Figure 2From: Estimating Fisher discriminant error in a linear integrator model of neural population activityImpact of noise correlation on Fisher linear discriminant analysis. (A) Scenario where the tuning curves are the same for both populations of neurons, leading to \(r_{x} \rightarrow r_{y}\). Top left: illustration of tuning curves (black lines) and stimulus orientations (blue and red lines). Top right: example of numerical responses to two stimuli (red and blue circles), with noise correlation of 0.9. Bottom: solid line, analytical estimate. Filled black circles, numerical simulations. (B) Scenario where the tuning curves are offset by a fixed orientation. In this case, \(r_{x} \rightarrow \) -\(r_{y}\). (C) Symmetrical case arising when one of the populations (for instance, x) generates the same firing rate for a range of stimulus orientations, leading to \(r_{x} =0\). (D) Case where one population has higher gain, leading to \(\vert r_{x} \vert \neq \vert r_{y} \vert \)Back to article page