Figure 3.

Illustrations of networks with different connectivity statistics. All networks contain N = 9 neurons with N_conn = 22 connections, so that the connection probability is $\widehat{p}\approx 0.3$. For each neuron, darker inner color indicates larger in-degree and darker outer color indicates larger out-degree. (A) Network with large convergence. There is large variance in in-degree. N_recip = 4, N_conv = 42, N_div = 23, and N_chain = 45 so that ${\widehat{\alpha }}_{\text{recip}}\approx 0.2$, ${\widehat{\alpha }}_{\text{conv}}\approx 0.8$, ${\widehat{\alpha }}_{\text{div}}\approx 0.0$, and ${\widehat{\alpha }}_{\text{chain}}\approx 0.0$. (B) Network with large divergence (the same network as in panel A, but with connections reversed). There is large variance in out-degree. N_recip = 4, N_conv = 23, N_div = 42, and N_chain = 45 so that ${\widehat{\alpha }}_{\text{receip}}\approx 0.2$, ${\widehat{\alpha }}_{\text{conv}}\approx 0.0$, ${\widehat{\alpha }}_{\text{div}}\approx 0.8$, and ${\widehat{\alpha }}_{\text{chain}}\approx 0.0$. (C) Network with few chains. Neurons with large in-degree tend to have small out-degree, and neurons with large out-degree tend to have small in-degree. N_recip = 2, N_conv = 33, N_div = 35, and N_chain = 29 so that ${\widehat{\alpha }}_{\text{receip}}\approx -0.4$, ${\widehat{\alpha }}_{\text{conv}}\approx 0.4$, ${\widehat{\alpha }}_{\text{div}}\approx 0.5$, and ${\widehat{\alpha }}_{\text{chain}}\approx -0.4$. (D) Network with many chains. Neurons with large in-degree tend to have large out-degree. N_recip = 6, N_conv = 33, N_div = 33, and N_chain = 65 so that ${\widehat{\alpha }}_{\text{receip}}\approx 0.8$, ${\widehat{\alpha }}_{\text{conv}}\approx 0.4$, ${\widehat{\alpha }}_{\text{div}}\approx 0.4$, and ${\widehat{\alpha }}_{\text{chain}}\approx 0.4$.