ABSTRACT
Objective:To investigate the relationship between the changes of default network topology properties of brain function and cognitive function in patients with end-stage renal disease (ESRD).Methods:A total of 31 patients with ESRD were enrolled in the Department of Nephrology, Changzhou Second Hospital Affiliated to Nanjing Medical University from January 2019 to December 2020, and 18 healthy persons were included in the same period as the control group.The cognitive function was evaluated with the Montreal cognitive assessment (MoCA) and trail making tests, and then the subjects were examined by resting-state functional magnetic resonance imaging (rs-fMRI). After preprocessing, the brain functional network was constructed and the topology properities of the network were calculated.The SPSS 20.0 software was used for statistical analysis.Independent sample t-test, chi square test and Pearson correlation analysis were used for data statistics. Results:(1) The score of MoCA in the ESRD group(23.37±1.77) was significantly lower than that in the healthy control group(27.94±1.13)( t=9.537, P<0.001). (2) The levels of Eglobal, Elocal, Cp and Sigma in ESRD group ((0.129±0.025), (0.148±0.040), (0.188±0.046), (1.593±0.650)) were significantly lower than those in healthy control group ((0.160±0.040), (0.212±0.024), (0.276±0.049), (2.004±0.864))( t=3.591, 7.474, 7.058, 2.034, all P<0.05). The Lp value of the ESRD group (8.131±1.905) was significantly higher than that of the control group (6.777±2.150)( t=2.583, P< 0.05). The node efficiency values of bilateral dorsolateral superior frontal gyrus, left middle frontal gyrus, bilateral posterior cingulate gyrus, right hippocampus, left superior marginal gyrus, bilateral angular gyrus and bilateral cuneate anterior lobe in ESRD group ((0.133±0.071), (0.201±0.047), (0.211±0.106), (0.175±0.066), (0.276±0.113), (0.122±0.146), (0.042±0.075), (0.171±0.027), (0.154±0.078), (0.240±0.095), (0.161±0.056))were lower than those in the healthy control group((0.312±0.075), (0.289±0.091), (0.277±0.132), (0.284±0.053), (0.368±0.063), (0.231±0.227), (0.120±0.162), (0.296±0.064), (0.310±0.186), (0.318±0.066), (0.286±0.103))( t=2.107-9.436, all P<0.05). (3)Pearson correlation analysis showed that the node efficiency values of bilateral posterior cingulate gyrus and right hippocampus in ESRD group were positively correlated with the score of MoCA( r=0.36, 0.49, 0.53, all P<0.05). Conclusion:The topological structure of brain functional network is abnormal in ESRD patients, which can affect the cognitive function of patients.
ABSTRACT
Cognitive impairment is one of the three primary symptoms of schizophrenic patients and shows important value in early detection and warning for high-risk individuals. To study the specifics of electroencephalogram (EEG) in patients with schizophrenia under the cognitive load, we collected EEG signals from 17 schizophrenic patients and 19 healthy controls, extracted signals of each band based on wavelet transform, calculated the characteristics of nonlinear dynamic and functional brain networks, and automatically classified the two groups of people by using a machine learning algorithm. Experimental results indicated that the correlation dimension and sample entropy showed significant differences in α, β, θ, and γ rhythm of the Fp1 and Fp2 electrodes between groups under the cognitive load. These results implied that the functional disruptions in the frontal lobe might be the important factors of cognitive impairments in schizophrenic patients. Further results of the automatic classification analysis indicated that the combination of nonlinear dynamics and functional brain network properties as the input characteristics of the classifier showed the best performance, with the accuracy of 76.77%, sensitivity of 72.09%, and specificity of 80.36%. The results of this study demonstrated that the combination of nonlinear dynamics and function brain network properties may be potential biomarkers for early screening and auxiliary diagnosis of schizophrenia.
ABSTRACT
Objective To investigate the effect of transcranial direct current stimulation (tDCS) on the amplitude of low-frequency fluctuation (ALFF) of the resting brain function network in patients in a minimal conscious state (MCS) so as to explore the mechanism.Methods Eleven MCS patients were selected.Among them,there were 9 males and 2 females,10 with cerebral trauma and 1 with cerebral hemorrhage,with an average age of (37.3±8.4) and an average course of disease of (3.4±0.1) months.All subjects were given a resting-state functional magnetic resonance imaging (rs-fMRI) assessment prior to the single tDCS treatment,followed by a 20-minute single sham tDCS treatment at a time.After single-sham stimulation,a second time rs-fMRI assessment test will be conducted,followed by a real tDCS treatment for 20 minutes.Eventually,a third time rs-fMRI assessment test will be implemented.Results No significant statistical difference was shown in terms of all the parameters after single shamtDCS as compared to those before the treatment (P＞0.05).After single real-tDCS,no significant change was observed with CRS-R score,ALFF of default network (left anterior wedge),the frontal-parietal network (left fróntal lobe,right superior gyms),sensory motor network (left auxiliary motor area),subcortical network (right thalamus,bilateral caudate nuclei) was significantly higher than that before treatment,while the ALFF of the frontal network (frontal lobe) and auditory network (bilateral temporal lobes) was significantly decreased (P＜0.05).After single real-tDCS,the ALFF of default network (right frontal lobe) was significantly enhanced compared to that after single sham-tDCS (P＜0.05),while that of the salient network (left insula) and sensorimotor network (right central frontal) was significantly decreased (P＜0.05).Conclusion The enhancement of ALFF activity in the resting state brain function network is a possible neural mechanism for tDCS to promote the recovery of consciousness level in pa tients with minimal conscious state.