Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain
Fig 9
Functional Connectivity and Coherence Analysis of Experimental v.s. Model data.
Coherence analysis was performed on all data sets according to the procedure described in Coherence analysis. A) The parcel-to-parcel coherence matrices are first averaged in the slow wave frequency band and scaled by parcel-to-parcel distances to determine functional connectivity via percent of connected parcels and number of communities (determined by Louvain community detection). B) Full (unaveraged, unscaled) coherence matrices are then fitted with an exponential function to determine the full shape of the coherence landscape across distance and frequency. The resultant first (0.5 Hz) Lambda and mean Alpha in the slow wave frequency range (<2 Hz) are taken to describe the shape of the coherence landscape, and plotted in (B). (A.1 and B.1) show zoom-ins of each respective plot; the labels show the radius and factor of strength reduction—e.g., 10/5 indicates a model where connections longer than 10 mm are reduced by a factor of 5. This shows that the models with primarily mixed slow waves are the closest fit to experimental results across all 4 metrics. Full 3D coherence plots across distance and frequency are shown for the experimental data (C), the 10mm / 5 model (D), and the global slow wave base model (E), showing that the global slow wave model has a fundamentally different shape (lacking a dependence of coherence on distance) and much higher levels of coherence at low frequencies.