Graph Theoretical Analysis Research Articles

Topological organization of the brain network in thyroid-associated ophthalmopathy using graph theoretical analysis.

Mounting neuroimaging evidence indicates that patients with thyroid-associated ophthalmopathy (TAO) demonstrate altered brain function and structure. Nonetheless, the alterations in the topological properties of the functional brain connectome in TAO patients are not yet fully understood. This study aimed to investigate the topological organization of the functional brain connectome in TAO patients using graph-theoretic methods. Twenty-five TAO patients (10 males and 15 females) and 25 age-, sex-, and education-matched healthy controls (HCs) (10 males and 15 females) (the TAO and HC data are from the same dataset in previous studies) underwent resting-state MRI scans. Graph-theoretic analysis was used to study the global, nodal, and edge topological properties of the brain's functional connectome. Both the TAO and HC groups exhibited high-efficiency small-world networks in their brain functional networks. However, there were no significant differences in small-world properties (Cp, γ, λ, Lp, and σ) and network efficiency [global and local efficiencies (Eloc)] between the two groups. In addition, the TAO group demonstrated reduced betweenness centrality in the right fusiform and increased nodal Eloc in the right intraparietal sulcus ( P < 0.05, Bonferroni-corrected). Furthermore, the TAO group displayed altered functional connections among the default-mode network (DMN), visual network (VN), sensorimotor network (SMN), and cingulo-opercular network (CON). Patients with TAO exhibited abnormal topological organization of the human brain connectome, including decreased betweenness centrality and increased nodal Eloc. Moreover, the TAO group displayed altered functional connections primarily within the DMN, VN, SMN, and CON. These findings provide crucial insights into the neural mechanisms underlying visual loss, abnormal emotion regulation, and cognitive deficits in TAO patients.

Postoperative Nodal Efficiency of the Lesional-Hemispheric Hand Motor Area Increasing Potentially Facilitated Motor Recovery for SMA Syndrome.

Supplementary motor area (SMA) syndrome commonly occurs after glioma resection and requires weeks to months of recovery. Thirty-four glioma patients with SMA syndrome were reviewed and assigned to recovered and non-recovered groups based on whether their motor function recovered on postoperative day 7. To validate the association between variations in nodal properties and recovery time, neuro-navigated repetitive transcranial magnetic stimulation (nrTMS) was applied to stimulate potential nodes. Nine other patients (five nrTMS therapy and four sham-nrTMS treatments) with SMA syndrome with unrecovered motor functions on postoperation day 7 were prospectively enrolled. The potential nodes of the sensorimotor network related to recovery time were investigated using preoperative and postoperative resting-state functional magnetic resonance imaging, graph theoretical analysis, and dynamic functional connectome analysis. Nodal efficiency of the lesional-hemispheric upper limb region of BA 4 (A4ul_L) increased in the recovered group (preoperative, 0.472 ± 0.027; postoperative, 0.535 ± 0.020; p = 0.0006). The patients in the nrTMS therapy group quickly recovered (12.0 ± 1.6 days) compared to the sham-nrTMS group (29.5 ± 3.8 days, p = 0.0024). Variations in A4ul_L nodal efficiency was negatively correlated with recovery time (r = -0.841; p = 0.0046). A4ul_L demonstrates enhanced postoperative nodal efficiency and shows therapeutic potential in SMA syndrome recovery, suggesting its viability as a therapeutic target.

Impact of moderate aerobic exercise on small-world topology and characteristics of brain networks after sport-related concussion: an exploratory study

Sport-related concussion (SRC) is a complex brain injury. By applying graph-theoretical analysis to networks derived from neuroimaging techniques, studies have shown that despite an overall retention of small-world topology, changes in small-world properties occur after brain injury. Less is known about how exercise during athletes’ return to sport (RTS) influences these brain network properties. Therefore, in the present study dense electroencephalography (EEG) datasets were collected pre- and post-moderate aerobic exercise. Small-world properties of whole brain (WB) and the default mode network (DMN) were extracted from the EEG datasets of 21 concussed athletes and 21 healthy matched controls. More specifically, path length (LP), clustering coefficient (CP), and small-world index (SWI) in binary and weighted graphs were calculated in the alpha frequency band (7–13 Hz). Pre-exercise, SRC athletes had higher DMN-CP values compared to controls, while post-exercise SRC athletes had higher WB-LP compared to controls. Weighted WB analysis revealed a significant association between SRC and the absence of small-world topology (SWI ≤ 1) post-exercise. This explorative study provides preliminary evidence that moderate aerobic exercise during athletes’ RTS induces an altered network response. Furthermore, this altered response may be related to the clinical characteristics of the SRC athlete.

Graph theory-driven structural and functional connectivity analyses revealing regulatory mechanisms of brain network in patients with classic trigeminal neuralgia.

A specific regulatory mechanism underlying classical trigeminal neuralgia (cTN) remains unknown. The present study posits that the initiation and advancement of cTN may be attributed to a self-regulatory and compensatory mechanism within the brain's limbic system. A sample size of thirty-three patients diagnosed with cTN and twenty-one normal controls were recruited for this investigation. Functional magnetic resonance imaging data were collected from all participants. Graph-theoretic analysis was employed to identify abnormal nodes induced by cTN in the brain atlas, followed by determining the brain network function in conjunction with the outcomes of regional homogeneity (ReHo) and functional connectivity (FC). During data processing, relatively strict thresholds were set for all corrections. The findings indicated that the discrepancy in small-worldness characteristics between the two cohorts primarily stemmed from the characteristic path length. Additionally, there was an overlap between brain regions exhibiting markedly reduced node efficiency in cTN patients and those exhibiting markedly reduced ReHo signal. The FC analysis of the whole brain revealed nine brain regions with reduced connectivity in the cTN group, corresponding to brain regions with diminished node efficiency. Notably, most of these abnormal brain regions were located in the limbic system, providing evidence of the compensatory mechanism of the limbic system.

Molecular architecture and functional dynamics of the pre-incision complex in nucleotide excision repair

Nucleotide excision repair (NER) is vital for genome integrity. Yet, our understanding of the complex NER protein machinery remains incomplete. Combining cryo-EM and XL-MS data with AlphaFold2 predictions, we build an integrative model of the NER pre-incision complex(PInC). Here TFIIH serves as a molecular ruler, defining the DNA bubble size and precisely positioning the XPG and XPF nucleases for incision. Using simulations and graph theoretical analyses, we unveil PInC’s assembly, global motions, and partitioning into dynamic communities. Remarkably, XPG caps XPD’s DNA-binding groove and bridges both junctions of the DNA bubble, suggesting a novel coordination mechanism of PInC’s dual incision. XPA rigging interlaces XPF/ERCC1 with RPA, XPD, XPB, and 5′ ssDNA, exposing XPA’s crucial role in licensing the XPF/ERCC1 incision. Mapping disease mutations onto our models reveals clustering into distinct mechanistic classes, elucidating xeroderma pigmentosum and Cockayne syndrome disease etiology.

Disrupted white matter structural networks in patients with acute ischemic stroke in the right basal ganglia

Widespread structural changes have been observed in patients with stroke in previous diffusion tensor imaging studies. However, the topological organization of white matter structural networks after acute ischemic stroke (AIS) in the right basal ganglia (BG) remains unknown. The aim of our study is to investigate whether the topological structure of the white matter structural network is altered in patients with AIS in the right BG, and its relationship with cognition. Graph theoretical analysis was employed to investigate the topological architecture of whole-brain white matter structural networks in 40 AIS patients in the right BG and 40 healthy controls (HC), and network-based statistics (NBS) were applied to examine structural connectivity alterations. Compared to HC, AIS patients exhibited altered global network properties characterized by increased small-worldness, normalized clustering coefficient, and shortest path length, as well as decreased clustering coefficient, local efficiency, and global efficiency. The nodes with significantly decreased nodal properties in AIS patients were primarily located in the default mode network, limbic system, sensorimotor system, salience network, and central executive network. Reduced structural connectivity detected by NBS in AIS patients were primarily located in the lesional hemisphere. Furthermore, altered nodal properties were correlated with cognitive scores. Documenting the alterations in the topological patterns of white matter structural networks will help to promote the understanding of the neural mechanisms of cognitive impairment after AIS in the right BG.

Changes in functional and structural brain connectivity following bilateral hand transplantation

As a surgical treatment following amputation or loss of an upper limb, nearly 200 hand transplantations have been completed to date. We report here a magnetic resonance imaging (MRI) investigation of functional and structural brain connectivity for a bilateral hand transplant patient (female, 60 years of age), with a preoperative baseline and three postoperative testing sessions each separated by approximately six months. We used graph theoretical analyses to estimate connectivity within and between modules (networks of anatomical nodes), particularly a sensorimotor network (SMN), from resting-state functional MRI and structural diffusion-weighted imaging (DWI). For comparison, corresponding MRI measures of connectivity were obtained from 10 healthy, age-matched controls, at a single testing session. The patient's within-module functional connectivity (both SMN and non-SMN modules), and structural within-SMN connectivity, were higher preoperatively than that of the controls, indicating a response to amputation. Postoperatively, the patient's within-module functional connectivity decreased towards the control participants' values, across the 1.5 years postoperatively, particularly for hand-related nodes within the SMN module, suggesting a return to a more canonical functional organization. Whereas the patient's structural connectivity values remained relatively constant postoperatively, some evidence suggested that structural connectivity supported the postoperative changes in within-module functional connectivity.

Effect of Dialysis on Structural Brain Connectivity in Patients with End-Stage Renal Disease

Introduction: Patients with end-stage renal disease (ESRD) are known to have reduced structural and functional brain connectivity in the brain regions associated with cognitive function. However, the effect of dialysis on brain connectivity remains unclear. This study aimed to evaluate the effects of dialysis on structural brain connectivity in patients with ESRD. Methods: This prospective study included 20 patients with ESRD in the pre-dialysis stage and 35 healthy controls. The patients underwent T2-weighted and three-dimensional T1-weighted magnetic resonance imaging before and 3 months after dialysis initiation. Moreover, the cortical thickness was calculated. We applied graph theoretical analysis to calculate the structural covariance network based on cortical thickness. We compared the cortical thickness and structural covariance network of patients with ESRD in the pre-dialysis stage with those of healthy controls and with those of patients with ESRD in the post-dialysis stage. Results: The mean cortical thickness in both hemispheres was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (2.296 vs. 2.354, p = 0.030; 2.282 vs. 2.362, p = 0.004, respectively) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (2.333 vs. 2.296, p = 0.001; 2.322 vs. 2.282, p = 0.002, respectively). Analysis of the structural covariance network revealed that the assortative coefficient was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (−0.062 vs. −0.031, p = 0.029) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (−0.002 vs. −0.062, p = 0.042). Conclusion: We observed differences in the cortical thickness and structural covariance networks before and after dialysis in patients with ESRD. This indicates that dialysis affects structural brain connectivity, contributing to the understanding of the pathophysiological mechanism of cognitive function alterations resulting from dialysis in patients with ESRD.

Brain network changes after the first seizure: an insight into medication response?

After a first epileptic seizure, anti-seizure medications (ASMs) can change the likelihood of having a further event. This prospective study aimed to quantify brain network changes associated with taking ASM monotherapy. We applied graph theoretical network analysis to longitudinal resting-state functional MRI (fMRI) data from 28 participants who had recently experienced their first seizure. Participants were imaged before and during long-term ASM therapy, with a mean inter-scan interval of 6.9 months. After commencing ASM, we observed an increase in the clustering coefficient and a decrease in network path length. Brain changes after ASM treatment were most prominent in the superior frontoparietal and inferior fronto-temporal regions. Participants with recurrent seizures display the most pronounced network changes after ASM treatment. This study shows changes in brain network function after ASM administration, particularly in participants with recurrent seizures. Larger studies that ideally include control cohorts are required to understand further the connection between ASM-related brain network changes and longer-term seizure status.

Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study.

Task-related studies have consistently reported that listening to speech sounds activate the temporal and prefrontal regions of the brain. However, it is not well understood how functional organization of auditory and language networks differ when processing speech sounds from its resting state form. The knowledge of language network organization in typically developing infants could serve as an important biomarker to understand network-level disruptions expected in infants with hearing impairment. We hypothesized that topological differences of language networks can be characterized using functional connectivity measures in two experimental conditions (1) complete silence (resting) and (2) in response to repetitive continuous speech sounds (steady). Thirty normal-hearing infants (14 males and 16 females, age: 7.8 ± 4.8 months) were recruited in this study. Brain activity was recorded from bilateral temporal and prefrontal regions associated with speech and language processing for two experimental conditions: resting and steady states. Topological differences of functional language networks were characterized using graph theoretical analysis. The normalized global efficiency and clustering coefficient were used as measures of functional integration and segregation, respectively. We found that overall, language networks of infants demonstrate the economic small-world organization in both resting and steady states. Moreover, language networks exhibited significantly higher functional integration and significantly lower functional segregation in resting state compared to steady state. A secondary analysis that investigated developmental effects of infants aged 6-months or below and above 6-months revealed that such topological differences in functional integration and segregation across resting and steady states can be reliably detected after the first 6-months of life. The higher functional integration observed in resting state suggests that language networks of infants facilitate more efficient parallel information processing across distributed language regions in the absence of speech stimuli. Moreover, higher functional segregation in steady state indicates that the speech information processing occurs within densely interconnected specialized regions in the language network.

Modern chemical graph theory

AbstractGraph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study.This article is categorized under: Molecular and Statistical Mechanics &gt; Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism &gt; Computational Materials Science Structure and Mechanism &gt; Molecular Structures

The effect of cognitive reserve on the cognitive connectome in healthy ageing.

During ageing, different cognitive functions decline at different rates. Additionally, cognitive reserve may influence inter-individual variability in age-related cognitive decline. These complex relationships can be studied by constructing a so-called cognitive connectome and characterising it with advanced graph-theoretical network analyses. This study examined the effect of cognitive reserve on the cognitive connectome across age. A total of 334 cognitively healthy participants were stratified into early middle age (37-50years; n = 110), late middle age (51-64years; n = 106), and elderly (65-78years; n = 118) groups. Within each age group, individuals were subdivided into high and low cognitive reserve. For each subgroup, a cognitive connectome was constructed based on correlations between 47 cognitive variables. Applying graph theory, different global network measures were compared between the groups. Graph-theoretical network analyses revealed that individuals with high cognitive reserve were characterized by a stable cognitive connectome across age groups. High cognitive reserve groups only differed in modularity. In contrast, individuals with low cognitive reserve showed a marked reconfiguration of cognitive connectomes across age groups with differences extending over a variety of network measures including network strength, global efficiency, modularity, and small-worldness. Our results suggest a stabilizing effect of cognitive reserve on the cognitive connectome. Gaining further insights into these findings and underlying mechanisms will contribute to our understanding of age-related cognitive decline and guide the development of strategies to preserve cognitive function in ageing.

Investigating changes of functional brain networks in major depressive disorder by graph theoretical analysis of resting-state fMRI

BackgroundMajor Depressive Disorder (MDD), as a chronic mental disorder, causes changes in mood, thoughts, and behavior. The pathophysiology of the disorder and its treatment are still unknown. One of the most notable changes observed in patients with MDD through fMRI is abnormal functional brain connectivity. MethodsPreprocessed data from 60 MDD patients and 60 normal controls (NCs) were selected, which has been performed using the DPARSF toolbox. The whole-brain functional networks and topologies were extracted using graph theory-based methods. A two-sample, two-tailed t-test was used to compare the topological features of functional brain networks between the MDD and NCs groups using the DPABI-Net/Statistical Analysis toolbox. ResultsThe obtained results showed a decrease in both global and local efficiency in MDD patients compared to NCs, and specifically, MDD patients showed significantly higher path length values. Acceptable p-values were obtained with a small sample size and less computational volume compared to the other studies on large datasets. At the node level, MDD patients showed decreased and relatively decreased node degrees in the sensorimotor network (SMN) and the dorsal attention network (DAN), respectively, as well as decreased node efficiency in the SMN, default mode network (DMN), and DAN. Also, MDD patients showed slightly decreased node efficiency in the visual networks (VN) and the ventral attention network (VAN), which were reported after FDR correction with Q < 0.05. LimitationsAll participants were Chinese. ConclusionsCollectively, increased path length, decreased global and local efficiency, and also decreased nodal degree and efficiency in the SMN, DAN, DAN, VN, and VAN were found in patients compared to NCs.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy.

Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.

Early differential impact of MeCP2 mutations on functional networks in Rett syndrome patient-derived human cerebral organoids.

Human cerebral organoids derived from induced pluripotent stem cells can recapture early developmental processes and reveal changes involving neurodevelopmental disorders. Mutations in the X-linked methyl-CpG binding protein 2 (MECP2) gene are associated with Rett syndrome, and disease severity varies depending on the location and type of mutation. Here, we focused on neuronal activity in Rett syndrome patient-derived organoids, analyzing two types of MeCP2 mutations - a missense mutation (R306C) and a truncating mutation (V247X) - using calcium imaging with three-photon microscopy. Compared to isogenic controls, we found abnormal neuronal activity in Rett organoids and altered network function based on graph theoretic analyses, with V247X mutations impacting functional responses and connectivity more severely than R306C mutations. These changes paralleled EEG data obtained from patients with comparable mutations. Labeling DLX promoter-driven inhibitory neurons demonstrated differences in activity and functional connectivity of inhibitory and excitatory neurons in the two types of mutation. Transcriptomic analyses revealed HDAC2-associated impairment in R306C organoids and decreased GABAA receptor expression in excitatory neurons in V247X organoids. These findings demonstrate mutation-specific mechanisms of vulnerability in Rett syndrome and suggest targeted strategies for their treatment.

The effects of musicality on brain network topology in the context of Alzheimer’s disease and memory decline

Abstract Music’s role in modulating brain structure, particularly in neurodegenerative contexts such as Alzheimer’s Disease (AD), has been increasingly recognized. While previous studies have hinted at the potential neuroplastic benefits of musical engagement and training, the mechanisms through which music impacts structural connectivity in neurodegenerative pathways remain underexplored. We aimed to examine the impact of music perception skills, active musical engagement, and musical training on structural connectivity in areas relating to memory, emotion, and learning in individuals with worsening memory impairment, investigating the potential neuroplastic effects of music. Employing diffusion tensor imaging (DTI) based structural connectivity and graph theoretical analysis, we investigated brain topological features in 78 participants aged 42 to 85 with a range of memory impairments. Participants were assessed for musical training, engagement, and perception skills. The study analyzed regional and local network topological metrics to examine the influence of musical activities on graph metrics, while controlling for stages of objective memory impairment (SOMI) and diagnosis, separately. This study aimed to elucidate the effects of musical perception skills, active musical engagement, and musical training on structural connectivity within memory, emotion, and learning-related brain areas in individuals with varying degrees of memory impairment. We found enhanced structural connectivity of the right hippocampus and the right posterior cingulate cortex was associated with stronger local network metrics, such as clustering coefficient and betweenness centrality, with increased music perception skills like melody and beat perception. Musical training specifically impacted the clustering coefficient of the right hippocampus and the node degree of the right mid cingulate gyrus. Active musical engagement influenced the eigenvector centrality of the right hippocampus. Furthermore, musical training was associated with enhanced global metrics, such as global efficiency and characteristic path length. Our study integrates diffusion magnetic resonance imaging (MRI) and graph theoretical analysis to reveal significant effects of musical activities on structural connectivity in key brain regions. The results highlight the potential of musical activities to serve as a non-invasive modulatory tool for cognitive resilience, especially in memory impairment and neurodegeneration contexts. These insights contribute to the understanding of delaying AD onset and aiding early-stage patients through music-based interventions, emphasizing the importance of musical engagement in maintaining cognitive and brain health.

Alterations in functional brain connectivity following treatment for restless legs syndrome: The role of symptom improvement in restoring functional connectivity.

The pathophysiology of restless legs syndrome (RLS) remains incompletely understood. Although several studies have investigated the alterations of brain connectivity as one of the pathophysiological mechanisms of RLS, there are only few reports on functional connectivity changes after RLS treatment. Forty-nine patients with newly diagnosed RLS and 50 healthy controls were prospectively enrolled. The patients underwent resting-state functional magnetic resonance imaging (rs-fMRI) at baseline, and 39 patients underwent follow-up rs-fMRI, 3 months after treatment with pramipexole or pregabalin. Patients were divided into good or poor medication response groups. Functional brain connectivity was analysed using rs-fMRI and graph theoretical analysis. Significant differences in functional connectivity were observed between the RLS patients and healthy controls. The average path length, clustering coefficient, transitivity, and local efficiency were lower (2.02 vs. 2.30, p < 0.001; 0.45 vs. 0.56, p < 0.001; 3.08 vs. 4.21, p < 0.001; and 0.71 vs. 0.76, p < 0.001, respectively) and the global efficiency was higher (0.53 vs. 0.50, p < 0.001) in patients with RLS than in healthy controls. Differences in functional connectivity at the global level were also observed between post- and pre-treatment RLS patients who showed a good medication response. Transitivity in the post-treatment group was higher than that in the pre-treatment group (3.22 vs. 3.04, p = 0.007). Global efficiency was positively correlated with RLS severity (r = 0.377, p = 0.007). This study demonstrates that RLS is associated with distinct alterations in brain connectivity, which can be partially normalised following symptom management. These findings suggest that therapeutic interventions for RLS modulate brain function, emphasising the importance of symptom-focussed treatment in managing RLS.

Abnormal Topological Organization of Human Brain Connectome in Primary Dysmenorrhea Patients Using Graph Theoretical Analysis.

Accumulating studies have revealed altered brain function and structure in regions linked to sensory, pain and emotion in individuals with primary dysmenorrhea (PD). However, the changes in the topological properties of the brain's functional connectome in patients with PD experiencing chronic pain remain poorly understood. Our study aimed to explore the mechanism of functional brain network impairment in individuals withPD through a graph-theoretic analysis. This study was a randomized controlled trial that included individuals with PD and healthy controls (HC) from June 2021 to June 2022. The experiment took place in the magnetic resonance imaging facility at Jiangxi Provincial People's Hospital. Static MRI scans were conducted on 23 female patients with PD and 23 healthy female controls. A two-sample t-test was conducted to compare the global and nodal indices between the two groups, while the Network-Based Statistics (NBS) method was utilized to explore the functional connectivity alterations between the groups. In the global index, The PD group exhibited decreased Sigma (p = 0.0432) and Gamma (p = 0.0470) compared to the HC group among the small-world network properties.(p<0.05) In the nodal index, the PD group displayed reduced betweenness centrality and increased degree centrality in the default mode network (DMN), along with decreased nodal efficiency and increased degree centrality in the visual network (VN). (P < 0.05, Bonferroni-corrected) Furthermore, in the connection analysis, PD patients showed altered functional connectivity in the basal ganglia network (BGN), VN, and DMN.(NBS corrected). Our results indicate that individuals with PD showed abnormal brain network efficiency and abnormal connection within DMN, VN and BGN related to pain matrix. These findings have important references for understanding the neural mechanism of pain in PD.

Analyzing the topological properties of resting-state brain function network connectivity based on graph theoretical methods in patients with high myopia

AimRecent imaging studies have found significant abnormalities in the brain’s functional or structural connectivity among patients with high myopia (HM), indicating a heightened risk of cognitive impairment and other behavioral changes. However, there is a lack of research on the topological characteristics and connectivity changes of the functional networks in HM patients. In this study, we employed graph theoretical analysis to investigate the topological structure and regional connectivity of the brain function network in HM patients.MethodsWe conducted rs-fMRI scans on 82 individuals with HM and 59 healthy controls (HC), ensuring that the two groups were matched for age and education level. Through graph theoretical analysis, we studied the topological structure of whole-brain functional networks among participants, exploring the topological properties and differences between the two groups.ResultsIn the range of 0.05 to 0.50 of sparsity, both groups demonstrated a small-world architecture of the brain network. Compared to the control group, HM patients showed significantly lower values of normalized clustering coefficient (γ) (P = 0.0101) and small-worldness (σ) (P = 0.0168). Additionally, the HM group showed lower nodal centrality in the right Amygdala (P < 0.001, Bonferroni-corrected). Notably, there is an increase in functional connectivity (FC) between the saliency network (SN) and Sensorimotor Network (SMN) in the HM group, while the strength of FC between the basal ganglia is relatively weaker (P < 0.01).ConclusionHM Patients exhibit reduced small-world characteristics in their brain networks, with significant drops in γ and σ values indicating weakened global interregional information transfer ability. Not only that, the topological properties of the amygdala nodes in HM patients significantly decline, indicating dysfunction within the brain network. In addition, there are abnormalities in the FC between the SN, SMN, and basal ganglia networks in HM patients, which is related to attention regulation, motor impairment, emotions, and cognitive performance. These findings may provide a new mechanism for central pathology in HM patients.

EEG signature of near-death-like experiences during syncope-induced periods of unresponsiveness

During fainting, disconnected consciousness may emerge in the form of dream-like experiences. Characterized by extra-ordinary and mystical features, these subjective experiences have been associated to near-death-like experiences (NDEs-like). We here aim to assess brain activity during syncope-induced disconnected consciousness by means of high-density EEG monitoring. Transient loss of consciousness and unresponsiveness were induced in 27 healthy volunteers through hyperventilation, orthostasis, and Valsalva maneuvers. Upon awakening, subjects were asked to report memories, if any. The Greyson NDE scale was used to evaluate the potential phenomenological content experienced during the syncope-induced periods of unresponsiveness. EEG source reconstruction assessed cortical activations during fainting, which were regressed out with subjective reports collected upon recovery of normal consciousness. We also conducted functional connectivity, graph-theoretic and complexity analyses. High quality high-density EEG data were obtained in 22 volunteers during syncope and unresponsiveness (lasting 22±8 s). NDE-like features (Greyson NDE scale total score ≥7/32) were apparent for eight volunteers and characterized by higher activity in delta, theta and beta2 bands in temporal and frontal regions. The richness of the NDE-like content was associated with delta, theta and beta2 bands cortical current densities, in temporal, parietal and frontal lobes, including insula, right temporoparietal junction, and cingulate cortex. Our analyses also revealed a higher complexity and that networks related to delta, theta, and beta2 bands were characterized by a higher overall connectivity paralleled by a higher segregation (i.e., local efficiency) and a higher integration (i.e., global efficiency) for the NDE-like group compared to the non-NDE-like group. Fainting-induced NDE-like episodes seem to be sustained by surges of neural activity representing promising markers of disconnected consciousness.