Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis

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.

Drug-resistant juvenile myoclonic epilepsy: A literature review

The ILAE's Task Force on Nosology and Definitions revised in 2022 its definition of juvenile myoclonic epilepsy (JME), the most common idiopathic generalized epilepsy disorder, but this definition may well change again in the future. Although good drug response could almost be a diagnostic criterion for JME, drug resistance (DR) is observed in up to a third of patients. It is important to distinguish this from pseudoresistance, which is often linked to psychosocial problems or psychiatric comorbidities. After summarizing these aspects and the various definitions applied to JME, the present review lists the risk factors for DR-JME that have been identified in numerous studies and meta-analyses. The factors most often cited are absence seizures, young age at onset, and catamenial seizures. By contrast, photosensitivity seems to favor good treatment response, at least in female patients. Current hypotheses on DR mechanisms in JME are based on studies of either simple (e.g., cortical excitability) or more complex (e.g., anatomical and functional connectivity) neurophysiological markers, bearing in mind that JME is regarded as a neural network disease. This research has revealed correlations between the intensity of some markers and DR, and above all shed light on the role of these markers in associated neurocognitive and neuropsychiatric disorders in both patients and their siblings. Studies of neurotransmission have mainly pointed to impaired GABAergic inhibition. Genetic studies have generally been inconclusive. Increasing restrictions have been placed on the use of valproate, the standard antiseizure medication for this syndrome, owing to its teratogenic and developmental risks. Levetiracetam and lamotrigine are prescribed as alternatives, as is vagal nerve stimulation, and there are several other promising antiseizure drugs and neuromodulation methods. The development of better alternative treatments is continuing to take place alongside advances in our knowledge of JME, as we still have much to learn and understand.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

Differences in the Default Mode Network of Temporal Lobe Epilepsy Patients Detected by Hilbert-Huang Transform Based Dynamic Functional Connectivity

Resting-state functional connectivity, constructed via functional magnetic resonance imaging, has become an essential tool for exploring brain functions. Aside from the methods focusing on the static state, investigating dynamic functional connectivity can better uncover the fundamental properties of brain networks. Hilbert-Huang transform (HHT) is a novel time-frequency technique that can adapt to both non-linear and non-stationary signals, which may be an effective tool for investigating dynamic functional connectivity. To perform the present study, we investigated time-frequency dynamic functional connectivity among 11 brain regions of the default mode network by first projecting the coherence into the time and frequency domains, and subsequently by identifying clusters in the time-frequency domain using k-means clustering. Experiments on 14 temporal lobe epilepsy (TLE) patients and 21 age and sex-matched healthy controls were performed. The results show that functional connections in the brain regions of the hippocampal formation, parahippocampal gyrus, and retrosplenial cortex (Rsp) were reduced in the TLE group. However, the connections in the brain regions of the posterior inferior parietal lobule, ventral medial prefrontal cortex, and the core subsystem could hardly be detected in TLE patients. The findings not only demonstrate the feasibility of utilizing HHT in dynamic functional connectivity for epilepsy research, but also indicate that TLE may cause damage to memory functions, disorders of processing self-related tasks, and impairment of constructing a mental scene.

Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy

Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ-band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ-band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de-/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME.

Understanding frontal lobe function in epilepsy: Juvenile myoclonic epilepsy vs. frontal lobe epilepsy

AIM

To compare neuropsychological function in juvenile myoclonic epilepsy (JME) and frontal lobe epilepsy (FLE) since frontal circuitry is involved in both conditions. By drawing on previously theory-guided hypotheses and findings, a particular emphasis is placed on the way different cognitive-pathophysiological mechanisms act upon to produce frontal dysfunction in JME (frontal-executive and attention-related problems: vigilance, reaction times, processing speed, and response inhibition) and in FLE (reflecting the coproduct of the functional deficit zone), respectively.

METHODS

A total of 16 patients with JME, 34 patients with FLE, and 48 normal controls, all matched for age and education, were administered a comprehensive battery of tests to assess frontal-executive functions, as well as attention, memory, and learning domains. Participants did not take medications other than antiepileptics or have a psychiatric history.

RESULTS

Patients with FLE overall showed worse neuropsychological performance compared to both JME and HCs. With respect to JME, patients with FLE did significantly worse in measures of verbal and nonverbal executive function, short-term-, and long-term- auditory-verbal memory and learning, immediate and delayed episodic recall, visual attention and motor function, visuo-motor coordination and psychomotor speed, speed of visual information processing, and vocabulary. Patients with JME performed significantly worse compared to FLE only in associative semantic processing, while the former outperformed all groups in vocabulary, visuomotor coordination, and psychomotor speed.

CONCLUSION

We suggest that selective impairments of visual- and mostly auditory-speed of information processing, vigilance, and response inhibition may represent a salient neuropsychological feature in JME. These findings suggest the existence of an aberrantly working executive-attention system, secondary to pathological reticulo-thalamo-cortical dynamics. Contrariwise, cortically (frontal and extra-frontal) and subcortically induced malfunction in FLE is determined by the functional deficit zone i.e., the ensemble of cortical and subcortical areas that are functionally abnormal between seizures.

Altered Structural Brain Networks in Refractory and Nonrefractory Idiopathic Generalized Epilepsy

Introduction: Idiopathic generalized epilepsy (IGE) is a collection of generalized nonlesional epileptic network disorders. Around 20-40% of patients with IGE are refractory to antiseizure medication, and mechanisms underlying refractoriness are poorly understood. Here, we characterize structural brain network alterations and determine whether network alterations differ between patients with refractory and nonrefractory IGE. Methods: Thirty-three patients with IGE (10 nonrefractory and 23 refractory) and 39 age- and sex-matched healthy controls were studied. Network nodes were segmented from T1-weighted images, while connections between these nodes (edges) were reconstructed from diffusion magnetic resonance imaging (MRI). Diffusion networks of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and streamline count (Count) were studied. Differences between all patients, refractory, nonrefractory, and control groups were computed using network-based statistics. Nodal volume differences between groups were computed using Cohen's d effect size calculation. Results: Patients had significantly decreased bihemispheric FA and Count networks and increased MD and RD networks compared with controls. Alterations in network architecture, with respect to controls, differed depending on treatment outcome, including predominant FA network alterations in refractory IGE and increased nodal volume in nonrefractory IGE. Diffusion MRI networks were not influenced by nodal volume. Discussion: Although a nonlesional disorder, patients with IGE have bihemispheric structural network alterations that may differ between patients with refractory and nonrefractory IGE. Given that distinct nodal volume and FA network alterations were observed between treatment outcome groups, a multifaceted network analysis may be useful for identifying imaging biomarkers of refractory IGE.

Distributed source localization of epileptiform discharges in juvenile myoclonic epilepsy: Standardized low-resolution brain electromagnetic tomography (sLORETA) Study

Juvenile myoclonic epilepsy (JME) is a common generalized epilepsy syndrome considered the prototype of idiopathic generalized epilepsy. To date, generalized and focal seizures have been the fundamental concepts for classifying seizure types. In several studies, focal features of JME have been reported predominantly in the frontal lobe. However, results in previous studies are inconsistent. Therefore, we investigated the origin of epileptiform discharges in JME. We performed electroencephalography source localization using a distributed model with standardized low-resolution brain electromagnetic tomography. In 20 patients with JME, standardized low-resolution brain electromagnetic tomography images corresponding to the midpoint of the ascending phase and the negative peak of epileptiform discharges were obtained from a total of 362 electroencephalography epochs (181 epochs at each timepoint). At the ascending phase, the maximal current source density was located in the frontal lobe (58.6%), followed by the parietal (26.5%) and occipital lobes (8.8%). At the negative peak, the maximal current source density was located in the frontal lobe (69.1%), followed by the parietal (11.6%) and occipital lobes (9.4%). In the ascending phase, 41.4% of discharges were located outside the frontal lobe, and 30.9% were in the negative peak. Frontal predominance of epileptiform discharges was observed; however, source localization extending to various cortical regions also was identified. This widespread pattern was more prominent in the ascending phase (P = .038). The study results showed that JME includes widespread cortical regions over the frontal lobe. The current concept of generalized epilepsy and pathophysiology in JME needs further validation.

Correlations Between Structural Brain Abnormalities, Cognition and Electroclinical Characteristics in Patients With Juvenile Myoclonic Epilepsy

Objective

To explore the structural brain abnormality and its relationship with neuropsychological disorders and electroclinical characteristics in juvenile myoclonic epilepsy (JME) patients.

Methods

Sixty-seven patients diagnosed with JME and 56 healthy controls were enrolled. All subjects underwent MRI using T1-weighted 3D brain structural images with 1 mm thickness. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) analyses were performed. They also underwent a series of neuropsychological tests to assess cognitive function. The correlation analyses were conducted between structural changes, neuropsychological outcomes, and electroclinical features.

Results

The gray matter concentration (GMC) was decreased in the bilateral pre-central and post-central gyrus, right anterior cingulate gyrus, left posterior orbital region, bilateral occipital regions, bilateral hippocampus and bilateral caudate nucleus in the JME groups (corrected P < 0.05). The evaluation of gray matter volume (GMV) showed significant decrease respectively in bilateral pre-central and post-central gyrus, left paracentral lobule, left orbital gyrus, left amygdala, left basal ganglia and left thalamus of JME patients (P < 0.05). The cortex thicknesses of the right inferior temporal gyrus, right insular gyrus, and right cingulate gyrus had negative correlations with the disease duration significantly. At the same time, the whole-brain white matter volume was positively associated with the course of the disease (P < 0.05). Patients with persistent abnormal EEG discharges had significantly less whole-brain gray matter volume than JME patients with normal EEG (P = 0.03). Correlation analyses and linear regression analyses showed that, in addition to the gray matter volumes of frontal and parietal lobe, the temporal lobe, as well as the basal ganglia and thalamus, were also significantly correlated with neuropsychological tests' results (P < 0.05).

Conclusion

The JME patients showed subtle structural abnormalities in multiple brain regions that were not only limited to the frontal lobe but also included the thalamus, basal ganglia, parietal lobe, temporal lobe and some occipital cortex, with significant involvement of the primary somatosensory cortex and primary motor cortex. And we significantly demonstrated a correlation between structural abnormalities and cognitive impairment. In addition, the course of disease and abnormal discharges had a specific negative correlation with the structural changes.

Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy

Neuroimaging studies have shown that juvenile myoclonic epilepsy (JME) is characterized by impaired brain networks. However, few studies have investigated the potential disruptions in rich‐club organization—a core feature of the brain networks. Moreover, it is unclear how structure–function relationships dynamically change over time in JME. Here, we quantify the anatomical rich‐club organization and dynamic structural and functional connectivity (SC–FC) coupling in 47 treatment‐naïve newly diagnosed patients with JME and 40 matched healthy controls. Dynamic functional network efficiency and its association with SC–FC coupling were also calculated to examine the supporting of structure–function relationship to brain information transfer. The results showed that the anatomical rich‐club organization was disrupted in the patient group, along with decreased connectivity strength among rich‐club hub nodes. Furthermore, reduced SC–FC coupling in rich‐club organization of the patients was found in two functionally independent dynamic states, that is the functional segregation state (State 1) and the strong somatomotor‐cognitive control interaction state (State 5); and the latter was significantly associated with disease severity. In addition, the relationships between SC–FC coupling of hub nodes connections and functional network efficiency in State 1 were found to be absent in patients. The aberrant dynamic SC–FC coupling of rich‐club organization suggests a selective influence of densely interconnected network core in patients with JME at the early phase of the disease, offering new insights and potential biomarkers into the underlying neurodevelopmental basis of behavioral and cognitive impairments observed in JME.

Sex-specific disease modifiers in juvenile myoclonic epilepsy

Juvenile myoclonic epilepsy (JME) is a common idiopathic generalised epilepsy with variable seizure prognosis and sex differences in disease presentation. Here, we investigate the combined epidemiology of sex, seizure types and precipitants, and their influence on prognosis in JME, through cross-sectional data collected by The Biology of Juvenile Myoclonic Epilepsy (BIOJUME) consortium. 765 individuals met strict inclusion criteria for JME (female:male, 1.8:1). 59% of females and 50% of males reported triggered seizures, and in females only, this was associated with experiencing absence seizures (OR = 2.0, p < 0.001). Absence seizures significantly predicted drug resistance in both males (OR = 3.0, p = 0.001) and females (OR = 3.0, p < 0.001) in univariate analysis. In multivariable analysis in females, catamenial seizures (OR = 14.7, p = 0.001), absence seizures (OR = 6.0, p < 0.001) and stress-precipitated seizures (OR = 5.3, p = 0.02) were associated with drug resistance, while a photoparoxysmal response predicted seizure freedom (OR = 0.47, p = 0.03). Females with both absence seizures and stress-related precipitants constitute the prognostic subgroup in JME with the highest prevalence of drug resistance (49%) compared to females with neither (15%) and males (29%), highlighting the unmet need for effective, targeted interventions for this subgroup. We propose a new prognostic stratification for JME and suggest a role for circuit-based risk of seizure control as an avenue for further investigation.

Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies

Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunction are increasingly recognized as core disease dimensions and can affect patient well-being, sometimes more than the seizures themselves. Connectome-based approaches hold immense promise for revealing mechanisms that contribute to dysfunction and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first discuss work in drug-resistant epilepsy syndromes, that is, temporal lobe epilepsy, related to mesiotemporal sclerosis (TLE), and extratemporal epilepsy (ETE), related to malformations of cortical development. While these are traditionally conceptualized as ‘focal’ epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We also review work in idiopathic generalized epilepsy (IGE), a subset of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome-specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research.

Epilepsy is increasingly recognized as a network disorder characterized by recurrent seizures as well as broad-ranging cognitive difficulties and affective dysfunction. Our manuscript reviews recent literature highlighting brain network substrates of cognitive and affective dysfunction in common epilepsy syndromes, namely temporal lobe epilepsy secondary to mesiotemporal sclerosis, extratemporal epilepsy secondary to malformations of cortical development, and idiopathic generalized epilepsy syndromes arising from subcortico-cortical pathophysiology. We discuss prior work that has indicated both shared and distinct brain network signatures of cognitive and affective dysfunction across the epilepsy spectrum, improves our knowledge of structure-function links and interindividual heterogeneity, and ultimately aids screening and monitoring of therapeutic strategies.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

White matter structural connectivity as a biomarker for detecting juvenile myoclonic epilepsy by transferred deep convolutional neural networks with varying transfer rates

Objective. By detecting abnormal white matter changes, diffusion magnetic resonance imaging (MRI) contributes to the detection of juvenile myoclonic epilepsy (JME). In addition, deep learning has greatly improved the detection performance of various brain disorders. However, there is almost no previous study effectively detecting JME by a deep learning approach with diffusion MRI.Approach. In this study, the white matter structural connectivity was generated by tracking the white matter fibers in detail based on Q-ball imaging and neurite orientation dispersion and density imaging. Four advanced deep convolutional neural networks (CNNs) were deployed by using the transfer learning approach, in which the transfer rate searching strategy was proposed to achieve the best detection performance.Main results. Our results showed: (a) Compared to normal control, the white matter' neurite density of JME was significantly decreased. The most significantly abnormal fiber tracts between the two groups were found to be cortico-cortical connection tracts. (b) The proposed transfer rate searching approach contributed to find each CNN's best performance, in which the best JME detection accuracy of 92.2% was achieved by using the Inception_resnet_v2 network with a 16% transfer rate.Significance. The results revealed: (a) Through detection of the abnormal white matter changes, the white matter structural connectivity can be used as a useful biomarker for detecting JME, which helps to characterize the pathophysiology of epilepsy. (b) The proposed transfer rate, as a new hyperparameter, promotes the CNNs transfer learning performance in detecting JME.

Functional network topology in drug resistant and well-controlled idiopathic generalized epilepsy: a resting state functional MRI study

Despite an increasing number of drug treatment options for people with idiopathic generalized epilepsy (IGE), drug resistance remains a significant issue and the mechanisms underlying it remain poorly understood. Previous studies have largely focused on potential cellular or genetic explanations for drug resistance. However, epilepsy is understood to be a network disorder and there is a growing body of literature suggesting altered topology of large-scale resting networks in people with epilepsy compared with controls. We hypothesize that network alterations may also play a role in seizure control. The aim of this study was to compare resting state functional network structure between well-controlled IGE (WC-IGE), drug resistant IGE (DR-IGE) and healthy controls. Thirty-three participants with IGE (10 with WC-IGE and 23 with DR-IGE) and 34 controls were included. Resting state functional MRI networks were constructed using the Functional Connectivity Toolbox (CONN). Global graph theoretic network measures of average node strength (an equivalent measure to mean degree in a network that is fully connected), node strength distribution variance, characteristic path length, average clustering coefficient, small-world index and average betweenness centrality were computed. Graphs were constructed separately for positively weighted connections and for absolute values. Individual nodal values of strength and betweenness centrality were also measured and ‘hub nodes’ were compared between groups. Outcome measures were assessed across the three groups and between both groups with IGE and controls. The IGE group as a whole had a higher average node strength, characteristic path length and average betweenness centrality. There were no clear differences between groups according to seizure control. Outcome metrics were sensitive to whether negatively correlated connections were included in network construction. There were no clear differences in the location of ‘hub nodes’ between groups. The results suggest that, irrespective of seizure control, IGE interictal network topology is more regular and has a higher global connectivity compared to controls, with no alteration in hub node locations. These alterations may produce a resting state network that is more vulnerable to transitioning to the seizure state. It is possible that the lack of apparent influence of seizure control on network topology is limited by challenges in classifying drug response. It is also demonstrated that network topological features are influenced by the sign of connectivity weights and therefore future methodological work is warranted to account for anticorrelations in graph theoretic studies.

Epilepsy enhance global efficiency of language networks in right temporal lobe gliomas

Aims

We analyzed the resting state functional magnetic resonance images to investigate the alterations of neural networks in patients with glioma‐related epilepsy (GRE).

Methods

Fifty‐six patients with right temporal lower‐grade glioma were divided into GRE (n = 28) and non‐GRE groups. Twenty‐eight healthy subjects were recruited after matching age, sex, and education level. Sensorimotor, visual, language, and left executive control networks were applied to generate functional connectivity matrices, and their topological properties were investigated.

Results

No significant alterations in functional connectivity were found. The least significant discovery test revealed differences only in the language network. The shortest path length, clustering coefficient, local efficiency, and vulnerability were greater in the non‐GRE group than in the other groups. The nodal efficiencies of two nodes (mirror areas to Broca and Wernicke) were weaker in the non‐GRE group than in the other groups. The node of degree centrality (Broca), nodal local efficiency (Wernicke), and nodal clustering coefficient (temporal polar) were greater in the non‐GRE group than in the healthy group.

Conclusion

Different tumor locations alter different neural networks. Temporal lobe gliomas in the right hemisphere altered the language network. Glioma itself and GRE altered the network in opposing ways in patients with right temporal glioma.

Selective impairment of auditory attention processing in idiopathic generalized epilepsies: Implications for their cognitive pathophysiology

The neuropsychological characteristics of Idiopathic Generalized Epilepsies (IGEs) as a wide syndrome encompassing different clinical entities have been as yet not well understood. We have studied neuropsychological performance in patients suffering Juvenile Myoclonic Epilepsy (JME) and Generalized Tonic Clonic Seizures (IGE-GTCS-only) to provide indirect-cognitive evidence on the pathophysiology of IGE-related neuropsychological dysfunction. Greater arousal-related impairments were expected for the auditory modality, by drawing on previous anatomo-clinical and neuro-evolutionary accounts. We have studied neurocognitive functioning in 26 IGE patients, suffering either JME (n = 16) or IGE-GTCS-only (n = 10), and their healthy counterparts consisted of 26 (18 females) demographically matched participants. IGE patients (JME and IGE-GTCS-only) did worse with respect to HC (healthy controls) in visual- and auditory- speed of information processing (reaction time), auditory-vigilance and -response inhibition, visuo-motor coordination, visual working memory and motor speed, delayed visual recall, immediate- and delayed verbal episodic recall, lexical access and retrieval, semantic associative processing, auditory-verbal memory span and verbal learning. Although both IGE-GTCS-only and JME patients delayed episodic recall was defective, the former did significantly worse. We believe that IGE patients' neuropsychological derailments represent indirect-secondary manifestations of a primary cortical tone deregulation inherent to IGEs' pathophysiology. In particular, IGE patients' worse-dissociated performance in auditory TOVA-also seen previously in TBI and schizophrenia-may implicate a grater vulnerability of the auditory information processing system, as well as a possibly shared cognitive pathophysiological component between IGE and the above nosologies.

Can we predict drug response by functional connectivity in patients with juvenile myoclonic epilepsy?

OBJECTIVES

We investigated functional connectivity based on EEG using graph theoretical analysis in patients with newly diagnosed juvenile myoclonic epilepsy (JME), and whether it could play a role as a biomarker predicting antiepileptic drug (AED) response.

METHODS

We consecutively enrolled 38 patients with JME and 40 normal controls. The initial EEG was undertaken at the time of diagnosis of JME in a drug-naïve state. The second EEG was done after at least 12 months from the time of the initial EEG. We classified the patients with JME into two groups according to AED response at the time of taking the second EEG. We investigated functional connectivity based on graph theoretical analysis using connectivity measures of the coherence and phase locking value.

RESULTS

In the analysis of functional connectivity using coherence as a connectivity measure, the global efficiency and local efficiency in the AED poor responders (N = 4) decreased, whereas the small-worldness index increased. In the analysis of functional connectivity using phase locking value as a connectivity measure, the global efficiency and local efficiency in the AED poor responders decreased. However, in the AED good responders (N = 34), none of the network measures were different from those in healthy controls.

CONCLUSIONS

We newly found that there were significant differences of functional connectivity based on initial EEG according to AED response in the patients with JME. This suggests that brain connectivity could play a role as a new biomarker predicting AED response in patients with JME.

Motor hyperactivation during cognitive tasks: An endophenotype of juvenile myoclonic epilepsy

OBJECTIVE

Juvenile myoclonic epilepsy (JME) is the most common genetic generalized epilepsy syndrome. Myoclonus may relate to motor system hyperexcitability and can be provoked by cognitive activities. To aid genetic mapping in complex neuropsychiatric disorders, recent research has utilized imaging intermediate phenotypes (endophenotypes). Here, we aimed to (a) characterize activation profiles of the motor system during different cognitive tasks in patients with JME and their unaffected siblings, and (b) validate those as endophenotypes of JME.

METHODS

This prospective cross-sectional investigation included 32 patients with JME, 12 unaffected siblings, and 26 controls, comparable for age, sex, handedness, language laterality, neuropsychological performance, and anxiety and depression scores. We investigated patterns of motor system activation during episodic memory encoding and verb generation functional magnetic resonance imaging (fMRI) tasks.

RESULTS

During both tasks, patients and unaffected siblings showed increased activation of motor system areas compared to controls. Effects were more prominent during memory encoding, which entailed hand motion via joystick responses. Subgroup analyses identified stronger activation of the motor cortex in JME patients with ongoing seizures compared to seizure-free patients. Receiver-operating characteristic curves, based on measures of motor activation, accurately discriminated both patients with JME and their siblings from healthy controls (area under the curve: 0.75 and 0.77, for JME and a combined patient-sibling group against controls, respectively; P < .005).

SIGNIFICANCE

Motor system hyperactivation represents a cognitive, domain-independent endophenotype of JME. We propose measures of motor system activation as quantitative traits for future genetic imaging studies in this syndrome.

Interictal structural and functional connectivity in idiopathic generalized epilepsy: A systematic review of graph theoretical studies

The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.

Juvenile myoclonic epilepsy shows increased posterior theta, and reduced sensorimotor beta resting connectivity

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We investigated whole brain source space connectivity in JME using across standard MEG frequency bands.

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Connectivity was increased in posterior theta and alpha bands in JME, and decreased in sensorimotor beta band.

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Our findings highlight altered interactions between posterior networks of arousal and attention and the motor system in JME.

Background

Widespread structural and functional brain network changes have been shown in Juvenile Myoclonic Epilepsy (JME) despite normal clinical neuroimaging. We sought to better define these changes using magnetoencephalography (MEG) and source space connectivity analysis for optimal neurophysiological and anatomical localisation.

Methods

We consecutively recruited 26 patients with JME who underwent resting state MEG recording, along with 26 age-and-sex matched controls. Whole brain connectivity was determined through correlation of Automated Anatomical Labelling (AAL) atlas source space MEG timeseries in conventional frequency bands of interest delta (1−4 Hz), theta (4−8 Hz), alpha (8−13 Hz), beta (13−30 Hz) and gamma (40−60 Hz). We used a Linearly Constrained Minimum Variance (LCMV) beamformer to extract voxel wise time series of ‘virtual sensors’ for the desired frequency bands, followed by connectivity analysis using correlation between frequency- and node-specific power fluctuations, for the voxel maxima in each AAL atlas label, correcting for noise, potentially spurious connections and multiple comparisons.

Results

We found increased connectivity in the theta band in posterior brain regions, surviving statistical correction for multiple comparisons (corrected p < 0.05), and decreased connectivity in the beta band in sensorimotor cortex, between right pre- and post- central gyrus (p < 0.05) in JME compared to controls.

Conclusions

Altered resting-state MEG connectivity in JME comprised increased connectivity in posterior theta – the frequency band associated with long range connections affecting attention and arousal - and decreased beta-band sensorimotor connectivity. These findings likely relate to altered regulation of the sensorimotor network and seizure prone states in JME.

Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy

Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy. It is yet unclear to what extent JME leads to abnormal network activation patterns. Here, we characterized statistical regularities in magnetoencephalograph (MEG) resting-state networks and their differences between JME patients and controls by combining a pairwise maximum entropy model (pMEM) and novel energy landscape analyses for MEG. First, we fitted the pMEM to the MEG oscillatory power in the front-oparietal network (FPN) and other resting-state networks, which provided a good estimation of the occurrence probability of network states. Then, we used energy values derived from the pMEM to depict an energy landscape, with a higher energy state corresponding to a lower occurrence probability. JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta, and gamma bands. Furthermore, simulations of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of energy minima was shortened in JME patients. These network alterations were highlighted by significant classification of individual participants employing energy values as multivariate features. Our findings suggested that JME patients had altered multistability in selective functional networks and frequency bands in the fronto-parietal cortices.

Thalamic nuclei volumes and network in juvenile myoclonic epilepsy

OBJECTIVE

The aim of this study was to investigate the alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with juvenile myoclonic epilepsy (JME) compared to healthy controls.

METHODS

We enrolled 50 patients with JME and 42 healthy controls. We obtained structural volumes of the individual thalamic nuclei based on T1-weighted imaging and performed intrinsic thalamic network analysis using graph theoretical analysis. We analyzed the differences of thalamic nuclei volumes and intrinsic thalamic networks between the patients with JME and healthy controls.

RESULTS

In the patients with JME, there were significant alterations of thalamic nuclei volumes compared to healthy controls. Right laterodorsal and left suprageniculate nuclei volumes were significantly increased (0.0019% vs 0.0014%, P < .0001; 0.0011% vs 0.0008%, P = .0006, respectively), whereas left ventral posterolateral, left ventromedial, and left pulvinar inferior nuclei volumes (0.0572% vs 0.0664%, P = .0001; 0.0013% vs 0.0015%, P = .0002; 0.0120% vs 0.0140%, P < .0001, respectively) were decreased in the patients with JME. Furthermore, the intrinsic thalamic network of the patients with JME was significantly different from that of the healthy controls. The modularity in the patients with JME was significantly increased over that in healthy controls (0.0785 vs 0.0212, P = .039).

CONCLUSION

We found that there were significant alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with JME compared to healthy controls. These findings might contribute to the underlying pathogenesis of in JME.

Cognitive Function in Genetic Generalized Epilepsies: Insights From Neuropsychology and Neuroimaging

Genetic generalized epilepsies (GGE), previously called idiopathic generalized epilepsies, constitute about 20% of all epilepsies, and include childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, and epilepsy with generalized tonic-clonic seizures alone (CAE, JAE, JME, and GGE-GTCS, respectively). GGE are characterized by high heritability, likely underlain by polygenetic mechanisms, which may relate to atypical neurodevelopmental trajectories. Age of onset ranges from pre-school years, for CAE, to early adulthood for GGE-GTCS. Traditionally, GGE have been considered benign, a belief contrary to evidence from neuropsychology studies conducted over the last two decades. In JME, deficits in executive and social functioning are common findings and relate to impaired frontal lobe function. Studies using neuropsychological measures and cognitive imaging paradigms provide evidence for hyperconnectivity between prefrontal and motor cortices, aberrant fronto-thalamo-cortical connectivity, and reduced fronto-cortical and subcortical gray matter volumes, which are associated with altered cognitive performance. Recent research has also identified associations between abnormal hippocampal morphometry and fronto-temporal activation during episodic memory. Longitudinal studies on individuals with newly diagnosed JME have observed cortical dysmaturation, which is paralleled by delayed cognitive development compared to the patients' peers. Comorbidities and cognitive deficits observed in other GGE subtypes, such as visuo-spatial and language deficits in both CAE and JAE, have also been correlated with atypical neurodevelopment. Although it remains unclear whether cognitive impairment profiles differ amongst GGE subtypes, effects may become more pronounced with disease duration, particularly in absence epilepsies. Finally, there is substantial evidence that patients with JME and their unaffected siblings share patterns of cognitive deficits, which is indicative of an underlying genetic etiology (endophenotype), independent of seizures and anti-epileptic medication.

Structural and functional connectivity in newly diagnosed juvenile myoclonic epilepsy

OBJECTIVES

We aimed to evaluate structural and functional connectivity of patients with newly diagnosed juvenile myoclonic epilepsy (JME) compared to healthy subjects.

METHODS

We enrolled 36 patients with a diagnosis of JME, who were newly diagnosed and drug-naïve. They underwent T1-weighted imaging, and structural volumes were calculated using FreeSurfer software. In addition, EEG data were obtained from all of them. Structural and functional connectivity matrices were estimated by calculating the structural volumes and EEG amplitude correlation, respectively. Then, the connectivity measures were calculated using the BRAPH program. We also enrolled healthy subjects to compare its structural and functional connectivity with the patients with JME.

RESULTS

We observed that patients with JME exhibited significantly different functional and structural connectivity compared to healthy control subjects. In the global structural connectivity, global efficiency, and local efficiency, and small-worldness index were decreased, whereas characteristic path length was increased in patients with JME. Betweenness centrality of cingulate, precentral, superior parietal, and superior frontal cortex was increased in patients with JME whereas that of hippocampus was decreased. In the functional connectivity, the betweenness centrality of the fronto-central electrodes was significantly increased.

CONCLUSIONS

This study reports that the structural connectivity and functional connectivity in patients with JME are significantly different from those in healthy control subjects, even those with newly diagnosed drug-naive state. The patients with JME exhibited disrupted topological disorganization of the global brain network and hub reorganization in structural and functional connectivity. These alterations are implicated in the pathogenesis of JME and suggestive of network disease.

Sensorimotor network hypersynchrony as an endophenotype in families with genetic generalized epilepsy: A resting-state functional magnetic resonance imaging study

Recent evidence suggests that three specific brain networks show state-dependent levels of synchronization before, during, and after episodes of generalized spike-wave discharges (GSW) in patients with genetic generalized epilepsy (GGE). Here, we investigate whether synchronization in these networks differs between patients with GGE (n = 13), their unaffected first-degree relatives (n = 17), and healthy controls (n = 18). All subjects underwent two 10-minute simultaneous electroencephalographic-functional magnetic resonance imaging (fMRI) recordings without GSW. Whole-brain data were divided into 90 regions, and blood oxygen level-dependent (BOLD) phase synchrony in a 0.04-0.07-Hz band was estimated between all pairs of regions. Three networks were defined: (1) the network with highest synchrony during GSW events, (2) a sensorimotor network, and (3) an occipital network. Average synchrony (mean node degree) was inferred across each network over time. Notably, synchrony was significantly higher in the sensorimotor network in patients and in unaffected relatives, compared to controls. There was a trend toward higher synchrony in the GSW network in patients and in unaffected relatives. There was no difference between groups for the occipital network. Our findings provide evidence that elevated fMRI BOLD synchrony in a sensorimotor network is a state-independent endophenotype of GGE, present in patients in the absence of GSW, and present in unaffected relatives.

Progressive dissociation of cortical and subcortical network development in children with new-onset juvenile myoclonic epilepsy

OBJECTIVE

Structural and functional magnetic resonance imaging (MRI) studies have consistently documented cortical and subcortical abnormalities in patients with juvenile myoclonic epilepsy (JME). However, little is known about how these structural abnormalities emerge from the time of epilepsy onset and how network interactions between and within cortical and subcortical regions may diverge in youth with JME compared to typically developing children.

METHODS

We examined prospective covariations of volumetric differences derived from high-resolution structural MRI during the first 2 years of epilepsy diagnosis in a group of youth with JME (n = 21) compared to healthy controls (n = 22). We indexed developmental brain changes using graph theory by computing network metrics based on the correlation of the cortical and subcortical structural covariance near the time of epilepsy and 2 years later.

RESULTS

Over 2 years, normally developing children showed modular cortical development and network integration between cortical and subcortical regions. In contrast, children with JME developed a highly correlated and less modular cortical network, which was atypically dissociated from subcortical structures. Furthermore, the JME group also presented higher clustering and lower modularity indices than controls, indicating weaker modules or communities. The local efficiency in JME was higher than controls across the majority of cortical nodes. Regarding network hubs, controls presented a higher number than youth with JME that were spread across the brain with ample representation from the different modules. In contrast, children with JME showed a lower number of hubs that were mainly from one module and comprised mostly subcortical structures.

SIGNIFICANCE

Youth with JME prospectively developed a network of highly correlated cortical regions dissociated from subcortical structures during the first 2 years after epilepsy onset. The cortical-subcortical network dissociation provides converging insights into the disparate literature of cortical and subcortical abnormalities found in previous studies.

Juvenile Myoclonic Epilepsy Shows Potential Structural White Matter Abnormalities: A TBSS Study

Background: Several studies on patients with juvenile myoclonic epilepsy (JME) showed widespread white matter (WM) abnormalities in the brain. The aim of this study was to investigate potential structural abnormalities in JME patients (1) compared to healthy controls, (2) among JME subgroups with or without photoparoxysmal responses (PPR), and (3) in correlation with clinical variables. Methods: A selection of 31 patients with JME (12 PPR positive) and 27 age and gender matched healthy controls (HC) were studied at a tertiary epilepsy center. Fractional anisotropy (FA) was calculated and intergroup differences analyzed using Tract Based Spatial Statistics (TBSS). Results: Compared to HC the JME group showed reduced FA widespread and bilateral in the longitudinal fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, anterior and posterior thalamic radiation, corona radiata, corpus callosum, cingulate gyrus and external capsule (p < 0.01). Subgroup analysis revealed no significant differences of WM alterations between PPR positive and negative patients and with clinical and epilepsy-related factors. Conclusions: Widespread microstructural abnormalities among patients with JME have been identified.Prior findings of frontal and thalamofrontal microstructural abnormalities have been confirmed. Additionally, microstructural abnormalities were found in widespread extra-frontal regions that may help to validate pathophysiological concepts of JME.

Changes in Dynamics Within and Between Resting-State Subnetworks in Juvenile Myoclonic Epilepsy Occur at Multiple Frequency Bands

Time-varying connectivity analyses have indicated idiopathic generalized epilepsy (IGE) could cause significant abnormalities in dynamic connective pattern within and between resting-state sub-networks (RSNs). However, previous studies mainly focused on the IGE-induced dynamic changes of functional connectivity (FC) in specific frequency band (0.01–0.08 Hz or 0.01–0.15 Hz), ignoring the changes across different frequency bands. Here, 24 patients with IGE characterized by juvenile myoclonic epilepsy (JME) and 24 matched healthy controls were studied using a data-driven frequency decomposition approach and a sliding window approach. The RSN dynamics, including intra-RSN dynamics and inter-RSN dynamics, was further calculated to investigate dynamic FC changes within and between RSNs in JME patients in each decomposed frequency band. Compared to healthy controls, JME patients not only showed frequency-dependent decrease in intra-RSN dynamics within multiple RSNs but also exhibited fluctuant alterations in inter-RSN dynamics among several RSNs over different frequency bands especially in the ventral/dorsal attention network and the subcortical network. Additionally, the disease severity had significantly negative correlations with both intra-RSN dynamics within the subcortical network and inter-RSN dynamics between the subcortical network and the default network at the lower frequency band (0.0095–0.0195 Hz). These results suggested that abnormal dynamic FC within and between RSNs in JME occurs at multiple frequency bands and the lower frequency band (0.0095–0.0195 Hz) was probably more sensitive to JME-caused dynamic FC abnormalities. The frequency subdivision and selection are potentially helpful for detecting particular changes of dynamic FC in JME.

Juvenile myoclonic epilepsy refractory to treatment in a tertiary referral center

INTRODUCTION

Juvenile myoclonic epilepsy (JME) is an epileptic syndrome often regarded as one in which seizures are relatively easy to control. Individuals with JME, however, often require lifelong therapy to remain seizure-free, and a few have refractory epilepsy. We ascertained a population with JME and characterized a subgroup with refractory epilepsy.

MATERIAL AND METHODS

We audited and reviewed clinical records of individuals diagnosed with JME identified via a sample of 6600 individuals in a clinical database from a specialized epilepsy clinic at a tertiary referral center.

RESULTS

We identified 240 people with a diagnosis of JME (146 females), with a mean age at seizure onset of 14.2years (SD: 4.5), and a mean age at diagnosis of 15.6years (SD: 4.9). Clinical phenotypes seen were classic JME phenotype (88%), childhood absence epilepsy evolving into JME (6%), JME with adolescent absences (4%), and JME with astatic seizures (2%). More than a quarter (28%) had a family history of epilepsy. The most commonly used antiepileptic drug (AED) was sodium valproate in 78% of individuals, followed by levetiracetam (64%) and lamotrigine (55%). In the previous year, 47.5% were seizure-free. Using the International League against Epilepsy (ILAE) definitions and considering National Institute for Health and Care Excellence (NICE)-recommended AEDs for this syndrome, 121 individuals (50.4%) were identified as having refractory epilepsy.

DISCUSSION

Juvenile myoclonic epilepsy is often regarded as a benign epileptic syndrome, but in this setting, half of the individuals with JME have refractory epilepsy with only about a quarter of those seizure-free in the previous year. Despite some advances in the understanding of this syndrome, there is still much to do before we can offer all the best outcomes.

Anatomy Based Networks and Topology Alteration in Seizure-Related Cognitive Outcomes

Epilepsy is a paroxysmal neurological disorder characterized by recurrent and unprovoked seizures affecting approximately 50 million people worldwide. Cognitive dysfunction induced by seizures is a severe comorbidity of epilepsy and epilepsy syndromes and reduces patients’ quality of life. Seizures, along with accompanying histopathological and pathophysiological changes, are associated with cognitive comorbidities. Advances in imaging technology and computing allow anatomical and topological changes in neural networks to be visualized. Anatomical components including the hippocampus, amygdala, cortex, corpus callosum (CC), cerebellum and white matter (WM) are the fundamental components of seizure- and cognition-related topological networks. Damage to these structures and their substructures results in worsening of epilepsy symptoms and cognitive dysfunction. In this review article, we survey structural, network changes and topological alteration in different regions of the brain and in different epilepsy and epileptic syndromes, and discuss what these changes may mean for cognitive outcomes related to these disease states.

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.

Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity

A common finding in human functional brain-imaging studies is that damage to neural systems paradoxically results in enhanced functional connectivity between network regions, a phenomenon commonly referred to as 'hyperconnectivity'. Here, we describe the various ways that hyperconnectivity operates to benefit a neural network following injury while simultaneously negotiating the trade-off between metabolic cost and communication efficiency. Hyperconnectivity may be optimally expressed by increasing connections through the most central and metabolically efficient regions (i.e., hubs). While adaptive in the short term, we propose that chronic hyperconnectivity may leave network hubs vulnerable to secondary pathological processes over the life span due to chronically elevated metabolic stress. We conclude by offering novel, testable hypotheses for advancing our understanding of the role of hyperconnectivity in systems-level brain plasticity in neurological disorders.

Thalamic hypoperfusion and disrupted cerebral blood flow networks in idiopathic generalized epilepsy: Arterial spin labeling and graph theoretical analysis

PURPOSE

The aim of this study was to investigate interictal cerebral blood flow (CBF) distributions and graph theoretical networks in idiopathic generalized epilepsy (IGE) using arterial spin labeling (ASL) imaging and anatomical covariance methods of graph theoretical analysis.

MATERIAL AND METHODS

We recruited 19 patients with IGE and 19 age-/gender-matched healthy controls. Their CBF images were obtained by pseudo-continuous ASL imaging and compared using statistical parametric mapping 8 software (SPM8) and Graph Analysis Toolbox (GAT).

RESULTS

The ASL imaging could detect interictal hypoperfusion in the thalamus, upper midbrain, and left cerebellum in IGE. Additionally, the graph theoretical analyses revealed characteristic findings of the CBF network of IGE, including significantly reduced resilience to attacks and changes of regional clustering especially in the bilateral temporo-occipital areas and lateral frontal lobes. There was no significance in the comparisons of network metrics.

CONCLUSION

These findings could contribute to a better understanding of the pathophysiology of IGE.

Praxis-induced seizures in a patient with juvenile myoclonic epilepsy: MEG-EEG coregistration study

Purpose

Juvenile myoclonic epilepsy (JME) is one of the most common generalized idiopathic epilepsies of childhood and adolescence. In some patients with JME, mathematical calculus and praxis may induce myoclonic seizures.

Methods

A reflex myoclonic seizure was recorded by simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) when a generalized spike–wave synchronous pattern at 3 Hz was observed.

Results

Source reconstruction localized the epileptogenic area to the right premotor frontal cortex.

Conclusions

The present study demonstrates that the origin of epileptiform activity in JME can be localized in brain areas associated with the premotor frontal cortex.

Altered Local Spontaneous Brain Activity in Juvenile Myoclonic Epilepsy: A Preliminary Resting-State fMRI Study

Purpose. The purpose of this study was to evaluate the regional synchronization of brain in patients with juvenile myoclonic epilepsy (JME). Methods. Resting-state fMRI data were acquired from twenty-one patients with JME and twenty-two healthy subjects. Regional homogeneity (ReHo) was used to analyze the spontaneous activity in whole brain. Two-sample t-test was performed to detect the ReHo difference between two groups. Correlations between the ReHo values and features of seizures were calculated further. Key Findings. Compared with healthy controls, patients showed significantly increased ReHo in bilateral thalami and motor-related cortex regions and a substantial reduction of ReHo in cerebellum and occipitoparietal lobe. In addition, greater ReHo value in the left paracentral lobule was linked to the older age of onset in patients. Significance. These findings implicated the abnormality of thalamomotor cortical network in JME which were associated with the genesis and propagation of epileptiform activity. Moreover, our study supported that the local brain spontaneous activity is a potential tool to investigate the epileptic activity and provided important insights into understanding the pathophysiological mechanisms of JME.

The Vulnerability to Suicidal Behavior is Associated with Reduced Connectivity Strength

Suicidal behavior constitutes a major public health problem. Based on the stress–diathesis model, biological correlates of a diathesis might help to predict risk after stressor-exposure. Structural changes in cortical and subcortical areas and their connections have increasingly been linked with the diathesis. The current study identified structural network changes associated with a diathesis using a whole-brain approach by examining the structural connectivity between regions in euthymic suicide attempters (SA). In addition, the association between connectivity measures, clinical and genetic characteristics was investigated. We hypothesized that SA showed lower connectivity strength, associated with an increased severity of general clinical characteristics and an elevated expression of short alleles in serotonin polymorphisms. Thirteen euthymic SA were compared with fifteen euthymic non-attempters and seventeen healthy controls (HC). Clinical characteristics and three serotonin-related genetic polymorphisms were assessed. Diffusion MRI together with anatomical scans were administered. Preprocessing was performed using Explore DTI. Whole brain tractography of the diffusion-weighted images was followed by a number of streamlines-weighted network analysis using NBS. The network analysis revealed decreased connectivity strength in SA in the connections between the left olfactory cortex and left anterior cingulate gyrus. Furthermore, SA had increased suicidal ideation, hopelessness and self-reported depression, but did not show any differences for the genetic polymorphisms. Finally, lower connectivity strength between the right calcarine fissure and the left middle occipital gyrus was associated with increased trait anxiety severity (r_s = −0.78, p < 0.01) and hopelessness (r_s = −0.76, p < 0.01). SA showed differences in white matter network connectivity strength associated with clinical characteristics. Together, these variables could play an important role in predicting suicidal behavior.