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Both natural and engineered networks are often modular. Whether a network node interacts with only nodes from its own module or nodes from multiple modules provides insight into its functional role. The participation coefficient ( PC) is typically used to measure this attribute, although its value also depends on the size and connectedness of the module it belongs to and may lead to nonintuitive identification of highly connected nodes. Here, we develop a normalized PC that reduces the influence of intramodular connectivity compared with the conventional PC. Using brain, C. elegans, airport, and simulated networks, we show that our measure of participation is not influenced by the size or connectedness of modules, while preserving conceptual and mathematical properties, of the classic formulation of PC. Unlike the conventional PC, we identify London and New York as high participators in the air traffic network and demonstrate stronger associations with working memory in human brain networks, yielding new insights into nodal participation across network modules.

ObjectiveRecent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.MethodsWe extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.ResultsIn MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.SignificanceFrom cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.

Objective: Epilepsy is a common and serious neurological disorder. This cross‐sectional analysis addresses the burden of epilepsy at different stages of the disease. Methods: This pilot study is embedded within the Australian Epilepsy Project (AEP), aiming to provide epilepsy support through a national network of dedicated sites. For this analysis, adults aged 18–65 years with first unprovoked seizure (FUS), newly diagnosed epilepsy (NDE), or drug‐resistant epilepsy (DRE) were recruited between February–August 2022. Baseline clinicodemographic data were collected from the participants who completed questionnaires to assess their quality of life (QOLIE‐31, EQ‐5D‐5L), work productivity (Work Productivity and Activity Impairment [WPAI]), and care needs. Univariate analysis and multivariate regression was performed. Results: 172 participants formed the study cohort (median age 34, interquartile range [IQR]: 26–45), comprising FUS (n = 44), NDE (n = 53), and DRE (n = 75). Mean QOLIE‐31 score was 56 (standard deviation [SD] ± 18) and median EQ‐5D‐5L score was 0.77 (IQR: 0.56–0.92). QOLIE‐31 but not EQ‐5D‐5L scores were significantly lower in the DRE group compared to FUS and NDE groups (p < 0.001). Overall, 64.5% of participants participated in paid work, with fewer DRE (52.0%) compared with FUS (76.7%) and NDE (72.5%) (p < 0.001). Compared to those not in paid employment, those in paid employment had significantly higher quality of life scores (p < 0.001). Almost 5.8% of participants required formal care (median 20 h/week, IQR: 12–55) and 17.7% required informal care (median 16 h/week, IQR: 7–101). Significance: Epilepsy is associated with a large burden in terms of quality of life, productivity and care needs. Plain Language Summary: This is a pilot study from the Australian Epilepsy Project (AEP). It reports health economic data for adults of working age who live with epilepsy. It found that people with focal drug‐resistant epilepsy had lower quality of life scores and were less likely to participate in paid employment compared to people with new diagnosis epilepsy. This study provides important local data regarding the burden of epilepsy and will help researchers in the future to measure the impact of the AEP on important personal and societal health economic outcomes. [ABSTRACT FROM AUTHOR]

Malformations of cerebral cortical development include a wide range of developmental disorders that are common causes of neurodevelopmental delay and epilepsy. In addition, study of these disorders contributes greatly to the understanding of normal brain development and its perturbations. The rapid recent evolution of molecular biology, genetics and imaging has resulted in an explosive increase in our knowledge of cerebral cortex development and in the number and types of malformations of cortical development that have been reported. These advances continue to modify our perception of these malformations. This review addresses recent changes in our perception of these disorders and proposes a modified classification based upon updates in our knowledge of cerebral cortical development.

Improved quality of life (QoL) is an important outcome goal following epilepsy surgery. This study aims to quantify change in QoL for adults with drug‐resistant epilepsy (DRE) who undergo epilepsy surgery, and to explore clinicodemographic factors associated with these changes. We conducted a systematic review and meta‐analysis using Medline, Embase, and Cochrane Central Register of Controlled Trials. All studies reporting pre‐ and post‐epilepsy surgery QoL scores in adults with DRE via validated instruments were included. Meta‐analysis assessed the postsurgery change in QoL. Meta‐regression assessed the effect of postoperative seizure outcomes on postoperative QoL as well as change in pre‐ and postoperative QoL scores. A total of 3774 titles and abstracts were reviewed, and ultimately 16 studies, comprising 1182 unique patients, were included. Quality of Life in Epilepsy Inventory–31 item (QOLIE‐31) meta‐analysis included six studies, and QOLIE‐89 meta‐analysis included four studies. Postoperative change in raw score was 20.5 for QOLIE‐31 (95% confidence interval [CI] = 10.9–30.1, I2 = 95.5) and 12.1 for QOLIE‐89 (95% CI = 8.0–16.1, I2 = 55.0%). This corresponds to clinically meaningful QOL improvements. Meta‐regression demonstrated a higher postoperative QOLIE‐31 score as well as change in pre‐ and postoperative QOLIE‐31 score among studies of cohorts with higher proportions of patients with favorable seizure outcomes. At an individual study level, preoperative absence of mood disorders, better preoperative cognition, fewer trials of antiseizure medications before surgery, high levels of conscientiousness and openness to experience at the baseline, engagement in paid employment before and after surgery, and not being on antidepressants following surgery were associated with improved postoperative QoL. This study demonstrates the potential for epilepsy surgery to provide clinically meaningful improvements in QoL, as well as identifies clinicodemographic factors associated with this outcome. Limitations include substantial heterogeneity between individual studies and high risk of bias. [ABSTRACT FROM AUTHOR]