The predictive value of the normalized connectome for the functional in-strength is further validated through comparisons with numerical simulations of the Stuart-Landau model. This model is often used to describe mesoscopic neuronal activity (Courtiol et al., 2020; Deco et al., 2017; Deco & Kringelbach, 2020; Petkoski & Jirsa, 2019) because it encompasses the working points of population rate models (Deco, Jirsa, McIntosh, Sporns, & Kötter, 2009). Correlating the spatial activation patterns with the predictions from the spectral in-strength and capacity shows that the normalized metrics capture the dynamics of the model better than using only the weights. This is besides the derivations being made on the Kuramoto model that does not contain amplitude dynamics, and that assumes difference instead of additive coupling. Better performance of the wave coupling is consistent across the frequencies, and holds for different working points, such as sub- and supercritical, with or without added noise.
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