First evidence of long-term effects of transcranial pulse stimulation (TPS) on the human brain

Background With the high spatial resolution and the potential to reach deep brain structures, ultrasound-based brain stimulation techniques offer new opportunities to non-invasively treat neurological and psychiatric disorders. However, little is known about long-term effects of ultrasound-based brain stimulation. Applying a longitudinal design, we comprehensively investigated neuromodulation induced by ultrasound brain stimulation to provide first sham-controlled evidence of long-term effects on the human brain and behavior. Methods Twelve healthy participants received three sham and three verum sessions with transcranial pulse stimulation (TPS) focused on the cortical somatosensory representation of the right hand. One week before and after the sham and verum TPS applications, comprehensive structural and functional resting state MRI investigations and behavioral tests targeting tactile spatial discrimination and sensorimotor dexterity were performed. Results Compared to sham, global efficiency significantly increased within the cortical sensorimotor network after verum TPS, indicating an upregulation of the stimulated functional brain network. Axial diffusivity in left sensorimotor areas decreased after verum TPS, demonstrating an improved axonal status in the stimulated area. Conclusions TPS increased the functional and structural coupling within the stimulated left primary somatosensory cortex and adjacent sensorimotor areas up to one week after the last stimulation. These findings suggest that TPS induces neuroplastic changes that go beyond the spatial and temporal stimulation settings encouraging further clinical applications.

Exploring Functional Brain Network Modularity in Educational Contexts

The brain's modular functional organization facilitates adaptability. Modularity has been linked with a wide range of cognitive abilities such as intelligence, memory, and learning. However, much of this work has (1) considered modularity while a participant is at rest rather than during tasks conditions and/or (2) relied primarily on lab-based cognitive assessments. Thus, the extent to which modularity can provide information about real-word behavior remains largely unknown. Here, we investigated whether functional modularity during resting-state and task-based fMRI was associated with academic learning (measured by GPA) and ability (measured by PSAT) in a large sample of high school students. Additional questions concerned the extent to which modularity differs between rest and task conditions, and across spatial scales. Results indicated that whole-brain modularity during task conditions was significantly associated with academic learning. In contrast to prior work, no such associations were observed for resting-state modularity. We further showed that differences in modularity between task conditions and resting-state varied across spatial scales. Taken together, the present findings inform how functional brain network modularity - during task conditions and while at rest - relate to a range of cognitive abilities.

Brain Functional Network Analysis of Patients with Primary Angle-Closure Glaucoma

Objectives. Recent resting-state functional magnetic resonance imaging (fMRI) studies have focused on glaucoma-related neuronal degeneration in structural and spontaneous functional brain activity. However, there are limited studies regarding the differences in the topological organization of the functional brain network in patients with glaucoma. In this study, we aimed to assess both potential alterations and the network efficiency in the functional brain networks of patients with primary angle-closure glaucoma (PACG). Methods. We applied resting-state fMRI data to construct the functional connectivity network of 33 patients with PACG ( 54.21 ± 7.21 years ) and 33 gender- and age-matched healthy controls ( 52.42 ± 7.80 years ). The differences in the global and regional topological brain network properties between the two groups were assessed using graph theoretical analysis. Partial correlations between the altered regional values and clinical parameters were computed for patients with PACG. Results. No significant differences in global topological measures were identified between the two groups. However, significant regional alterations were identified in the patients with PACG, including differences within visual and nonvisual (somatomotor and cognition-emotion) regions. The normalized clustering coefficient and normalized local efficiency of the right superior parietal gyrus were significantly correlated with the retinal fiber layer thickness (RNFLT) and the vertical cup to disk ratio (V C/D). In addition, the normalized node betweenness of the left middle frontal gyrus (orbital portion) was significantly correlated with the V C/D in the patients with PACG. Conclusions. Our results suggest that regional inefficiency with decrease and compensatory increase in local functional properties of visual and nonvisual nodes preserved the brain network of the PACG at the global level.

The research of EEG feature extraction and classification for subjects with different organizational commitment

With the development of EEG analysis technology, researchers have gradually explored the correlation between personality trait (such as Big Five personality) and EEG. However, there are still many challenges in model construction. In this paper, we tried to classify the people with different organizational commitment personality trait through EEG. Firstly, we organized the participants to complete the organizational commitment questionnaire and recorded their resting state EEG. We divided 10 subjects into two classes (positive and negative) according to the questionnaire scores. Then, various EEG features including power spectral density, microstate, functional brain network and nonlinear features from segmented EEG sample were extracted as the input of different machine learning classifiers. Next, several evaluation metrics were used to evaluate the results of the cross-validation experiment. Finally, the results show that the EEG power in α band, the weighted clustering coefficient of functional brain network and the Permutation Entropy of EEG are relatively good features for this classification task. Furthermore, the highest classification accuracy rate can reach 79.9% with 0.87 AUC (the area under the ROC). The attempts in this paper may serve as the basis for our future research.

Age- and Sex-Related Topological Organization of Human Brain Functional Networks and Their Relationship to Cognition

Age and sex associated with changes in the functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 United Kingdom Biobank participants (mean = 62.83 ± 7.41 years). Age was associated with an overall decrease in the effectiveness of network communication (i.e., integration) and loss of functional specialization (i.e., segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks, which were less segregated than in men (FDR adjusted p < 0.05). The age-related changes were also more apparent in men than in women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p ≤ 0.002). This may imply that individual measures may be inadequate to capture much of the variance in the neural activity or its output and need further refinement. The complexity of the organization of the functional brain may be shaped by the age and sex of an individual, which ultimately may influence the cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.

Associations of the Disrupted Functional Brain Network and Cognitive Function in End-Stage Renal Disease Patients on Maintenance Hemodialysis: A Graph Theory-Based Study of Resting-State Functional Magnetic Resonance Imaging

Objective: Cognitive impairment (CI) is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis (MHD). Brain network analysis based on graph theory is a promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients.Methods: A total of 39 patients on MHD (19 cases with CI and 20 without) and 25 healthy controls (HCs) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging (rs-fMRI) and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis.Results: Compared with HCs, the global parameters [sigma, gamma, and local efficiency (Eloc)] in both patient groups decreased significantly (p < 0.05, Bonferroni corrected). The clustering coefficient (Cp) in patients with CI was significantly lower than that in the other two groups (p < 0.05, Bonferroni corrected). The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral (SFGdor) and gyrus rectus (REC) of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased (all p < 0.05, Bonferroni corrected). The global Cp and regional parameters in the three brain regions (right SFGdor, REC, and left amygdala) were significantly correlated with the cognitive function scores (all FDR q < 0.05).Conclusion: This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD.

Functional brain network and trail making test changes after major surgery and delirium

BackgroundDelirium is a frequent complication of elective surgery in elderly patients, associated with an increased risk of long-term cognitive impairment and dementia. Disturbances in the functional brain network were previously reported during delirium. We hypothesized persisting alterations in functional brain networks three months after elective surgery in patients with postoperative delirium, and hypothesized that postoperative brain connectivity changes (irrespective of delirium) are related to cognitive decline.MethodsElderly patients (N=554) undergoing elective surgery underwent clinical assessments (including Trail Making Test B (TMT-B) and resting-state functional magnetic resonance imaging (rs-fMRI) before and three months after surgery. Delirium was assessed on the first seven postoperative days. After strict motion correction, rs-fMRI connectivity strength and network characteristics were calculated in 246 patients (130 patients underwent scans at both timepoints), of whom 38 (16%) developed postoperative delirium.ResultsRs-fMRI functional connectivity strength increased after surgery in the total study population (β=0.006, 95%CI=0.000–0.012, p=0.021), but decreased after postoperative delirium (β=-0.014, 95%CI=0.000–0.012, p=0.026). No difference in TMT-B scores was found at follow-up between patients with and without postoperative delirium. Patients who decreased in functional connectivity strength declined in TMT-B scores compared to the group that did not (β=11.04, 95%CI=0.85-21.2, p=0.034).ConclusionsDelirium was associated with decreased functional connectivity strength three months after the syndrome was clinically resolved, which implies that delirium has lasting impact on brain networks. Decreased connectivity strength was associated with statistically significant (but not necessarily clinically relevant) cognitive deterioration after major surgery, which was not specifically related to delirium.Summary statementDelirium was associated with decreased resting-state fMRI functional connectivity strength three months after the syndrome was clinically resolved. Irrespective of delirium, decreased connectivity strength after major surgery was associated with a statistically significant cognitive deterioration.