The aim of this paper is to reveal the change of the brain function for nicotine addicts after smoking cessation, and explore the basis of neural physiology for the nicotine addicts in the process of smoking cessation. Fourteen subjects, who have a strong dependence on nicotine, have agreed to give up smoking and insist on completing the test, and 11 volunteers were recruited as the controls. The resting state functional magnetic resonance imaging and the regional homogeneity (ReHo) algorithm have been used to study the neural activity before and after smoking cessation. A two factors mixed design was used to investigate within-group effects and between-group effects. After 2 weeks’ smoking cessation, the increased ReHo value were exhibited in the brain area of supplementary motor area, paracentral lobule, calcarine, cuneus and lingual gyrus. It suggested that the synchronization of neural activity was enhanced in these brain areas. And between-group interaction effects were appeared in supplementary motor area, paracentral lobule, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results indicate that the brain function in supplementary motor area of smoking addicts would be enhanced significantly after 2 weeks’ smoking cessation.
Objective To investigate the differences in the topology of functional brain networks between populations with good spatial navigation ability and those with poor spatial navigation ability. Methods From September 2020 to September 2021, 100 college students from PLA Army Border and Coastal Defense Academy were selected to test the spatial navigation ability. The 25 students with the highest spatial navigation ability were selected as the GN group, and the 25 with the lowest spatial navigation ability were selected as the PN group, and their resting-state functional MRI and 3D T1-weighted structural image data of the brain were collected. Graph theory analysis was applied to study the topology of the brain network, including global and local topological properties. Results The variations in the clustering coefficient, characteristic path length, and local efficiency between the GN and PN groups were not statistically significant within the threshold range (P>0.05). The brain functional connectivity networks of the GN and PN groups met the standardized clustering coefficient (γ)>1, the standardized characteristic path length (λ)≈1, and the small-world property (σ)>1, being consistent with small-world network property. The areas under curve (AUCs) for global efficiency (0.22±0.01 vs. 0.21±0.01), γ value (0.97±0.18 vs. 0.81±0.18) and σ value (0.75±0.13 vs. 0.64±0.13) of the GN group were higher than those of the PN group, and the differences were statistically significant (P<0.05); the between-group difference in AUC for λ value was not statistically significant (P>0.05). The results of the nodal level analysis showed that the AUCs for nodal clustering coefficients in the left superior frontal gyrus of orbital region (0.29±0.05 vs. 0.23±0.07), the right rectus gyrus (0.29±0.05 vs. 0.23±0.09), the middle left cingulate gyrus and its lateral surround (0.22±0.02 vs. 0.25±0.02), the left inferior occipital gyrus (0.32±0.05 vs. 0.35±0.05), the right cerebellar area 3 (0.24±0.04 vs. 0.26±0.03), and the right cerebellar area 9 (0.22±0.09 vs. 0.13±0.13) were statistically different between the two groups (P<0.05). The differences in AUCs for degree centrality and nodal efficiency between the two groups were not statistically significant (P>0.05). Conclusions Compared with people with good spatial navigation ability, the topological properties of the brains of the ones with poor spatial navigation ability still conformed to the small-world network properties, but the connectivity between brain regions reduces compared with the good spatial navigation ability group, with a tendency to convert to random networks and a reduced or increased nodal clustering coefficient in some brain regions. Differences in functional brain network connectivity exist among people with different spatial navigation abilities.
Brain aging can affect the strength of functional connectivity between brain regions. In recent years, studies have shown that functional connectivity is fluctuant over time, and can reflect more physiological and pathological information. Therefore, in the study resting state functional magnetic resonance imaging (fMRI) data of 32 elderly subjects and 36 younger subjects were selected, and the sliding window technique was used to estimate dynamic functional connectivity network. Then, the dependency of fluctuating energy difference on frequency band was studied using wavelet packet analysis, conducting the linear regression with age at the same time. Results showed that the fluctuating energy in older group was significantly higher than that in the young group in low frequency, and it was significantly lower than that in the young people in high frequency. These results suggested that the dynamic functional connectivity between networks in the elderly exist slow wave phenomenon, which may be related to the decreased reaction rate of the elderly. This article provides new ideas and methods for the research about brain aging, and promotes a theoretical basis for further understanding of the physiological significance of brain dynamic functional connectivity.
Early diagnosis and accurate stage of liver fibrosis are important for conducting the clinic therapy and assessing the therapeutic outcome. Functional magnetic resonance imaging (fMRI), as a noninvasive and effective method, plays an important role in diagnosis and stage of liver fibrosis. This review focuses on the advances in fMRI evaluation of liver fibrosis.
Amblyopia is a visual development deficit caused by abnormal visual experience in early life, mainly manifesting as defected visual acuity and binocular visual impairment, which is considered to reflect abnormal development of the brain rather than organic lesions of the eye. Previous studies have reported abnormal spontaneous brain activity in patients with amblyopia. However, the location of abnormal spontaneous activity in patients with amblyopia and the association between abnormal brain function activity and clinical deficits remain unclear. The purpose of this study is to analyze spontaneous brain functional activity abnormalities in patients with amblyopia and their associations with clinical defects using resting-state functional magnetic resonance imaging (fMRI) data. In this study, 31 patients with amblyopia and 31 healthy controls were enrolled for resting-state fMRI scanning. The results showed that spontaneous activity in the right angular gyrus, left posterior cerebellum, and left cingulate gyrus were significantly lower in patients with amblyopia than in controls, and spontaneous activity in the right middle temporal gyrus was significantly higher in patients with amblyopia. In addition, the spontaneous activity of the left cerebellum in patients with amblyopia was negatively associated with the best-corrected visual acuity of the amblyopic eye, and the spontaneous activity of the right middle temporal gyrus was positively associated with the stereoacuity. This study found that adult patients with amblyopia showed abnormal spontaneous activity in the angular gyrus, cerebellum, middle temporal gyrus, and cingulate gyrus. Furthermore, the functional abnormalities in the cerebellum and middle temporal gyrus may be associated with visual acuity defects and stereopsis deficiency in patients with amblyopia. These findings help explain the neural mechanism of amblyopia, thus promoting the improvement of the treatment strategy for amblyopia.
A great number of studies have demonstrated functional abnormalities in children with attention-deficit/hyperactivity disorder (ADHD), although conflicting results have also been reported. And few studies analyzed homotopic functional connectivity between hemispheres. In this study, resting-state functional magnetic resonance imaging (MRI) data were recorded from 45 medication-na?ve ADHD children and 26 healthy controls. The regional homogeneity (ReHo), degree centrality (DC) and voxel-mirrored homotopic connectivity (VMHC) values were compared between the two groups to depict the intrinsic brain activities. We found that ADHD children exhibited significantly lower ReHo and DC values in the right middle frontal gyrus and the two values correlated with each other; moreover, lower VMHC values were found in the bilateral occipital lobes of ADHD children, which was negatively related with anxiety scores of Conners' Parent Rating Scale (CPRS-R) and positively related with completed categories of Wisconsin Card Sorting Test (WCST). Our results might suggest that less spontaneous neuronal activities of the right middle frontal gyrus and the bilateral occipital lobes in ADHD children.
Entropy model is widely used in epileptic electroencephalogram (EEG) analysis, but there are few reports on how to objectively select the parameters to compute the entropy model in the analysis of resting-state functional magnetic resonance imaging (rfMRI). Therefore, an optimization algorithm to confirm the parameters in multi-scale entropy (MSE) model was proposed, and the location of epileptogenic hemisphere was taken as an example to test the optimization effect by supervised machine learning. The rfMRI data of 20 temporal lobe epilepsy (TLE) patients with hippocampal sclerosis, positive on structural magnetic resonance imaging, were divided into left and right groups. Then, the parameters in MSE model were optimized by the receiver operating characteristic curves (ROC) and area under ROC curve (AUC) values in sensitivity analysis, and the entropy value of the brain regions with statistically significant difference between the groups were taken as sensitive features to epileptogenic hemisphere lateral. The optimized entropy values of these bio-marker brain areas were considered as feature vectors input into the support vector machine (SVM). Finally, combining optimized MSE model with SVM could accurately distinguish epileptogenic hemisphere in TLE at an average accuracy rate of 95%, which was higher than the current level. The results show that the MSE model parameter optimization algorithm can accurately extract the functional imaging markers sensitive to the epileptogenic hemisphere, and achieve the purpose of objectively selecting the parameters for MSE in rfMRI, which provides the basis for the application of entropy in advanced technology detection.
Objective To review the current status of magnetic resonance imaging (MRI) techniques in the evaluation of hepatic fibrosis. Methods The application and recent advances of various kinds of MRI techniques in evaluating hepatic fibrosis were summarized by literature review. Results The state-of-the-art of MRI evaluating of hepatic fibrosis included common contrast-enhanced MRI, double contrast-enhanced MRI, and various functional MRI techniques. Common contrast-enhanced MRI could detect morphological changes of the liver, but little value in phasing. Double contrast-enhanced MRI markedly increased the contrast to noise ratio. Except diagnosis liver fibrosis, functional MRI also could phase it by its serverity. Conclusion MRI techniques, especially those functional MRI techniques, are advancing very fast and have very great potentiality in both the diagnosis and severity assessment of hepatic fibrosis.
This study sought to reveal the difference of brain functions at resting-state between subjects with sub-health and normal controls by using the functional magnetic resonance imaging (fMRI) technology. Resting-state fMRI scans were performed on 24 subjects of sub-health and on 24 healthy controls with gender, age and education matched with the sub-health persons. Compared to the healthy controls, the sub-health group showed significantly higher regional homogeneity (ReHo) in the left post-central gyrus and the right post-central gyrus. On the other hand, the sub-health group showed significantly lower ReHo in the left superior frontal gyrus, in the right anterior cingulated cortex and ventra anterior cingulate gyrus, in the left dorsolateral frontal gyrus, and in the right middle temporal gyrus. The Significant difference in ReHo suggests that thebsub-health persons have abnormalities in certain brain regions. It is proved that its specific action and meaning deserves further assessment.
ObjectiveSeizure-related respiratory or cardiac dysfunction was once thought to be the direct cause of sudden unexpected death in epilepsy (SUDEP), but both may be secondary to postictal cerebral inhibition. An important issue that has not been explored to date is the neural network basis of cerebral inhibition. Our aim was to investigate the features of neural networks in patients at high risk for SUDEP using a blood oxygen level-dependent (BOLD) resting-state functional MRI (Rs-fMRI) technique.
MethodsRs-fMRI data were recorded from 13 patients at high risk for SUDEP and 12 patients at low risk for SUDEP. The amplitude of low-frequency fluctuations (ALFF) values were compared between the two groups to decipt the regional brain activities.
ResultsCompared with patients at low risk for SUDEP, patients at high risk exhibited significant ALFF reductions in the right superior frontal gyrus, the left superior orbital frontal gyrus, the left insula and the left thalamus; and ALFF increase in the right middle cigulum gyrus, the right supplementary motor area and the left thalamus.
ConclusionsThese findings highlight the need to understand the fundamental neural network dysfunction in SUDEP, which may fill the missing link between seizure-related cardiorespiratory dysfunction and SUDEP, and provide a promising neuroimaging biomarker for risk prediction of SUDEP.
