Extended Data Fig. 6: Dimension and noise contributions to local decorrelation performance.

a, b: Dimension (a) and noise (b) contributions to the performance shown in Fig. 8b, using the same parameters. c, d: Dimension (c) and noise (d) contributions to the performance shown in Fig. 8c, using the same parameters. e-g: Dimension (e) and noise (f) contributions to the performance (g), for the antennal lobe architecture, as a function of the in-degree of Kenyon cells K. Input was generated using a clustered representation. The green dashed line indicates the value obtained with optimal compression. The parameters were chosen to be consistent with the insect olfactory system anatomy, that is D = Nc = 50, N = 1000, M = 2000, p = 1, f = 0.1, σ = 1, P = 100. Note that when K ≥ 8, the local decorrelation strategy requires more synapses than the optimal compression one, for which K = 7 and L = 20. h, i: Dimension (h) and noise (i) contributions to the performance shown in Fig. 8d, using the same parameters. For all panels, the shaded areas indicate the standard deviation across network realizations.