Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study

Brain functional network changes in patients with juvenile myoclonic epilepsy: a study based on graph theory and Granger causality analysis

Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown that the brain networks are disrupted in adolescent patients with juvenile myoclonic epilepsy (JME). However, previous studies have mainly focused on investigating brain connectivity disruptions from the perspective of static functional connections, overlooking the dynamic causal characteristics between brain network connections. In our study involving 37 JME patients and 35 Healthy Controls (HC), we utilized rs-fMRI to construct whole-brain functional connectivity network. By applying graph theory, we delved into the altered topological structures of the brain functional connectivity network in JME patients and identified abnormal regions as key regions of interest (ROIs). A novel aspect of our research was the application of a combined approach using the sliding window technique and Granger causality analysis (GCA). This method allowed us to delve into the dynamic causal relationships between these ROIs and uncover the intricate patterns of dynamic effective connectivity (DEC) that pervade various brain functional networks. Graph theory analysis revealed significant deviations in JME patients, characterized by abnormal increases or decreases in metrics such as nodal betweenness centrality, degree centrality, and efficiency. These findings underscore the presence of widespread disruptions in the topological features of the brain. Further, clustering analysis of the time series data from abnormal brain regions distinguished two distinct states indicative of DEC patterns: a state of strong connectivity at a lower frequency (State 1) and a state of weak connectivity at a higher frequency (State 2). Notably, both states were associated with connectivity abnormalities across different ROIs, suggesting the disruption of local properties within the brain functional connectivity network and the existence of widespread multi-functional brain functional networks damage in JME patients. Our findings elucidate significant disruptions in the local properties of whole-brain functional connectivity network in patients with JME, revealing causal impairments across multiple functional networks. These findings collectively suggest that JME is a generalized epilepsy with localized abnormalities. Such insights highlight the intricate network dysfunctions characteristic of JME, thereby enriching our understanding of its pathophysiological features.

Abnormal white matter structural network topological property in patients with temporal lobe epilepsy

BACKGROUND

Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in patients with temporal lobe epilepsy (TLE). However, alterations in the topological properties of the WM structural network in patients with TLE remain unclear. Graph theoretical analysis provides a new perspective for evaluating the connectivity of WM structural networks.

METHODS

DTI was used to map the structural networks of 18 patients with TLE (10 males and 8 females) and 29 (17 males and 12 females) age- and gender-matched normal controls (NC). Graph theory was used to analyze the whole-brain networks and their topological properties between the two groups. Finally, partial correlation analyses were performed on the weighted network properties and clinical characteristics, namely, duration of epilepsy, verbal intelligence quotient (IQ), and performance IQ.

RESULTS

Patients with TLE exhibited reduced global efficiency and increased characteristic path length. A total of 31 regions with nodal efficiency alterations were detected in the fractional anisotropy_ weighted network of the patients. Communication hubs, such as the middle temporal gyrus, right inferior temporal gyrus, left calcarine, and right superior parietal gyrus, were also differently distributed in the patients compared with the NC. Several node regions showed close relationships with duration of epilepsy, verbal IQ, and performance IQ.

CONCLUSIONS

Our results demonstrate the disruption of the WM structural network in TLE patients. This study may contribute to the further understanding of the pathological mechanism of TLE.

Topological properties and connectivity patterns in brain networks of patients with refractory epilepsy combined with intracranial electrical stimulation

Objective

Although intracranial electrical stimulation has emerged as a treatment option for various diseases, its impact on the properties of brain networks remains challenging due to its invasive nature. The combination of intracranial electrical stimulation and whole-brain functional magnetic resonance imaging (fMRI) in patients with refractory epilepsy (RE) makes it possible to study the network properties associated with electrical stimulation. Thus, our study aimed to investigate the brain network characteristics of RE patients with concurrent electrical stimulation and obtain possible clinical biomarkers.

Methods

Our study used the GRETNA toolbox, a graph theoretical network analysis toolbox for imaging connectomics, to calculate and analyze the network topological attributes including global measures (small-world parameters and network efficiency) and nodal characteristics. The resting-state fMRI (rs-fMRI) and the fMRI concurrent electrical stimulation (es-fMRI) of RE patients were utilized to make group comparisons with healthy controls to identify the differences in network topology properties. Network properties comparisons before and after electrode implantation in the same patient were used to further analyze stimulus-related changes in network properties. Modular analysis was used to examine connectivity and distribution characteristics in the brain networks of all participants in study.

Results

Compared to healthy controls, the rs-fMRI and the es-fMRI of RE patients exhibited impaired small-world property and reduced network efficiency. Nodal properties, such as nodal clustering coefficient (NCp), betweenness centrality (Bc), and degree centrality (Dc), exhibited differences between RE patients (including rs-fMRI and es-fMRI) and healthy controls. The network connectivity of RE patients (including rs-fMRI and es-fMRI) showed reduced intra-modular connections in subcortical areas and the occipital lobe, as well as decreased inter-modular connections between frontal and subcortical regions, and parieto-occipital regions compared to healthy controls. The brain networks of es-fMRI showed a relatively weaker small-world structure compared to rs-fMRI.

Conclusion

The brain networks of RE patients exhibited a reduced small-world property, with a tendency toward random networks. The network connectivity patterns in RE patients exhibited reduced connections between cortical and subcortical regions and enhanced connections among parieto-occipital regions. Electrical stimulation can modulate brain network activity, leading to changes in network connectivity patterns and properties.

Abnormal functional connectivity of the posterior hypothalamus and other arousal regions in surgical temporal lobe epilepsy

OBJECTIVE

This study sought to characterize resting-state functional MRI (fMRI) connectivity patterns of the posterior hypothalamus (pHTH) and the nucleus basalis of Meynert (NBM) in surgical patients with mesial temporal lobe epilepsy (mTLE), and to investigate potential correlations between functional connectivity of these arousal regions and neurocognitive performance.

METHODS

The study evaluated resting-state fMRI in 60 patients with preoperative mTLE and in 95 healthy controls. The authors first conducted voxel-wise connectivity analyses seeded from the pHTH, combined anterior and tuberal hypothalamus (atHTH; i.e., the rest of the hypothalamus), and the NBM ipsilateral (ipsiNBM) and contralateral (contraNBM) to the epileptogenic zone. Based on these results, the authors included the pHTH, ipsiNBM, and frontoparietal neocortex in a network-based statistic (NBS) analysis to elucidate a network that best distinguishes patients from controls. The connections involving the pHTH and ipsiNBM from this network were included in age-corrected pairwise region of interest (ROI) analysis, along with connections between arousal structures, including the pHTH, ipsiNBM, and brainstem arousal regions. Finally, patient functional connectivity was correlated with clinical neurocognitive testing scores for IQ as well as attention and concentration tests.

RESULTS

The voxel-wise analysis demonstrated that the pHTH, when compared with the atHTH, showed more widespread functional connectivity decreases in surgical mTLE patients when compared with controls. It was also observed that the ipsiNBM, but not the contraNBM, showed decreased functional connectivity in mTLE. The NBS analysis uncovered a perturbed network of frontoparietal regions, the pHTH, and ipsiNBM that distinguishes patients from controls. Age-corrected ROI analysis revealed functional connectivity decreases between the pHTH and bilateral superior frontal gyri, medial orbitofrontal cortices, rostral anterior cingulate cortices, and inferior parietal cortices in mTLE when compared with controls. For the ipsiNBM, there was reduced connectivity with bilateral medial orbitofrontal and rostral anterior cingulate cortices. Age-corrected ROI analysis also demonstrated upstream connectivity decreases from controls between the pHTH and the brainstem arousal regions, cuneiform/subcuneiform (CSC) nuclei, and ventral tegmental area, as well as the ipsiNBM and CSC nuclei. Reduced functional connectivity was also detected between the pHTH and ipsiNBM. Lastly, neurocognitive test scores for attention and concentration were found to be positively correlated with the functional connectivity between the pHTH and ipsiNBM, suggesting worse performance associated with connectivity perturbations.

CONCLUSIONS

This study demonstrated perturbed resting-state functional connectivity of arousal regions in surgical mTLE and is one of the first investigations to demonstrate decreased functional connectivity of the pHTH with frontoparietal regions and other arousal regions. Connectivity disturbances in arousal regions may contribute to neurocognitive deficits in surgical mTLE patients.

Functional connectivity alterations in traumatic brain injury patients with late seizures

PTE is a neurological disorder characterized by recurrent and spontaneous epileptic seizures. PTE is a major public health problem occurring in 2-50% of TBI patients. Identifying PTE biomarkers is crucial for the development of effective treatments. Functional neuroimaging studies in patients with epilepsy and in epileptic rodents have observed that abnormal functional brain activity plays a role in the development of epilepsy. Network representations of complex systems ease quantitative analysis of heterogeneous interactions within a unified mathematical framework. In this work, graph theory was used to study resting state functional magnetic resonance imaging (rs-fMRI) and reveal functional connectivity abnormalities that are associated with seizure development in traumatic brain injury (TBI) patients. We examined rs-fMRI of 75 TBI patients from Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) which aims to identify validated Post-traumatic epilepsy (PTE) biomarkers and antiepileptogenic therapies using multimodal and longitudinal data acquired from 14 international sites. The dataset includes 28 subjects who had at least one late seizure after TBI and 47 subjects who had no seizures within 2 years post-injury. Each subject's neural functional network was investigated by computing the correlation between the low frequency time series of 116 regions of interest (ROIs). Each subject's functional organization was represented as a network consisting of nodes, brain regions, and edges that show the relationship between the nodes. Then, several graph measures concerning the integration and the segregation of the functional brain networks were extracted in order to highlight changes in functional connectivity between the two TBI groups. Results showed that the late seizure-affected group had a compromised balance between integration and segregation and presents functional networks that are hyperconnected, hyperintegrated but at the same time hyposegregated compared with seizure-free patients. Moreover, TBI subjects who developed late seizures had more low betweenness hubs.

Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients

Introduction

Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data.

Methods

The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed.

Results

Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength.

Discussion

Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.

Aberrant brain gray matter and functional networks topology in end stage renal disease patients undergoing maintenance hemodialysis with cognitive impairment

Purpose

To characterize the topological properties of gray matter (GM) and functional networks in end-stage renal disease (ESRD) patients undergoing maintenance hemodialysis to provide insights into the underlying mechanisms of cognitive impairment.

Materials and methods

In total, 45 patients and 37 healthy controls were prospectively enrolled in this study. All subjects completed resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) examinations and a Montreal cognitive assessment scale (MoCA) test. Differences in the properties of GM and functional networks were analyzed, and the relationship between brain properties and MoCA scores was assessed. Cognitive function was predicted based on functional networks by applying the least squares support vector regression machine (LSSVRM) and the whale optimization algorithm (WOA).

Results

We observed disrupted topological organizations of both functional and GM networks in ESRD patients, as indicated by significantly decreased global measures. Specifically, ESRD patients had impaired nodal efficiency and degree centrality, predominantly within the default mode network, limbic system, frontal lobe, temporal lobe, and occipital lobe. Interestingly, the involved regions were distributed laterally. Furthermore, the MoCA scores significantly correlated with decreased standardized clustering coefficient (γ), standardized characteristic path length (λ), and nodal efficiency of the right insula and the right superior temporal gyrus. Finally, optimized LSSVRM could predict the cognitive scores of ESRD patients with great accuracy.

Conclusion

Disruption of brain networks may account for the progression of cognitive dysfunction in ESRD patients. Implementation of prediction models based on neuroimaging metrics may provide more objective information to promote early diagnosis and intervention.

Brain Network Alterations in Rectal Cancer Survivors With Depression Tendency: Evaluation With Multimodal Magnetic Resonance Imaging

Surgery and chemotherapy may increase depression tendency in patients with rectal cancer (RC). Nevertheless, few comprehensive studies are conducted on alterations of brain network induced by depression tendency in patients with RC. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) data were collected from 42 patients with RC with surgery and chemotherapy and 38 healthy controls (HCs). Functional network (FN) was constructed from extracting average time courses in brain regions, and structural network (SN) was established by deterministic tractography. Graph theoretical analysis was used to calculate network properties. Networks resilient of two networks were assessed. Clinical correlation analysis was explored between altered network parameters and Hamilton depression scale (HAMD) score. This study revealed impaired FN and SN at both local and global levels and changed nodal efficiency and abnormal small-worldness property in patients with RC. On the whole, all FNs are more robust than SN. Moreover, compared with HC, patients with RC show less robustness in both networks. Regions with decreased nodal efficiency were associated with HAMD score. These cognitive dysfunctions are mainly attributable to depression-related brain functional and structural network alterations. Brain network reorganization is to prevent patients with RC from more serious depression after surgery and chemotherapy.

A Comparative Analysis of White Matter Structural Networks on SCLC Patients After Chemotherapy

Previous sMRI, DTI and rs-fMRI studies in small cell lung cancer (SCLC) patients have reported that patients after chemotherapy had gray and white matter structural alterations along with functional deficits. Nonetheless, few are known regarding the potential alterations in the topological organization of the WM structural network in SCLC patients after chemotherapy. In this context, the scope of the present study is to evaluate the WM structural network of 20 SCLC patients after chemotherapy and to 14 healthy controls, by applying a combination of DTI with graph theory. The results revealed that both SCLC and healthy controls groups demonstrated small world properties. The SCLC patients had decreased values in the clustering coefficient, local efficiency and degree metrics as well as increased shortest path length when compared to the healthy controls. Moreover, the two groups reported different topological reorganization of hub distribution. Lastly, the SCLC patients exhibited significantly decreased structural connectivity in comparison to the healthy group. These results underline that the topological organization of the WM structural network in SCLC patients was disrupted and hence constitute new vital information regarding the effects that chemotherapy and cancer may have in the patients' brain at network level.

A study of brain functional network and alertness changes in temporal lobe epilepsy with and without focal to bilateral tonic-clonic seizures

BACKGROUND

Temporal lobe epilepsy (TLE) is commonly refractory. Epilepsy surgery is an effective treatment strategy for refractory epilepsy, but patients with a history of focal to bilateral tonic-clonic seizures (FBTCS) have poor outcomes. Previous network studies on epilepsy have found that TLE and idiopathic generalized epilepsy with generalized tonic-clonic seizures (IGE-GTCS) showed altered global and nodal topological properties. Alertness deficits also were found in TLE. However, FBTCS is a common type of seizure in TLE, and the implications for alertness as well as the topological rearrangements associated with this seizure type are not well understood.

METHODS

We obtained rs-fMRI data and collected the neuropsychological assessment data from 21 TLE patients with FBTCS (TLE- FBTCS), 18 TLE patients without FBTCS (TLE-non- FBTCS) and 22 controls, and constructed their respective functional brain networks. The topological properties were analyzed using the graph theoretical approach and correlations between altered topological properties and alertness were analyzed.

RESULTS

We found that TLE-FBTCS patients showed more serious impairment in alertness effect, intrinsic alertness and phasic alertness than the patients with TLE-non-FBTCS. They also showed significantly higher small-worldness, normalized clustering coefficient (γ) and a trend of higher global network efficiency (gE) compared to TLE-non-FBTCS patients. The gE showed a significant negative correlation with intrinsic alertness for TLE-non-FBTCS patients.

CONCLUSION

Our findings show different impairments in brain network information integration, segregation and alertness between the patients with TLE-FBTCS and TLE-non-FBTCS, demonstrating that impairments of the brain network may underlie the disruptions in alertness functions.

High prevalence of pathological alertness and wakefulness on maintenance of wakefulness test in adults with focal-onset epilepsy

BACKGROUND

Excessive daytime sleepiness (EDS) is a common complaint in adults with epilepsy (AWE), but objective evaluation is lacking. We used the maintenance of wakefulness test (MWT) to objectively measure the ability of adults with focal-onset epilepsy to maintain wakefulness in soporific conditions.

METHODS

Adults with epilepsy participating in a study investigating the effects of lacosamide on sleep and wakefulness underwent baseline ambulatory polysomnography (PSG)/EEG followed by MWT. Mean sleep latency (MSL) and mean percent sleep time (MST, mean percentage of non-wake EEG scored in 3-sec bins from lights out to sleep onset averaged over the 4 MWT trials) were quantified. Subjective sleepiness was assessed by the Epworth Sleepiness Scale (ESS). Spearman correlation and linear regression assessed relationships between MWT parameters, ESS and relevant sleep and epilepsy-related variables.

RESULTS

Maintenance of wakefulness test MSL in 51 AWE (mean age 43.5 ± 13 years, 69% female, mean BMI 24.6 ± 11.2 kg/m²) was 21.7 ± 11.9 min; 45.1% had an abnormally short MSL <19.4 min and 15.7% <8 min. MST was 9.3% [3.3, 19.1]. Mean ESS score was 8.8 ± 5.7; 39% had elevated ESS (>10). No correlation between subjective ESS and objective MSL (p = 0.67) or MST (p = 0.61) was found. MSL was significantly shorter in subjects with focal to bilateral tonic-clonic seizures (FBTCS; 7.9 min [13.6, 22.3]) compared to those without (27.4 min [21.2, 33.6], p = 0.013). Younger subjects had shorter MSL; MSL increased 3.2 min for every 10-year increase in age.

CONCLUSION

We found a high prevalence of objective sleepiness/difficulty maintaining wakefulness on the MWT and subjective sleepiness using the ESS in AWE without a correlation between the two. More severe objective sleepiness was found in subjects with a history of FBTCS and younger age. Further research is needed to determine mechanistic underpinnings and optimal measurements of pathological sleepiness in people with epilepsy given the burden of it on quality of life.

An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth

Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95 % confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies.

Multiscale dynamic mean field (MDMF) model relates resting-state brain dynamics with local cortical excitatory-inhibitory neurotransmitter homeostasis

Previous computational models have related spontaneous resting-state brain activity with local excitatory–inhibitory balance in neuronal populations. However, how underlying neurotransmitter kinetics associated with E–I balance govern resting-state spontaneous brain dynamics remains unknown. Understanding the mechanisms by virtue of which fluctuations in neurotransmitter concentrations, a hallmark of a variety of clinical conditions, relate to functional brain activity is of critical importance. We propose a multiscale dynamic mean field (MDMF) model—a system of coupled differential equations for capturing the synaptic gating dynamics in excitatory and inhibitory neural populations as a function of neurotransmitter kinetics. Individual brain regions are modeled as population of MDMF and are connected by realistic connection topologies estimated from diffusion tensor imaging data. First, MDMF successfully predicts resting-state functional connectivity. Second, our results show that optimal range of glutamate and GABA neurotransmitter concentrations subserve as the dynamic working point of the brain, that is, the state of heightened metastability observed in empirical blood-oxygen-level-dependent signals. Third, for predictive validity the network measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) from existing healthy and pathological brain network studies could be captured by simulated functional connectivity from an MDMF model.

How changes in neurotransmitter kinetics impact the organization of large-scale neurocognitive networks is an open question in neuroscience. Here, we propose a multiscale dynamic mean field (MDMF) model that incorporates biophysically realistic kinetic parameters of receptor binding in a dynamic mean field model and captures brain dynamics from the “whole brain.” MDMF could reliably reproduce the resting-state brain functional connectivity patterns. Further employing graph theoretic methods, MDMF could qualitatively explain the idiosyncrasies of network integration and segregation measures reported by previous clinical studies.

Altered EEG Brain Networks in Patients with Acute Peripheral Herpes Zoster

OBJECTIVE

To investigate whether the brain networks changed in patients with acute peripheral herpes zoster (HZ).

METHODS

We reviewed the EEG database in Jianyang People's Hospital. Patients with acute HZ (n=71) were enrolled from January 2016 to December 2020. Each included subject underwent a ten-minute and 16-channel EEG examination. Five epochs of 10-second EEG data in resting-state were collected from each HZ patient. Five 10-second resting-state EEG epochs from sex- and age-matched healthy controls (HC, n=71) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were collected. Brain network and graph theory analysis based on phase locking value parameter and functional ICA were performed using a self-writing Matlab code and the LORETA KEY tool.

RESULTS

Compared with the HC group, the HZ patients showed significant altered brain networks. The graph theory analysis revealed that the clustering coefficient and local efficiency of full band in HZ patients were lower than those in HC group (P<0.05). In beta band, the global efficiency and local efficiency of HZ patients group decreased, compared with healthy group (P<0.05). The functional ICA showed that three components showed significant differences between the two groups. In component 2, HZ patients showed excess superior frontal gyrus (BA10) neuro oscillation in delta band and less medial frontal gyrus (BA 11) neuro oscillation in beta and gamma bands than that in HCs. And for component 3, the alpha band of the HZ patients presented increased neuro activities in superior frontal gyrus (BA 11) and decreased neuro activities in occipital lobe (BA 18). In component 4, the inferior frontal gyrus (BA 47) showed excess activity in the left hemisphere and reduced activity in the right hemisphere in delta band, compared with HC group.

CONCLUSION

Altered brain networks exist in resting-state EEG data of patients with acute HZ. The changes of EEG brain networks in HZ patients are characterized by decreased global efficiency and local efficiency in beta band. Moreover, the spontaneous oscillation of some brain regions involving pain management and the connectivity of default mode network changed in HZ patients. Our study provided novel understanding of HZ from an electrophysiological view, and led to converging evidence for treatment of HZ with neural regulation in future.

Single-subject gray matter networks in temporal lobe epilepsy patients with hippocampal sclerosis

OBJECTIVE

Previous studies have demonstrated structural brain network abnormalities in patients with temporal lobe epilepsy (TLE) using cortical thickness or gray matter (GM) volume. However, no studies have applied single-subject GM network analysis. Here, we first applied an analysis of similarity-based single-subject GM networks to individual patients with TLE.

MATERIALS AND METHODS

We recruited 51 patients with TLE and unilateral hippocampal sclerosis (22 left, 29 right TLE) and 51 age- and gender- matched healthy controls. Single-subject structural networks were extracted from three-dimensional T1-weighted magnetic resonance images for each subject. In this method, nodes were defined as small cortical regions and edges representing connecting regions that have high statistical similarity. The constructed graphs were analyzed using the graph theoretical approach. The following global and local network properties were calculated: betweenness centrality, clustering coefficient, and characteristic path length. In addition, small world properties (normalized path length λ, normalized clustering coefficient γ, and small-world network value σ) were obtained and compared with those for the controls.

RESULTS

Although the small-world configurations were retained, impaired global clustering coefficient was observed in left and right TLE. At a regional level, patients with left TLE showed a widespread decrease of the clustering coefficient beyond the ipsilateral temporal lobe and a decreased characteristic path length in the ipsilateral temporal pole. On the other hand, patients with right TLE showed a localized decrease of the clustering coefficient in the ipsilateral temporal lobe.

CONCLUSIONS

Our findings suggest that global and local network properties disrupted and moved toward randomized networks in TLE patients in comparison to controls. This network alteration was more extensive in left TLE than in right TLE patients. Single-subject GM networks may contribute to a better understanding of the pathophysiology of TLE.

Disturbance of functional and effective connectivity of the salience network involved in attention deficits in right temporal lobe epilepsy

The salience network (SN) acts as a switch that generates transient control signals to regulate the executive control network (ECN) and the default mode network (DMN) and has been implicated in cognitive processes. Temporal lobe epilepsy (TLE) is usually accompanied by different types of cognitive deficits, but whether it is associated with dysfunctional connectivity of the SN remains unknown. To address this, thirty-six patients with right TLE (rTLE) and thirty-six healthy controls (HCs) were recruited for the present study. All of the participants were subjected to attention network test (ANT) and resting-state functional resonance imaging (rs-fMRI) scanning. The patient group showed deficits in attention performance. Moreover, the functional connectivity (FC) and effective connectivity (EC) were analyzed based on key SN hubs (the anterior cingulate cortex (ACC) and the bilateral anterior insula (AI)). When compared with those in the HC group, the ACC showed increased FC with the left middle frontal gyrus and the left precentral gyrus, and the right AI showed decreased FC with the right precuneus and the right superior occipital gyrus in the patient group. The EC analysis revealed an increased inflow of information from the left middle temporal gyrus to the ACC and the right AI and an increased outflow of information from the bilateral AI to the left middle frontal gyrus. Furthermore, in the correlation analysis, the abnormal EC from the right AI to the left middle temporal gyrus was positively correlated with the executive control effect. These findings demonstrated aberrant modulation of the SN in rTLE, which was particularly characterized by dysfunctional connectivity between the SN and key brain regions in the DMN and ECN. Elucidation of this effect may further contribute to the comprehensive understanding of the neural mechanisms of the SN in regard to attention deficits in patients with TLE.

Aberrant cerebral intrinsic activity and cerebro-cerebellar functional connectivity in right temporal lobe epilepsy: a resting-state functional MRI study

OBJECTIVE

Numerous neuroimaging studies have demonstrated that functional brain aberrations are associated with cognitive impairments in temporal lobe epilepsy (TLE). Here, we aimed to investigate the neural substrates of attention deficits by combining assessment of regional intrinsic brain activities with large-scale functional connectivity in patients with right TLE (rTLE).

METHODS

Thirty-five patients with rTLE and 33 matched healthy controls were recruited. All participants completed the Attention Network Test (ANT) and resting-sate functional MRI (rs-fMRI) scans. The z-standardized fractional amplitude of the low-frequency fluctuation (zfALFF) approach was applied to evaluate the brain's intrinsic activity. The cerebral regions with significant zfALFF values were selected as seeds for subsequent functional connectivity analyses. A correlation analysis was performed between functional activity and clinical variables.

RESULTS

Compared with the healthy control group, the patients showed decreased zfALFF in the right inferior temporal gyrus and bilateral superior parietal gyrus, and the right inferior temporal gyrus exhibited increased functional connectivity with the bilateral cerebellum-6/vermis-6 and decreased functional connectivity with right superior frontal gyrus. The ANT indicated that the rTLE group exhibited attention deficits. Furthermore, a positive correlation was found between the zfALFF value of the left superior parietal gyrus and alerting performance, while a negative correlation between the zfALFF value of the right superior parietal gyrus and disease duration.

CONCLUSION

This study demonstrated aberrant intrinsic cerebral activity and functional connectivity in the whole brain network, which may act as responsible and compensatory factors in attention deficits, especially further profoundly illuminated the compensatory role of cerebellum in patients with rTLE.

Alterations of core structural network connectome associated with suicidal ideation in major depressive disorder patients

Suicide ideation (SI) is a most high-risk clinical sign for major depressive disorder (MDD). However, whether the rich-club network organization as a core structural network is associated with SI and how the related neural circuits are distributed in MDD patients remain unknown. Total 177 participants including 69 MDD patients with SI (MDDSI), 58 MDD without SI (MDDNSI) and 50 cognitively normal (CN) subjects were recruited and completed neuropsychological tests and diffusion-tensor imaging scan. The rich-club organization was identified and the global and regional topological properties of structural networks, together with the brain connectivity of specific neural circuit architectures, were analyzed. Further, the support vector machine (SVM) learning was applied in classifying MDDSI or MDDNSI from CN subjects. MDDSI and MDDNSI patients both exhibited disrupted rich-club organizations. However, MDDSI patients showed that the differential network was concentrated on the non-core low-level network and significantly destroyed betweeness centrality was primarily located in the regional non-hub regions relative to MDDNSI patients. The differential structural network connections involved the superior longitudinal fasciculus and the corpus callosum were incorporated in the cognitive control circuit and default mode network. Finally, the feeder serves as a potentially powerful indicator for distinguishing MDDSI patients from MDDNSI or CN subjects. The altered rich-club organization provides new clues to understand the underlying pathogenesis of MDD patients, and the feeder was useful as a diagnostic neuroimaging biomarker for differentiating MDD patients with or without SI.

Comparison of topological properties of functional brain networks with graph theory in temporal lobe epilepsy with different duration of disease

Background

Our study was performed to measure the alterations in topological properties of the functional brain network of temporal lobe epilepsy (TLE) at different durations, exploring the potential progression and neuropathophysiological mechanisms of TLE.

Methods

Fifty-eight subjects, including 17 TLE patients with a disease duration of ≤5 years (TLE-SD), 20 TLE patients with a disease duration of >5 years (TLE-LD), and 21 healthy controls firstly underwent the Attention Network Test (ANT) to assess the alertness function and received the resting-state functional magnetic resonance imaging (rs-fMRI). Next, a functional brain network was set up, and then the related graph of theoretical network analysis was conducted. Finally, the correlation between network property and the neuropsychological score was analyzed.

Results

The global and local efficiencies of functional brain networks in TLE-SD patients significantly decreased and tended toward random alterations. Also, the degree centrality (DC) and nodal efficiency (Ne) in right medial pre-frontal thalamus (mPFtha) and right rostral temporal thalamus (rTtha) of TLE-SD patients significantly reduced. Further analysis showed that alertness was positively associated with the characteristic path length but negatively related to the global and local efficiencies in TLE-SD patients; alertness was negatively related to the Ne of mPFtha in TLE-LD patients.

Conclusions

Our study showed that the functional brain network of TLE patients might undergo compensatory reorganization as the disease progresses, which provides useful insights into the progression and mechanism of TLE.

Aberrant basal ganglia-thalamo-cortical network topology in juvenile absence epilepsy: A resting-state EEG-fMRI study

PURPOSE

The underlying pathophysiology of juvenile absence epilepsy (JAE) is unclear. Since cortical and subcortical brain regions are thought to be altered in genetic generalized epilepsy, the present study examined the resting-state functional network topology of the same regions in JAE.

METHODS

Electroencephalography and functional magnetic resonance imaging (EEG-fMRI) were performed on 18 JAE patients and 28 healthy controls (HCs). The topology of functional networks was analyzed using the graph-theoretic method. Both global and nodal network parameters were calculated, and parameters differing significantly between the two groups were correlated with clinical variables.

RESULTS

Both JAE patients and HCs had small-world functional network topological architectures. However, JAE patients showed higher values for the global parameters of clustering coefficient (Cp) and normalized characteristic path length (Lambda). At the nodal level, patients exhibited greater centrality at widespread cortices, including the left superior parietal gyrus, right superior temporal gyrus, right orbital part of middle frontal gyrus and bilateral supplementary motor area. Conversely, patients showed decreased nodal centrality predominantly in the limbic network, left thalamus and right caudate nucleus. Degree centrality in the right hippocampus and betweenness centrality in the right caudate nucleus positively correlated with epilepsy duration.

CONCLUSION

The global functional network of JAE shows small-world properties, but tends to be regular with higher segregation and lower integration. Regions in the basal ganglia-thalamo-cortical network have aberrant nodal centrality. The hippocampus and caudate nucleus may reorganize as epilepsy progresses. Our findings indicate the pathogenesis and compensatory mechanisms to seizure attacks and cognitive deficits of JAE.

Altered White Matter Structural Network in Frontal and Temporal Lobe Epilepsy: A Graph-Theoretical Study

Temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) are the largest subgroup of partial epilepsy, and focal cortical dysplasias (FCDs) are highly epileptogenic brain lesions and are a frequent cause for antiepileptic drug (AED)-resistant focal epilepsies that mostly occur in the temporal and frontal lobes. We performed a graph-theoretical study based on the diffusion tensor imaging (DTI) data of patients with FLE or TLE caused by FCDs or lesions with high suspicion of FCDs and evaluated their cognitive function by the Chinese version of the Montreal Cognitive Assessment-Basic (MoCA-BC). The construction of the white matter structural network and graph-theoretical analysis was performed by Pipeline for Analysing Brain Diffusion Images (PANDA) and Graph-theoretical Network Analysis (GRETNA). We used the nonparametric analysis of covariance to compare the differences in diffusion metrics, network attributes and nodal attributes among FLE, TLE, and healthy control (HC) groups and then performed post hoc pairwise comparisons. Nonparametric Spearman partial correlation analysis was performed to analyse the correlation of network attributes with the age of onset, duration of disease, and MoCA-BC scores in patients with FLE and TLE. The results showed that the white matter structural network in patients with FLE and TLE was impaired in a more extensive set of regions than the FCD location. The similarities in white matter alterations between FLE and TLE suggested that their epileptogenic network might affect the fronto-temporal white matter tracts and thalamo-occipital connections, which might be responsible for the overlapping cognitive deficits in FLE and TLE. The white matter impairments in patients with FLE were more severe than those in patients with TLE, which might be explained by more affected nodes in the areas of DMN in patients with FLE.

Disrupted functional network in patients with temporal lobe epilepsy with impaired alertness

Cognitive impairment is common in patients with temporal lobe epilepsy (TLE). Alertness is an important subfunction of cognition, but it is poorly understood in TLE. We hypothesized that disruptions to underlying brain networks may affect alertness in patients with TLE. Patients with unilateral TLE were grouped into low-alertness and high-alertness groups, and they were matched with healthy controls (HCs) (n = 20 each). Functional magnetic resonance imaging (fMRI) was used to construct functional brain networks, and graph theory was used to identify topological parameters of the networks. At the global level, patients with low alertness had networks with less small-worldness and less normalized clustering than HCs. At the nodal level, patients with low alertness exhibited decreased centrality of the bilateral parahippocampal gyrus compared with HCs and increased centrality of the right postcentral gyrus compared with patients with high alertness. This study reveals a decreased separation, tending toward randomization, of the functional network in patients with TLE with impaired alertness. Our results also suggest that the parahippocampal gyrus may contribute to impaired alertness and the right postcentral gyrus plays an important role in the modulation of alertness in patients with TLE.

Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness

BACKGROUND

To date, no functional MRI (fMRI) studies have focused on brain entropy in right temporal lobe epilepsy (rTLE) patients. Here, we characterized brain entropy (BEN) alterations in patients with rTLE using resting-state functional MRI(rs-fMRI) and explored the relationship between BEN and alertness.

METHOD

Thirty-one rTLE patients and 33 controls underwent MRI scanning to investigate differences in BEN and resting-state functional connectivity (rs-FC) in regions of interest (ROIs) between patients and controls. Correlation analyses were performed to examine relationships between the BEN of each ROI and alertness reaction times (RTs) in rTLE patients.

RESULTS

Compared with controls, the BEN of rTLE patients was significantly increased in the right middle temporal gyrus, inferior temporal gyrus, and other regions of the left hemisphere and significantly decreased in the right middle frontal gyrus and left supplementary motor area (p < .05). The rs-FCs between the ROIs (at p < .01, with the left superior parietal lobule and right precentral gyrus defined as ROI1 and ROI2, respectively) and the whole brain showed an increasing trend in rTLE patients. In addition, the BEN of ROI2 was associated with the intrinsic alertness and phasic alertness RTs of patients with rTLE.

CONCLUSIONS

Our findings suggest that BEN is altered in patients with rTLE and that decreased BEN in the right precentral gyrus is positively related to intrinsic and phasic alertness; the abnormal FC in the brain regions with altered entropy suggests a reconstruction of brain functional connectivity. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to TLE.

Understanding white matter structural connectivity differences between cognitively impaired and nonimpaired active professional fighters

Long-term traumatic brain injury due to repeated head impacts (RHI) has been shown to be a risk factor for neurodegenerative disorders, characterized by a loss in cognitive performance. Establishing the correlation between changes in the white matter (WM) structural connectivity measures and neuropsychological test scores might help to identify the neural correlates of the scores that are used in daily clinical setting to investigate deficits due to repeated head blows. Hence, in this study, we utilized high angular diffusion MRI (dMRI) of 69 cognitively impaired and 70 nonimpaired active professional fighters from the Professional Fighters Brain Health Study, and constructed structural connectomes to understand: (a) whether there is a difference in the topological WM organization between cognitively impaired and nonimpaired active professional fighters, and (b) whether graph-theoretical measures exhibit correlations with neuropsychological scores in these groups. A dMRI derived structural connectome was constructed for every participant using brain regions defined in AAL atlas as nodes, and the product of fiber number and average fractional anisotropy of the tracts connecting the nodes as edges. Our study identified a topological WM reorganization due to RHI in fighters prone to cognitive decline that was correlated with neuropsychological scores. Furthermore, graph-theoretical measures were correlated differentially with neuropsychological scores between groups. We also found differentiated WM connectivity involving regions of hippocampus, precuneus, and insula within our cohort of cognitively impaired fighters suggesting that there is a discernible WM topological reorganization in fighters prone to cognitive decline.

Structural alterations of the brain preceded functional alterations in major depressive disorder patients: Evidence from multimodal connectivity

BACKGROUND

Recent studies showed that major depressive disorder (MDD) has been involved in abnormal functional and structural connections in specific brain regions. However, comprehensive researches on MDD-related alterations in the topological organization of brain functional and structural networks are still limited.

METHODS

Functional network (FN) was constructed from resting-state functional MRI temporal series correlations and structural network (SN) was established by Diffusion tensor imaging (DTI) data in 58 MDD patients and 71 healthy controls (HC). The measurements of the network properties were calculated for two networks respectively. Correlations were conducted between altered network parameters and Hamilton depression scale (HAMD) score. Additionally, network resilient analysis were conducted on FN and SN.

RESULTS

The losses of small-worldness charateristics and the decline of nodal efficiency across FN and SN were found in MDD patients. Based on network-based statistic (NBS) approach, the decreased connections in MDD patients were mainly found in the superior occipital gyrus, superior temporal gyrus for FN and SN, while the increased connections were distributed in putamen, superior frontal gyrus only for SN. Compared with the FN, the SN showed less resilient to targeted or random node failure. Besides, altered edges in NBS and regions with decreased nodal efficiency were negatively associated with HAMD score in MDD patients.

LIMITATIONS

The samples size is small and most of the MDD patients take different antidepressant medications.

CONCLUSIONS

Alterations of SN in the brain of MDD patients preceded that of FN to some extent, and reorganization of the brain network was a mechanism which compensated for functional and structural alterations during disease progression.

Models of Network Spread and Network Degeneration in Brain Disorders

Network analysis can provide insight into key organizational principles of brain structure and help identify structural changes associated with brain disease. Though static differences between diseased and healthy networks are well characterized, the study of network dynamics, or how brain networks change over time, is increasingly central to understanding ongoing brain changes throughout disease. Accordingly, we present a short review of network models of spread, network dynamics, and network degeneration. Borrowing from recent suggestions, we divide this review into two processes by which brain networks can change: dynamics on networks, which are functional and pathological consequences taking place atop a static structural brain network; and dynamics of networks, which constitutes a changing structural brain network. We focus on diffusion magnetic resonance imaging-based structural or anatomic connectivity graphs. We address psychiatric disorders like schizophrenia; developmental disorders like epilepsy; stroke; and Alzheimer's disease and other neurodegenerative diseases.

Progressive topological disorganization of brain network in focal epilepsy

OBJECTIVE

Increasing evidence has suggested that epilepsy is a network disease. Graph theory is a mathematical tool that allows for the analysis and quantification of the brain network. We aimed to evaluate the influences of duration of epilepsy on the topological organization of brain network in focal epilepsy patients with normal MRI using the graph theoretical analysis based on diffusion tenor imaging.

METHODS

We prospectively enrolled 66 patients with focal epilepsy (18/66 patients were newly diagnosed) and 84 healthy subjects. All of the patients with epilepsy had normal MRI on visual inspection. All of the subjects underwent diffusion tensor imaging that was analyzed using graph theory to obtain network measures.

RESULTS

The measures of characteristic path length and small-worldness in the patients with focal epilepsy were significantly decreased, even after multiple corrections (P < .01). Moreover, the measures including mean clustering coefficient and global efficiency in the patients with epilepsy had strong tendency to decrease compared to those in healthy subjects (P = .0153 and P = .0138, respectively). When comparing the measures among the patients with newly diagnosed/chronic epilepsy and healthy subjects using ANOVA, the characteristic path length (P = .006), small-worldness (P = .032), and global efficiency (P = .004) were significantly different. In addition, the duration of epilepsy was negatively correlated with global efficiency (r = -.249, P = .0454).

CONCLUSIONS

We newly found a progressive topological disorganization of the brain network in focal epilepsy. In addition, we demonstrated disrupted topological organization in focal epilepsy, shifting toward a more random state.