Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Oct 2016
[Analysis of the Characteristics of Infantile Small World Neural Network Node Properties Correlated with the Influencing Factors].
We applied resting-state functional magnetic resonance imaging(rfMRI)combined with graph theory to analyze 90 regions of the infantile small world neural network of the whole brain. We tried to get the following two points clear:1 whether the parameters of the node property of the infantile small world neural network are correlated with the level of infantile intelligence development;2 whether the parameters of the infantile small world neural network are correlated with the children’s baseline parameters,i.e.,the demographic parameters such as gender,age,parents’ education level,etc. Twelve cases of healthy infants were included in the investigation(9males and 3females with the average age of 33.42±8.42 months.)We then evaluated the level of infantile intelligence of all the cases and graded by Gesell Development Scale Test. ⋯ The node attributes of small world neural network are widely related to infantile intelligence level,moreover the distribution is characteristic in different encephalic regions. The distribution of dominant encephalic is in accordance the related functions. The existing correlations reflect the ever changing small world nervous network during infantile development.