At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters
Fig 4
Filter construction is sensitive to various parameters.
As previously, filters used are τ1 = 10ms (blue), τ2 = 100ms (green) and τ3 = 500ms (red). Default inhibitory time constant: τw = 50ms. Goodness of fit (R2) (A1,B1,C1) and Lyapunov exponent (A2,B2,C2) are compared to a control shown as light solid lines in all subplots. A: Effect of additive white noise (n = 0.01) in the network (dark lines). B: Effect of increased input variability (vin = 2) (dark solid lines) and increased variability of the inhibitory weight (vw = 2) (dotted lines). C: Effect of increased sparseness by reducing probability of connectivity to a = 0.04 for network size N = 1k (dotted lines) and N = 10k (dark solid lines). For a better comparison x-axis was normalized with the probability of connectivity a.