## 2 Materials and Methods
### Model Simulations
#### 2.1.4 Local Manipulation Modeling  
Building upon prior modeling studies [38; 40; 61], we simulated local network alterations by reducing the excitability of selected nodes. This silencing was achieved by hyperpolarizing the manipulated nodes (Figure 1c) to an extent which completely suppresses their firing activity (mean firing rate = 0). To achieve this, we abolished the excitatory nonspecific input (ane = 0) and increased the nonspecific inhibitory input (ani = 0.6). We implemented the different manipulations in one hemisphere (the right hemisphere) to simulate an affected hemisphere and an intact one (left hemisphere). Consistent with empirical studies [27], we stimulated the affected hemisphere to assess cortical reactivity following perturbation near the silenced node.  
In line with previous work where 5% of the nodes were lesioned [39], in our study each manipulation involved approximately 4% of the connectome nodes (three nodes). As in [39], each local manipulation was defined by first choosing a central node (center of the manipulation) to be silenced and then selecting the remaining nodes to silence based on a geometrical distance criterion (Euclidean distance) from the central node. Manipulation details are reported in Table 2. Whenever the stimulated and manipulated nodes overlap, the latter were replaced with the closest non-manipulated nodes to the center of the manipulation. For instance, when stimulating rPCip, which was also part of local manipulation 1 (L1), we spared rPCip and silenced the next closest node (rV2). For a fair comparison across conditions between spontaneous and evoked metrics, non-identical manipulations were excluded whenever a correlation was performed (e.g., in Table S4 in Supplementary Material).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Local Manipulation Label** & **Nodes** & **Ranking (MFR\({}_{\mathbf{A}}\))** \\ \hline L1 & **PCip, PCs,** PCm & 10 \\ \hline L2 & **PFCcl, PFCdl,** PMCvl & 7 \\ \hline L3 & **TCc,** TCs,** TGi & 4 \\ \hline L4 & **V2,** V1, CCr & 18 \\ \hline L5 & **CCs, PFCorb,** Amyg & 19 \\ \hline L6 & **CCa,** CCp,** CCr & 13 \\ \hline L7 & M1, S1, PMCdl & 5 \\ \hline L8 & **PCm, PCip,** CCp & 15 \\ \hline L9 & **PFCdm,** CCa,** PFCm & 11 \\ \hline L10 & A1, A2, **S2** & 16 \\ \hline L11 & Amyg, PHC,CCs & 17 \\ \hline L12 & HC, PHC, TCv & 2 \\ \hline L13 & **PFCpol,** PFCm, PFCdm & 9 \\ \hline L14 & PFCvl, G, PMCvl & 8 \\ \hline L15 & TCpol, Amyg, **PFCorb** & 20 \\ \hline L16 & **CCa,** PFCdm, **PFCdl** & 12 \\ \hline L17 & IP, TCs, **S2** & 14 \\ \hline L18 & S1, M1, **PCs** & 3 \\ \hline L19 & **PFCdl,** CCA, **PFCcl** & 6 \\ \hline L20 & TCv, PHC, TGi & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: **Local manipulation labels in the Dconn connectome.** The labels of the local manipulations and the corresponding nodes silenced in the Dconn connectome. The ranking is based on the MFR difference (from lowest to highest). Note that when a stimulus overlaps with a silenced node (in bold), the latter is replaced by a nearby node.  
This procedure resulted in a total of 12 control conditions (stimulations without any node manipulation) and 240 manipulation conditions (silencing of 20 different nodes for each stimulation, 12 \(\times\) 20).