Modular architecture of metabolic brain network and its effects on the spread of perturbation impact

Retrosplenial Cortex Effects Contextual Fear Formation Relying on Dysgranular Constituent in Rats

“…The metabolic networks were constructed as a collection of 39 nodes representing brain regions connected by edges corresponding to the links between them; 39 anatomical brain regions ( Supplementary Figure 2 and Supplementary Table 1 ) were predefined by a three-dimensional digital map based on the Paxinos and Watson atlas ( Nie et al, 2013 ). The correlation coefficient between each pair of nodes was calculated with Pearson’s correlation in an intersubject manner, and the absolute value of correlation coefficient was used to define the weight of the edge ( Zhang et al, 2019 ).…”

“…Graph theoretic measurements were used to analyze the node properties. In this study, we mainly focused on the nodal degree and nodal efficiency, which characterized the node’s connectivity and efficiency of parallel information transfer in the network, respectively ( Choi et al, 2014 ; Zhang et al, 2019 ).…”

“…We quantitatively determined the hubs by the nodal Z -score. Z i -score is defined to measure how well-connected node i is to nodes in a network ( Zhang et al, 2019 ), which makes the nodal degree comparable between networks. The Z i -score is defined as…”

“… is the average of k over all the nodes, and σ k is the standard deviation of k in a weighted network. Node i is defined as a hub when Z i -score > 1 ( Zhang et al, 2019 ).…”

“…Relative to simple tests for regional metabolic patterns due to physiologic and pathologic activity, FDG metabolic brain networks would evaluate the property changes of the system globally as well as the relationships among local brain regions at the whole brain level, which is a significant advantage of this method to reveal the mechanisms of complex systems ( Yakushev et al, 2017 ). Nowadays, metabolic brain networks based on FDG-PET images have been emerging as a useful tool in basic and clinical neuroscience ( Zhang et al, 2019 ; Huang et al, 2020 ). In this study, to determine the roles of RSCg and RSCd during CFC of rat model, combining pharmacological approaches with [ 18 F]-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) imaging and brain network methods, we investigated their effects and the underlying network mechanisms.…”