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.
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.
White matter lesion (WML) of presumed vascular origin is one of the common imaging manifestations of cerebral small vessel diseases, which is the main reason of cognitive impairment and even vascular dementia in the elderly. However, there is a lack of early and effective diagnostic methods currently. In recent years, studies of diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) have shown that cognitive impairment in patients with WMLs is associated with disrupted white matter microstructural and brain network connectivity. Therefore, it’s speculated that DTI and rs-fMRI can be effective in early imaging diagnosis of WMLs-related cognitive impairment. This article reviews the role and significance of DTI and rs-fMRI in WMLs-related cognitive impairment.
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.
Nowadays, an increasing number of researches have shown that epilepsy, as a kind of neural network disease, not only affects the brain region of seizure onset, but also remote regions at which the brain network structures are damaged or dysfunctional. These changes are associated with abnormal network of epilepsy. Resting-state network is closely related to human cognitive function and plays an important role in cognitive process. Cognitive dysfunction, a common comorbidity of epilepsy, has adverse impacts on life quality of patients with epilepsy. The mechanism of cognitive dysfunction in epileptic patients is still incomprehensible, but the change of resting-state brain network may be associated with their cognitive impairment. In order to further understand the changes of resting-state network associated with the cognitive function and explore the brain network mechanism of the occurrence of cognitive dysfunction in patients with epilepsy, we review the related researches in recent years.
Electroconvulsive therapy (ECT) is an interventional technique capable of highly effective neuromodulation in major depressive disorder (MDD), but its antidepressant mechanism remains unclear. By recording the resting-state electroencephalogram (RS-EEG) of 19 MDD patients before and after ECT, we analyzed the modulation effect of ECT on the resting-state brain functional network of MDD patients from multiple perspectives: estimating spontaneous EEG activity power spectral density (PSD) using Welch algorithm; constructing brain functional network based on imaginary part coherence (iCoh) and calculate functional connectivity; using minimum spanning tree theory to explore the topological characteristics of brain functional network. The results show that PSD, functional connectivity, and topology in multiple frequency bands were significantly changed after ECT in MDD patients. The results of this study reveal that ECT changes the brain activity of MDD patients, which provides an important reference in the clinical treatment and mechanism analysis of MDD.
Although a great number of studies have investigated the changes of resting-state functional connectivity (rsFC) in patients with mental disorders, such as depression and schizophrenia etc, little is known how stable the changes are, and whether temporal sad or happy mood can modulate the intrinsic rsFC. In our experiments, happy and sad video clips were used to induce temporally happy and sad mood states in 20 healthy young adults. We collected functional magnetic resonance imaging (fMRI) data while participants were watching happy or sad video clips, which were administrated in two consecutive days. Seed-based functional connectivity analyses were conducted using the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), and amygdala as seeds to investigate neural network related to executive function, attention, and emotion. We also investigated the association of the rsFC changes with emotional arousability level to understand individual differences. There is significantly stronger functional connectivity between the left DLPFC and posterior cingulate cortex (PCC) under sad mood than that under happy mood. The increased connectivity strength was positively correlated with subjects' emotional arousability. The increased positive correlation between the left DLPFC and PCC under sad relative to happy mood might reflect an increased processing of negative emotion-relevant stimuli. The easier one was induced by strong negative emotion (higher emotional arousability), the greater the left DLPFC-PCC connectivity was indicated, the greater the instability of the intrinsic rsFC was shown.