Brain Network Analysis And Appplication Of Cognitive Neural Plasticity For ADHD

Attention deficit hyperactivity disorder(ADHD)is a mental disorder.Currently,the diagnosis of ADHD is limited to the scale of behavior.This study depends on the technology of functional magnetic resonance imaging(fMRI)taking children with ADHD disease as the research object.ADHD brain network is studied from different scales and different aspects,to reveal changes in the brain that ADHD children,which provide help for clinical diagnosis and treatment.The main work is as follows:1.The changes of the functional network properties of ADHD children were studied based on the AAL-1024 brain region.The functional brain network of ADHD children was constructed by using the brain region template of AAL-1024,and the network properties analysis was combined with graph theory.The results showed that compared with the normal group,the brain network of ADHD children was more sparse.According to the analysis of network node properties,the function of ADHD children in the frontal lobe was weakened,while the occipital lobe was enhanced.Based on cluster modularization analysis,the modularization of ADHD patients was reduced,and the bilateral frontal lobe and the frontoparietal network increased.The posterior cingulate was reduced to the anterior frontal and anterior temporal pole.2.The functional connection and effect connection of eight static brain networks in ADHD children were studied by using independent component analysis and condition granger causality analysis.The results showed that there were differences in the activation of 8 resting state networks between the two groups,and the average function connection value in the difference region was correlated with the patients' behavioral scale score.Based on the analysis of conditional GCA,the degree-in and degree-out of patient group was significantly greater than that of normal group.The effect connection analysis of the network showed that the patient group's dorsal attention network was enhanced with the affective network,sensorimotor network and language network.3.Two categories of people are classified by support vector machine.The results showed that the classification based on ReHo value can achieve better results.According to the feature weight map,the interest area was selected and the effect connection between the interested regions was studied by using the multi-variable GCA method.The results showed that ADHD had abnormal function in the frontal lobe-occipital lobe-cerebellum.