Identification Of Early Malnutrition Based On Brain Sources Activity

According to the World Health Organization(WHO)reported in 2017,up to 22.9% of children in developing countries are still suffered from malnutrition.The IQ and cognitive ability of malnourished children are significantly lower than those of normal children,and there are some phenomena such as emotional instability,poor school performance and weak social ability.These effects last for a long time and are serious social problems.However,up to now,there is no clear answer to which parts of the brain are affected by malnutrition in children.Therefore,it is of great significance to study the changes caused by early malnutrition in the brain.By comparing the EEG data of children suffering from malnutrition in the first year of life and those in the control group,the differences in EEG between the two groups were analyzed in order to find suitable biomarkers for malnutrition.Because of the volume effect of EEG measurement,the BC-VARETA traceability method is used to solve the inverse problem of EEG data after pretreatment.The traditional traceability method assumes that sources are independent of each other,but the Brain Connectivity Variable Resolution Electromagnetic Tomographic Analysis(BC-VARETA)method does not use this assumption,that is,the method can get the correlation between sources.Therefore,the results obtained are more accurate.The spectrum information and brain connection information in frequency domain are obtained.Subsequently,feature extraction of spectrum information was carried out to identify possible biomarkers of malnutrition.To construct a network with connection information and calculate network parameters,four indexes are clustering coefficient,average minimum path,local efficiency and global efficiency.The results of feature extraction showed that the temporal lobe,occipital lobe and limbic system of early malnutrition children were abnormal.It was found that the inferior temporal gyrus,superior temporal gyrus,lingual gyrus,cuneus,anterior cingulate gyrus and the Rolandic were significantly different from those of normal children.In terms of network topology parameters,it was found that there were significant differences in average path length,global efficiency and local efficiency between the two groups in the ?1band,but there was no significant difference in clustering coefficient.In the ? band,there are only significant differences in clustering coefficient.The global and local efficiencies and clustering coefficient of early malnutrition group were significantly higher than those of normal group in both frequency bands.We speculate that this is the result of brain function compensation of early malnutrition children in information processing due to the abnormality of some brain regions.These results indicate that compared with normal children,the brain function of early malnourished children has changed,and these changes may cause their IQ,cognitive and learning abilities to be significantly lower than that of normal children.We took the lead in the study of the source-based brain network of malnutrition,revealing the brain mechanism of malnutrition patients,hoping to provide some new ideas for exploring the mechanism of malnutrition-related diseases.