Figure 1. Example of PCA performed by Oja's rate-based plasticity rule.

(A) Theoretical cross-correlation matrix of 100 inputs induced by two Gaussian distributions of rates. Darker pixels indicate higher correlations. The circles indicate where the correlation for each source drops below 10% of its maximum (see the Gaussian profiles in D). (B) Traces of the weights modified by Oja's rule [26] in (1). At random times, the input rates follow either Gaussian rate profile corresponding to the green and blue curves in D; white noise is added at each timestep. (C) The asymptotic distribution of the weights (red) is close to the principal component of the matrix in A (black solid curve), but distinct from the second component (black dashed curve). (D) The final weight distribution (red) actually overlaps both Gaussian rate profiles in green dashed and blue dashed-dotted lines that induce correlation in the inputs. The green and blue curves correspond to the small and large circles in A, respectively.