Effect of tumor resection on the characteristics of functional brain networks

Brain functioning such as cognitive performance depends on the functional interactions between brain areas, namely, the functional brain networks. The functional brain networks of a group of patients with brain tumors are measured before and after tumor resection. In this work, we perform a weighted network analysis to understand the effect of neurosurgery on the characteristics of functional brain networks. Statistically significant changes in network features have been discovered in the beta (13–30 Hz) band after neurosurgery: the link weight correlation around nodes and within triangles increases which implies improvement in local efficiency of information transfer and robustness; the clustering of high link weights in a subgraph becomes stronger, which enhances the global transport capability; and the decrease in the synchronization or virus spreading threshold, revealed by the increase in the largest eigenvalue of the adjacency matrix, which suggests again the improvement of information dissemination.

Figure 1

(Color online) The pdf of a link weight in the brain functional networks measured before (empty markers) and after (solid markers) neurosurgery.

Figure 2

(Color online) The pdf of node strength in MEG before (red crosses) and after (blue circles) neurosurgery.

Figure 3

(Color online) Correlation between $\left(s_i+s_j\right)/2\left(N-1\right)$ and $w_{ij}$ of the brain function networks before (red crosses) and after (blue circles) neurosurgery.

Figure 4

(Color online) The spectra of one brain functional network and of the ${10}^4$ weight-reshuffled networks.

Figure 5

(Color online) The spectra (in the range around zero) of the brain function networks measured via MEG before (red crosses) and after (blue circles) tumor resection.

Figure 6

(Color online) The scatter plot of link weight correlation around a node ${\Sigma }_r$ versus the largest eigenvalue ${\lambda }_1$ of each of the networks measured before and after tumor resection.

Figure 7

(Color online) The scatter plot of rank dominance $RD$ versus the largest eigenvalue ${\lambda }_1$ of each of the networks measured before and after tumor resection.

Figure 8

(Color online) The degree distribution of the unweighted brain functional networks before (red crosses) and after surgery (blue circles) as well as the Gaussian curve fitting (black dotted line).

Figure 9

(Color online) The average degree $E\left[D_{\mathcal{N}\left(i\right)}\mid d_i=k\right]$ of the neighbors of nodes with a given degree $k$, in the unweighted networks measured before (red crosses) and after surgery (blue circles).