Figure 7: The loss of model-human similarity due to energy constraints depends on local and global structural features.

(a-c) The model-human similarity for cross-attractor coordination (no energy constraint, black solid lines) is stable with respect to varying global coupling G and local excitatory connectivity w_EE and w_EI (a: w_EE = 0.7 and w_EI = 0.35, b: w_EE = 2 and w_EI = 1, c: w_EE = 2.8 and w_EI = 1). Dashed lines indicate the model-human similarity when the model is energy-constrained, i.e., it does not cross the maximum energy gap between attractors. This “energy-constrained” similarity is computed by splitting the attractor repertoire into two subrepertoires, one above the maximum energy gap and one below it (c.f. Figure 6a). The cross-attractor coordination within each subrepertoire is compared to the human functional connectivity through Spearman’s correlation. The dashed lines indicate the greater correlation coefficient (ρ) among the two subrepertoires. The shaded area (Δρ) indicates the loss of model-human similarity due to the energy constraint. (d) Each point in the scatter plot represents the percent loss of model-human similarity for not crossing the maximum energy gap, given a specific combination of global coupling G and local connectivity w_EE and w_EI. Overall, the loss increases with the maximum gap size, which in turn depends on G (Figure 6b). The average loss (bars in d) decreases with increasing local excitatory connectivity (w_EE, w_EI). When the cross-attractor model was fitted to individual subjects (using n=100 unrelated HCP participants; c.f. Figure 5e), the optimal global connectivity G (e) and the corresponding maximum energy gap (f) and mean energy gap (g) are low, where the cross-attractor coordination is least affected by energy constraints. (*** p<0.001 with Bonferroni correction. Error bars are standard errors.)