². E, Conditional variance plotted as in D, but for normalized responses instead of linear responses. Gray curve represents independent neural responses (A). Black curve represents neural responses with a bowtie conditional-variance dependence (B). Dashed black curve corresponds to conditional variance following response-product homeostasis adaptation of normalization weights.