Spatial and temporal correlations in human cortex are inherently linked and predicted by functional hierarchy, vigilance state as well as antiepileptic drug load
Fig 4
STC in a neural network model.
Model simulations are shown for N = 1600 neurons on a 2-dimensional grid with periodic boundary conditions and distance-dependent connectivity strength. Other parameters are finh = fexc = λ = 1, if not stated otherwise. One neuron was activated randomly every maxt = 2000 time steps. Coloured bars give the ensemble average with whiskers extending to the 95% confidence interval. Results for surrogate data (shuffled time series) are given as grey bars. A, B The state of high AED can be mimicked in the model by decreasing the excitability of excitatory neurons, i.e., fexc = 1→0.95, leading to decreased SC, TC. C Co-variation between TC and SC for different model realizations with λ∈{0.7, 0.75, 0.8, 0.85, 0.9, 0.95, 1.0} (104 runs each, 7·104 runs in total, Spearman ρ = 0.79, p<m.p. (machine precision)). The black line shows a logarithmic fit. D No correlations are found in time-shuffled data. E, F SC and TC increase with the absolute value of the largest eigenvalue λ approaching its critical value of λ = 1 similar to the hierarchical increase of TC in iEEG data (Fig 3).