Architecture of the brain’s visual system enhances network stability and performance through layers, delays, and feedback
Fig 5
Bifurcation boundaries for 2, 3, and 5 layers.
The region of the parameter space where the network is stable depends on the number of layers N, the type of feedforward transmission (B: biological with delay, A: artificial without delay), and the distance of the feedback (see Eqs (7) and (8)). For the networks presented in the lower panels (a) N = 2, (b) N = 3, (c) N = 5, we see that the stability region for the biological case is larger or equal than for the artificial case. This is a repeating behavior for different N. Notation: (a) wi = α11 = α22, wp = α12α21. (b) wi = α11 = α22 = α33, wp = α12α21 = α23α32 and α31 = 0. (c) wshort = α23α32 = α34α43 = α45α54, wlong = α23α34α45α52. Note that in all cases, the red and blue curves intersect at the axes (wi = 0, wp = 0, wshort = 0 or wlong = 0). This is a consequence of the discussion presented in Section 3.2.