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Figure 2 | The Journal of Mathematical Neuroscience

Figure 2

From: Estimating Fisher discriminant error in a linear integrator model of neural population activity

Figure 2

Impact 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 \(\vert r_{x} \vert \neq \vert r_{y} \vert \)

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