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Previous studies have documented that children with newly diagnosed epilepsy often exhibit various behavioral comorbidities such as anxiety, depression, aggressive behavior, and attention that affect many aspects of their life including academic performance. Furthermore, these studies have identified distinct behavioral phenotype groups but have not investigated the trajectory of each of these groups over time. In this study we explore the presence and trajectory of behavior and academic performance in children with newly diagnosed epilepsy and their siblings over a 36-month period.

BackgroundAccumulating evidence indicates that children with newly diagnosed epilepsy have comorbidities including cognitive challenges. Research investigating comorbidities has focused on clinical epilepsy characteristics and neurobiological/genetic correlates. The role that sociodemographic disadvantage (SD) may play has received less attention. We investigated the role of SD in cognitive status in youth with newly diagnosed epilepsy over a follow-up of 36 months to determine the degree, extent, and duration of the role of disadvantage.MethodsA total of 289 children (six to 16 years) within six weeks of their first seizure along with 167 siblings underwent comprehensive neuropsychological assessments (intelligence, language, memory, executive function, processing speed, and academic achievement) at baseline, 18 months later, and at 36 months from baseline. Baseline demographic information (race, caregivers education, household income, and parental marital status), clinical epilepsy characteristics (e.g., age of onset), and magnetic resonance imaging (MRI) and electroencephalographic (EEG) information was collected.ResultsAn SD index was computed for each family and categorized into four groups by level of disadvantage. In children and siblings, the least disadvantaged group exhibited the highest Full-Scale IQ, neuropsychological factor scores, and academic performances, whereas the most disadvantaged showed the polar opposite with the worst performances across all tests. Findings remained stable and significant over 36 months. Linear regression analyses indicated that disadvantage was a more constant and stable predictor of cognitive and academic performance over time compared with clinical epilepsy characteristics and MRI/EEG abnormalities.ConclusionsThis study indicates the strong association between SD and cognitive/academic performance in children with newly diagnosed epilepsy and their siblings is significant and predictive of three-year cognitive outcomes.

ObjectiveThis study was undertaken to determine the short-term and longer term impact of sociodemographic disadvantage on the emotional-behavioral status of youths with new onset epilepsy and their unaffected siblings at the time of diagnosis and the subsequent 3 years.MethodsThree hundred twelve youths with newly diagnosed epilepsies and 223 unaffected siblings, aged 6-16 years, were independently assessed regarding their emotional and behavioral status by their parents and teachers at baseline, and at 18 at 36 months later; youths with seizures also completed self-report measures of depression, anxiety, and hostility at those three time points. A sociodemographic disadvantage score was computed for each family (children with newly diagnosed seizures and their siblings), and families were separated into four categories from most disadvantaged to least disadvantaged.ResultsIn both children and siblings, the least disadvantaged group exhibited the lowest level of neurobehavioral problems, whereas the most disadvantaged group showed a higher level of neurobehavioral problems across all the same behavior metrics. Findings remained stable and significant across all informants (parent, teacher, child) and across all time periods (throughout the 3-year period). Furthermore, both corrected and uncorrected linear regression analyses indicated that disadvantage was a more constant and stable predictor of behavioral and emotional problems over time compared to clinical seizure characteristics and abnormalities in magnetic resonance imaging and electroencephalographic testing.SignificanceSociodemographic disadvantage bears a strong relationship to youths with emotional and behavioral problems both at the time of diagnosis as well as prospectively. The relationship is robust and reflected in reports from multiple informants (parent, teacher, child self-report), evident in siblings as well, and possibly more explanatory than traditional clinical seizure variables. Future studies will be needed to determine whether this disadvantage factor is modifiable with early intervention.

OBJECTIVE: This study was undertaken to evaluate the cross-cultural application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) to a cohort of Spanish-speaking patients with temporal lobe epilepsy (TLE) living in the United States. METHODS: Eighty-four Spanish-speaking patients with TLE completed neuropsychological measures of memory, language, executive function, visuospatial functioning, and attention/processing speed as part of the Neuropsychological Screening Battery for Hispanics. The contribution of demographic and clinical variables to cognitive performance was evaluated. A sensitivity analysis was conducted by examining the base rates of impairment across several impairment thresholds. The IC-CoDE taxonomy was then applied, and the base rate of cognitive phenotypes for each cutoff was calculated. The distribution of phenotypes was compared to the published IC-CoDE taxonomy data, which utilized a large, multicenter cohort of English-speaking patients with TLE. RESULTS: Across the different impairment cutoffs, memory was the most impaired cognitive domain, with impairments in list learning ranging from 50% to 78%. Application of the IC-CoDE taxonomy utilizing a -1.5-SD cutoff revealed an intact cognitive profile in 47.6% of patients, single-domain impairment in 23.8% of patients, bidomain impairment in 14.3% of patients, and generalized impairment in 14.3% of the sample. This distribution was comparable to the phenotype distribution observed in the IC-CoDE validation sample. SIGNIFICANCE: We demonstrate a similar pattern and distribution of cognitive phenotypes in a Spanish-speaking epilepsy cohort compared to an English-speaking sample. This suggests stability in the underlying phenotypes associated with TLE and applicability of the IC-CoDE for guiding cognitive diagnostics in epilepsy research that can be applied to culturally and linguistically diverse samples.

BackgroundChildren with epilepsy frequently have sleep, behavior, and cognitive problems at the time of or before the epilepsy diagnosis. The primary goal of this study was to determine if specific sleep disturbance phenotypes exist in a large cohort of children with new-onset epilepsy and if these phenotypes are associated with specific cognitive and behavioral signatures.MethodsA total of354 children with new-onset epilepsy, aged six to 16 years, were recruited within six weeks of initial seizure onset. Each child underwent evaluation of their sleep along with self, parent, and teacher ratings of emotional-behavioral status. Two-step clustering using sleep disturbance (Sleep Behavior Questionnaire), naps, and sleep latency was employed to determine phenotype clusters.ResultsAnalysis showed three distinct sleep disturbance phenotypes-minimal sleep disturbance, moderate sleep disturbance, and severe sleep disturbance phenotypes. Children who fell into the minimal sleep disturbance phenotype had an older age of onset with the best cognitive performance compared with the other phenotypes and the lowest levels of emotional-behavioral problems. In contrast, children who fell into the severe sleep disturbance phenotype had the youngest age of onset of epilepsy with poor cognitive performance and highest levels of emotional-behavioral problems.ConclusionsThis study indicates that there are indeed specific sleep disturbance phenotypes that are apparent in children with newly diagnosed epilepsy and are associated with specific comorbidities. Future research should determine if these phenotypic groups persist over time and are predictive of long-term difficulties, as these subgroups may benefit from targeted therapy and intervention.

IntroductionDementia as an inevitable aging consequence has been challenged and underscores the need for investigations of the factors that confer resilience. We examine whether the functionally advantageous KL-VS variant of the putative aging suppressor KLOTHO gene attenuates age-related cognitive decline and deleterious biomolecular changes.MethodsTrajectories of change in memory and executive function (N = 360; 2-12 visits) and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers-amyloid beta (Aβ)42, total tau (t-tau), phosphorylated tau (p-tau) (N = 112; 2-4 samplings)-were compared between KL-VS non-carriers and heterozygotes in middle-aged and older adults from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center studies.ResultsMemory and executive function declined (p's ≤ 0.001) and CSF t-tau, p-tau, t-tau/Aβ42, and p-tau/Aβ42 levels increased (all p's ≤ 0.004) with age. The rate of p-tau accumulation was attenuated for KL-VS heterozygotes (p = 0.03).DiscussionKL-VS heterozygosity may confer resilience to AD-associated biomolecular changes.

IntroductionThere is substantial evidence that children with epilepsy experience more sleep, behavior and cognitive challenges than children without epilepsy. However, the literature is limited in describing the relationship between sleep, epilepsy, cognition and behavioral challenges and the interactions amongst these factors over time. This study aims to understand the nature and strength of the relationship between sleep, cognition, mood and behavior in children with new-onset epilepsy as assessed by multiple informants at multiple time periods using multiple different dependent measures.Methods332 participants (6-16years) were recruited within 6 weeks of their first recognized seizure. The comparison group was comprised of 266 healthy siblings. Participants underwent sleep evaluation by a parent using the Sleep Behavioral Questionnaire (SBQ), cognitive evaluation using a comprehensive neuropsychological test battery, a behavioral evaluation using the Child Behavior Checklist (CBCL from parents and TRF from teachers) and the Children's Depression Inventory (CDI). These evaluations were completed at baseline (B), at 18 months, and at 36 months.ResultsCompared to siblings, children with new-onset epilepsy had more sleep disturbance (SBQ), higher rates of behavioral problems (CBCL and TRF), lower cognitive testing scores, and higher rates of depression; which persisted over the 36-month study. Sleep significantly correlated with behavioral problems, cognitive scores and depression. When divided into categories based of sleep disturbance scores, 39.7% of children with epilepsy experienced "Persistently Abnormal Sleep", while 14.8% experienced "Persistently Normal Sleep". Children with persistently abnormal sleep experienced the highest rates of behavioral problems, depression and cognitive impairment compared to those with persistently normal sleep, regardless of epilepsy syndrome. Younger age of seizure onset, younger age at testing, and lower grade level at baseline were associated with persistently abnormal sleep.ConclusionsTo our knowledge, this is the first demonstration of the nature, strength, reliability, stability and persistence of the relationship between sleep, cognition, and behavioral problems over time in a large cohort of children with newly diagnosed epilepsy, as assessed by multiple informants at different timepoints. The results of this study indicate that children with epilepsy are at a high risk of significant persisting neurobehavioral multimorbidity. Therefore, early screening for these challenges may be essential for optimizing quality of life long-term.

ObjectiveBenign epilepsy with centrotemporal spikes (BECTS) is the most common childhood idiopathic localization-related epilepsy syndrome. BECTS presents normal routine magnetic resonance imaging (MRI); however, quantitative analytic techniques have captured subtle cortical and subcortical magnetic resonance anomalies. Network science, including graph theory (GT) analyses, facilitates understanding of brain covariance patterns, potentially informing in important ways how this common self-limiting epilepsy syndrome may impact normal patterns of brain and cognitive development.MethodsGT analyses examined the developmental covariance among cortical and subcortical regions in children with new/recent onset BECTS (n = 19) and typically developing healthy controls (n = 22) who underwent high-resolution MRI and cognitive assessment at baseline and 2 years later. Global (transitivity, global efficiency, and modularity index [Q]) and regional measures (local efficiency and hubs) were investigated to characterize network development in each group. Associations between baseline-based GT measures and cognition at both time points addressed the implications of GT analyses for cognition and prospective cognitive development. Furthermore, an individual contribution measure was investigated, reflecting how important for cognition it is for BECTS to resemble the correlation matrices of controls.ResultsGroups exhibited similar Q and overall network configuration, with BECTS presenting significantly higher transitivity and both global and local efficiency. Furthermore, both groups presented a similar number of hubs, with BECTS showing a higher number in temporal lobe regions compared to controls. The investigated measures were negatively associated with 2-year cognitive outcomes in BECTS.SignificanceChildren with BECTS present a higher-than-normal global developmental configuration compared to controls, along with divergence from normality in terms of regional configuration. Baseline GT measures demonstrate potential as a cognitive biomarker to predict cognitive outcome in BECTS 2 years after diagnosis. Similarities and differences in developmental network configurations and their implications for cognition and behavior across common epilepsy syndromes are of theoretical interest and clinical relevance.

OBJECTIVE:To identify distinct cognitive phenotypes in temporal lobe epilepsy (TLE) and evaluate patterns of white matter (WM) network alterations associated with each phenotype. METHODS:Seventy patients with TLE were characterized into 4 distinct cognitive phenotypes based on patterns of impairment in language and verbal memory measures (language and memory impaired, memory impaired only, language impaired only, no impairment). Diffusion tensor imaging was obtained in all patients and in 46 healthy controls (HC). Fractional anisotropy (FA) and mean diffusivity (MD) of the WM directly beneath neocortex (i.e., superficial WM [SWM]) and of deep WM tracts associated with memory and language were calculated for each phenotype. Regional and network-based SWM analyses were performed across phenotypes. RESULTS:The language and memory impaired group and the memory impaired group showed distinct patterns of microstructural abnormalities in SWM relative to HC. In addition, the language and memory impaired group showed widespread alterations in WM tracts and altered global SWM network topology. Patients with isolated language impairment exhibited poor network structure within perisylvian cortex, despite relatively intact global SWM network structure, whereas patients with no impairment appeared similar to HC across all measures. CONCLUSIONS:These findings demonstrate a differential pattern of WM microstructural abnormalities across distinct cognitive phenotypes in TLE that can be appreciated at both the regional and network levels. These findings not only help to unravel the underlying neurobiology associated with cognitive impairment in TLE, but they could also aid in establishing cognitive taxonomies or in the prediction of cognitive course in TLE.

ObjectiveStructural 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.MethodsWe 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.ResultsOver 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.SignificanceYouth 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.

INTRODUCTION: We examined whether the aging suppressor KLOTHO gene's functionally advantageous KL‐VS variant (KL‐VS heterozygosity [KL‐VSHET]) confers resilience against deleterious effects of aging indexed by cerebrospinal fluid (CSF) biomarkers of neuroinflammation (interleukin‐6 [IL‐6], S100 calcium‐binding protein B [S100B], triggering receptor expressed on myeloid cells [sTREM2], chitinase‐3‐like protein 1 [YKL‐40], glial fibrillary acidic protein [GFAP]), neurodegeneration (total α‐synuclein [α‐Syn], neurofilament light chain protein), and synaptic dysfunction (neurogranin [Ng]). METHODS: This Alzheimer disease risk‐enriched cohort consisted of 454 cognitively unimpaired adults (Mage = 61.5 ± 7.75). Covariate‐adjusted multivariate regression examined relationships between age (mean‐split[age ≥ 62]) and CSF biomarkers (Roche/NeuroToolKit), and whether they differed between KL‐VSHET (N = 122) and non‐carriers (KL‐VSNC; N = 332). RESULTS: Older age was associated with a poorer biomarker profile across all analytes (Ps ≤ 0.03). In age‐stratified analyses, KL‐VSNC exhibited this same pattern (Ps ≤ 0.05) which was not significant for IL‐6, S100B, Ng, and α‐Syn (Ps ≥ 0.13) in KL‐VSHET. Although age‐related differences in GFAP, sTREM2, and YKL‐40 were evident for both groups (Ps ≤ 0.01), the effect magnitude was markedly stronger for KL‐VSNC. DISCUSSION: Higher levels of neuroinflammation, neurodegeneration, and synaptic dysfunction in older adults were attenuated in KL‐VSHET. Highlights: Older age was associated with poorer profiles across all cerebrospinal fluid biomarkers of neuroinflammation, neurodegeneration, and synaptic dysfunction.KLOTHO KL‐VS non‐carriers exhibit this same pattern, which is does not significantly differ between younger and older KL‐VS heterozygotes for interleukin‐6, S100 calcium‐binding protein B, neurogranin, and total α‐synuclein.Although age‐related differences in glial fibrillary acidic protein, triggering receptor expressed on myeloid cells, and chitinase‐3‐like protein 1 are evident for both KL‐VS groups, the magnitude of the effect is markedly stronger for KL‐VS non‐carriers.Higher levels of neuroinflammation, neurodegeneration, and synaptic dysfunction in older adults are attenuated in KL‐VS heterozygotes. [ABSTRACT FROM AUTHOR]

Objective: Efforts to understand the global variability in cognitive profiles in patients with epilepsy have been stymied by the lack of a standardized diagnostic system. This study examined the cross‐cultural applicability of the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE) in a cohort of patients with temporal lobe epilepsy (TLE) in India that was diverse in language, education, and cultural background. Methods: A cohort of 548 adults with TLE from Mumbai completed a presurgical comprehensive neuropsychological evaluation. The IC‐CoDE taxonomy was applied to derive cognitive phenotypes in the sample. Analyses of variance were conducted to examine differences in demographic and clinical characteristics across the phenotypes, and chi‐squared tests were used to determine whether the phenotype distribution differed between the Mumbai sample and published data from a multicenter US sample. Results: Using the IC‐CoDE criteria, 47% of our cohort showed an intact cognitive profile, 31% a single‐domain impairment, 16% a bidomain impairment, and 6% a generalized impairment profile. The distribution of cognitive phenotypes was similar between the Indian and US cohorts for the intact and bidomain phenotypes, but differed for the single and generalized domains. There was a larger proportion of patients with single‐domain impairment in the Indian cohort and a larger proportion with generalized impairment in the US cohort. Among patients with single‐domain impairment, a greater proportion exhibited memory impairment in the Indian cohort, whereas a greater proportion showed language impairment in the US sample, likely reflecting differences in language administration procedures and sample characteristics including a higher rate of mesial temporal sclerosis in the Indian sample. Significance: Our results demonstrate the applicability of IC‐CoDE in a group of culturally and linguistically diverse patients from India. This approach enhances our understanding of cognitive variability across cultures and enables harmonized and inclusive research into the neuropsychological aspects of epilepsy. [ABSTRACT FROM AUTHOR]

Objective: This study evaluated the diagnostic performance of a widely available cognitive screener, the Montreal cognitive assessment (MoCA), to detect cognitive impairment in older patients (age ≥ 55) with epilepsy residing in the US, using the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE) as the gold standard. Methods: Fifty older adults with focal epilepsy completed the MoCA and neuropsychological measures of memory, language, executive function, and processing speed/attention. The IC‐CoDE taxonomy divided participants into IC‐CoDE Impaired and Intact groups. Sensitivity and specificity across several MoCA cutoffs were examined. Spearman correlations examined relationships between the MoCA total score and clinical and demographic variables and MoCA domain scores and individual neuropsychological tests. Results: IC‐CoDE impaired patients demonstrated significantly lower scores on the MoCA total, visuospatial/executive, naming, language, delayed recall, and orientation domain scores (Cohen's d range: 0.336–2.77). The recommended MoCA cutoff score < 26 had an overall accuracy of 72%, 88.2% sensitivity, and 63.6% specificity. A MoCA cutoff score < 24 yielded optimal sensitivity (70.6%) and specificity (78.8%), with overall accuracy of 76%. Higher MoCA total scores were associated with greater years of education (p = 0.016) and fewer antiseizure medications (p = 0.049). The MoCA memory domain was associated with several standardized measures of memory, MoCA language domain with category fluency, and MoCA abstraction domain with letter fluency. Significance: This study provides initial validation of the MoCA as a useful screening tool for older adults with epilepsy that can be used to identify patients who may benefit from comprehensive neuropsychological testing. Further, we demonstrate that a lower cutoff (i.e., <24) better captures cognitive impairment in older adults with epilepsy than the generally recommended cutoff and provides evidence for construct overlap between MoCA domains and standard neuropsychological tests. Critically, similar efforts in other regions of the world are needed. Plain Language Summary: The Montreal cognitive assessment (MoCA) can be a helpful tool to screen for cognitive impairment in older adults with epilepsy. We recommend that adults 55 or older with epilepsy who score less than 24 on the MoCA are referred to a neuropsychologist for a comprehensive evaluation to assess any changes in cognitive abilities and mood. [ABSTRACT FROM AUTHOR]

The recent revision of the classification of the epilepsies released by the ILAE Commission on Classification and Terminology (2005-2009) has been a major development in the field. Papers in this section of the special issue explore the relevance of other techniques to examine, categorize, and classify cognitive and behavioral comorbidities in epilepsy. In this review, we investigate the applicability of graph theory to understand the impact of epilepsy on cognition compared with controls and, then, the patterns of cognitive development in normally developing children which would set the stage for prospective comparisons of children with epilepsy and controls. The overall goal is to examine the potential utility of this analytic tool and approach to conceptualize the cognitive comorbidities in epilepsy. Given that the major cognitive domains representing cognitive function are interdependent, the associations between neuropsychological abilities underlying these domains can be referred to as a cognitive network. Therefore, the architecture of this cognitive network can be quantified and assessed using graph theory methods, rendering a novel approach to the characterization of cognitive status. We first provide fundamental information about graph theory procedures, followed by application of these techniques to cross-sectional analysis of neuropsychological data in children with epilepsy compared with that of controls, concluding with prospective analysis of neuropsychological development in younger and older healthy controls. This article is part of a Special Issue entitled "The new approach to classification: Rethinking cognition and behavior in epilepsy".

ObjectiveThis study identified items on the Child Behavior Checklist (CBCL) that predict those children and adolescents with epilepsy at highest risk for multiple psychiatric diagnoses.MethodsThree hundred twenty-eight children, ages 5-18 years, and their parents participated in separate structured psychiatric interviews about the children, which yielded Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision (DSM-IV-TR) diagnoses. Parents completed the CBCL. The sample was divided into a younger (≤12 years, n = 214) group and an older (>12-18 years, n = 114) group. This study identified a reduced set of parent-reported CBCL items associated with Multiple Diagnoses versus Single Diagnosis versus No Diagnosis using chi-square tests and stepwise logistic regression. We then performed a generalized logistic regression with Multiple Diagnoses versus Single Diagnosis versus No Diagnosis as the dependent variable and the reduced CBCL set of items as predictors. We calculated the area under the ROC (receiver operating characteristic) curve (AUC) as a measure of diagnostic accuracy for pairwise comparisons.ResultsFor the younger group, seven items (clingy, cruelty/bullying, perfectionist, nervous, poor school work, inattentive, and sulks) had high diagnostic accuracy (AUC = 0.88), and for the older group, three items (disobedient at school, loner, and lies/cheats) had high accuracy (AUC = 0.91) when comparing children with multiple psychiatric diagnoses to children with no diagnosis. For both age groups, there was less diagnostic accuracy in identifying children with a single versus no diagnosis (AUC = 0.75 [young]; 0.70 [older]).SignificanceThese findings suggest that responses to these two subsets of parent-reported CBCL items should alert clinicians to children and adolescents with epilepsy at risk for multiple psychiatric diagnoses and in need of a psychiatric referral.

ObjectiveNormal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC.MethodsNeuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed.ResultsThe community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE.SignificanceAdults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments.

Anxiety disorders represent a prevalent psychiatric comorbidity in both adults and children with epilepsy for which the etiology remains controversial. Neurobiological contributions have been suggested, but only limited evidence suggests abnormal brain volumes particularly in children with epilepsy and anxiety. Since the brain develops in an organized fashion, covariance analyses between different brain regions can be investigated as a network and analyzed using graph theory methods. We examined 46 healthy children (HC) and youth with recent onset idiopathic epilepsies with (n = 24) and without (n = 62) anxiety disorders. Graph theory (GT) analyses based on the covariance between the volumes of 85 cortical/subcortical regions were investigated. Both groups with epilepsy demonstrated less inter-modular relationships in the synchronization of cortical/subcortical volumes compared to controls, with the epilepsy and anxiety group presenting the strongest modular organization. Frontal and occipital regions in non-anxious epilepsy, and areas throughout the brain in children with epilepsy and anxiety, showed the highest centrality compared to controls. Furthermore, most of the nodes correlating to amygdala volumes were subcortical structures, with the exception of the left insula and the right frontal pole, which presented high betweenness centrality (BC); therefore, their influence in the network is not necessarily local but potentially influencing other more distant regions. In conclusion, children with recent onset epilepsy and anxiety demonstrate large scale disruptions in cortical and subcortical brain regions. Network science may not only provide insight into the possible neurobiological correlates of important comorbidities of epilepsy, but also the ways that cortical and subcortical disruption occurs.