Association of white matter diffusion characteristics and cognitive deficits in temporal lobe epilepsy

Temporal Lobe Epilepsy Perturbs the Brain-Wide Excitation-Inhibition Balance: Associations with Microcircuit Organization, Clinical Parameters, and Cognitive Dysfunction

Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models. A broad decrease in the Hurst exponent is observed in pharmaco-resistant temporal lobe epilepsy (TLE), suggesting more excitable network dynamics. Connectome decoders point to temporolimbic and frontocentral cortices as plausible network epicenters of E/I imbalance. Furthermore, computational simulations reveal that enhancing cortical excitability in TLE reflects atypical increases in recurrent connection strength of local neuronal ensembles. Mixed cross-sectional and longitudinal analyses show stronger E/I ratio elevation in patients with longer disease duration, more frequent electroclinical seizures as well as interictal epileptic spikes, and worse cognitive functioning. Hurst exponent-informed classifiers discriminate patients from healthy controls with high accuracy (72.4% [57.5%-82.5%]). Replicated in an independent dataset, this work provides in vivo evidence of a macroscale shift in E/I balance in TLE patients and points to progressive functional imbalances that relate to cognitive decline.

Mechanistic insight of curcumin: a potential pharmacological candidate for epilepsy

Recurrent spontaneous seizures with an extended epileptic discharge are the hallmarks of epilepsy. At present, there are several available anti-epileptic drugs (AEDs) in the market. Still no adequate treatment for epilepsy treatment is available. The main disadvantages of AEDs are their associated adverse effects. It is a challenge to develop new therapies that can reduce seizures by modulating the underlying mechanisms with no adverse effects. In the last decade, the neuromodulatory potential of phytoconstituents has sparked their usage in the treatment of central nervous system disorders. Curcumin is an active polyphenolic component that interacts at cellular and molecular levels. Curcumin's neuroprotective properties have been discovered in recent preclinical and clinical studies due to its immunomodulatory effects. Curcumin has the propensity to modulate signaling pathways involved in cell survival and manage oxidative stress, apoptosis, and inflammatory mechanisms. Further, curcumin can persuade epigenetic alterations, including histone modifications (acetylation/deacetylation), which are the changes responsible for the altered expression of genes facilitating the process of epileptogenesis. The bioavailability of curcumin in the brain is a concern that needs to be tackled. Therefore, nanonization has emerged as a novel drug delivery system to enhance the pharmacokinetics of curcumin. In the present review, we reviewed curcumin's modulatory effects on potential biomarkers involved in epileptogenesis including dendritic cells, T cell subsets, cytokines, chemokines, apoptosis mediators, antioxidant mechanisms, and cognition impairment. Also, we have discussed the nanocarrier systems for encapsulating curcumin, offering a promising approach to enhance bioavailability of curcumin.

Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations

OBJECTIVE

Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.

METHODS

A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.

RESULTS

Factor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group.

SIGNIFICANCE

Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.

Reorganization of pragmatic language networks in patients with temporal lobe epilepsy

OBJECTIVE

To investigate the neural networks involved in idiomatic expressions (IE) comprehension in healthy controls and patients with drug-resistant temporal lobe epilepsy (TLE), with a functional magnetic resonance imaging (fMRI) task.

METHODS

Thirty-two patients with TLE (left or right) and seventeen healthy controls were evaluated. Activated nodes in the fMRI task were defined as Regions of Interest (ROIs) for a posterior functional connectivity analysis.

RESULTS

All participants completed the task successfully. We found a bilateral fronto-temporal network, lateralized to the right, during IE processing in the overall sample. Compared to controls, patients additionally activated frontal, temporal, and insular areas in both hemispheres. Controls exhibited fewer connections but greater inhibitory connectivity, while the opposite (more connections and increased excitatory connectivity) occurred in patients. Compared to controls, TLE patients recruited additional brain areas on top of the expected bilateral frontotemporal network. The connectivity analysis revealed that controls exhibited more effective inhibitory connectivity, with more modular ROIs. In contrast, patients demonstrated greater excitatory connectivity.

CONCLUSION

The results suggest compensatory neural recruitment in additional areas in TLE during IE comprehension.

SIGNIFICANCE

Exacerbated connections in TLE may reflect the need to recruit alternative regions, resulting in higher costs and lower efficiency of the neural network.

Cross-cultural application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE): Cognitive phenotypes in people with temporal lobe epilepsy in India

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.

Cognitive phenotypes in patients with drug-resistant temporal lobe epilepsy: Relationships with cortisol and affectivity

OBJECTIVE

Drug-resistant temporal lobe epilepsy (TLE) is a neurological disorder characterized by cognitive deficits. This study examined whether patients with TLE and different cognitive phenotypes differ in cortisol levels and affectivity while controlling for demographic and clinical variables. Methods: In this cross-sectional study, 79 adults with TLE underwent neuropsychological evaluation in which memory, language, attention/processing speed, executive function, and affectivity were assessed. Six saliva samples were collected in the afternoon to examine the ability of the hypothalamic-pituitary-adrenal (HPA) axis to descend according to the circadian rhythm (C1 to C6). The cortisol area under the curve concerning ground (AUCg) was computed to examine global cortisol secretion.

RESULTS

Three cognitive phenotypes were identified: memory impairment, generalized impairment, and no impairment. The memory-impairment phenotype showed higher cortisol levels at C4, C5, and C6 than the other groups (p = 0.03, η2 = 0.06), higher cortisol AUCg than the generalized-impairment phenotype (p = 0.004, η2 = 0.14), and a significant reduction in positive affectivity after the evaluation (p = 0.026, η2 = 0.11). Higher cortisol AUCg and reductions in positive affectivity were significant predictors of the memory-impairment phenotype (p < 0.001; Cox and Snell R2 = 0.47).

CONCLUSIONS

Patients with memory impairment had a slower decline in cortisol levels in the afternoon, which could be interpreted as an inability of the HPA axis to inhibit itself. Thus, chronic stress may influence hippocampus-dependent cognitive function more than other cognitive functions in patients with TLE.

Neuroprotective effects of naltrexone in a mouse model of post-traumatic seizures

Traumatic Brain Injury (TBI) induces neuroinflammatory response that can initiate epileptogenesis, which develops into epilepsy. Recently, we identified anti-convulsive effects of naltrexone, a mu-opioid receptor (MOR) antagonist, used to treat drug addiction. While blocking opioid receptors can reduce inflammation, it is unclear if post-TBI seizures can be prevented by blocking MORs. Here, we tested if naltrexone prevents neuroinflammation and/or seizures post-TBI. TBI was induced by a modified Marmarou Weight-Drop (WD) method on 4-week-old C57BL/6J male mice. Mice were placed in two groups: non-telemetry assessing the acute effects or in telemetry monitoring for interictal events and spontaneous seizures both following TBI and naltrexone. Molecular, histological and neuroimaging techniques were used to evaluate neuroinflammation, neurodegeneration and fiber track integrity at 8 days and 3 months post-TBI. Peripheral immune responses were assessed through serum chemokine/cytokine measurements. Our results show an increase in MOR expression, nitro-oxidative stress, mRNA expression of inflammatory cytokines, microgliosis, neurodegeneration, and white matter damage in the neocortex of TBI mice. Video-EEG revealed increased interictal events in TBI mice, with 71% mice developing post-traumatic seizures (PTS). Naltrexone treatment ameliorated neuroinflammation, neurodegeneration, reduced interictal events and prevented seizures in all TBI mice, which makes naltrexone a promising candidate against PTS, TBI-associated neuroinflammation and epileptogenesis in a WD model of TBI.

Differential relational memory impairment in temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) is typically associated with pathology of the hippocampus, a key structure involved in relational memory, including episodic, semantic, and spatial memory processes. While it is widely accepted that TLE-associated hippocampal alterations underlie memory deficits, it remains unclear whether impairments relate to a specific cognitive domain or multiple ones.

METHODS

We administered a recently validated task paradigm to evaluate episodic, semantic, and spatial memory in 24 pharmacoresistant TLE patients and 50 age- and sex-matched healthy controls. We carried out two-way analyses of variance to identify memory deficits in individuals with TLE relative to controls across different relational memory domains, and used partial least squares correlation to identify factors contributing to variations in relational memory performance across both cohorts.

RESULTS

Compared to controls, TLE patients showed marked impairments in episodic and spatial memory, with mixed findings in semantic memory. Even when additionally controlling for age, sex, and overall cognitive function, between-group differences persisted along episodic and spatial domains. Moreover, age, diagnostic group, and hippocampal volume were all associated with relational memory behavioral phenotypes.

SIGNIFICANCE

Our behavioral findings show graded deficits across relational memory domains in people with TLE, which provides further insights into the complex pattern of cognitive impairment in the condition.

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.

Cortical Thickness Patterns of Cognitive Impairment Phenotypes in Drug-Resistant Temporal Lobe Epilepsy

OBJECTIVE

In temporal lobe epilepsy (TLE), a taxonomy classifying patients into 3 cognitive phenotypes has been adopted: minimally, focally, or multidomain cognitively impaired (CI). We examined gray matter (GM) thickness patterns of cognitive phenotypes in drug-resistant TLE and assessed potential use for predicting postsurgical cognitive outcomes.

METHODS

TLE patients undergoing presurgical evaluation were categorized into cognitive phenotypes. Network edge weights and distances were calculated using type III analysis of variance F-statistics from comparisons of GM regions within each TLE cognitive phenotype and age- and sex-matched healthy participants. In resected patients, logistic regression models (LRMs) based on network analysis results were used for prediction of postsurgical cognitive outcome.

RESULTS

A total of 124 patients (63 females, mean age ± standard deviation [SD] = 36.0 ± 12.0 years) and 117 healthy controls (63 females, mean age ± SD = 36.1 ± 12.0 years) were analyzed. In the multidomain CI group (n = 66, 53.2%), 28 GM regions were significantly thinner compared to healthy controls. Focally impaired patients (n = 37, 29.8%) showed 13 regions, whereas minimally impaired patients (n = 21, 16.9%) had 2 significantly thinner GM regions. Regions affected in both multidomain and focally impaired patients included the anterior cingulate cortex, medial prefrontal cortex, medial temporal, and lateral temporal regions. In 69 (35 females, mean age ± SD = 33.6 ± 18.0 years) patients who underwent surgery, LRMs based on network-identified GM regions predicted postsurgical verbal memory worsening with a receiver operating curve area under the curve of 0.70 ± 0.15.

INTERPRETATION

A differential pattern of GM thickness can be found across different cognitive phenotypes in TLE. Including magnetic resonance imaging with clinical measures associated with cognitive profiles has potential in predicting postsurgical cognitive outcomes in drug-resistant TLE. ANN NEUROL 2024;95:984-997.

Neurobehavioral and Clinical Comorbidities in Epilepsy: The Role of White Matter Network Disruption

Epilepsy is a common neurological disorder associated with alterations in cortical and subcortical brain networks. Despite a historical focus on gray matter regions involved in seizure generation and propagation, the role of white matter (WM) network disruption in epilepsy and its comorbidities has sparked recent attention. In this review, we describe patterns of WM alterations observed in focal and generalized epilepsy syndromes and highlight studies linking WM disruption to cognitive and psychiatric comorbidities, drug resistance, and poor surgical outcomes. Both tract-based and connectome-based approaches implicate the importance of extratemporal and temporo-limbic WM disconnection across a range of comorbidities, and an evolving literature reveals the utility of WM patterns for predicting outcomes following epilepsy surgery. We encourage new research employing advanced analytic techniques (e.g., machine learning) that will further shape our understanding of epilepsy as a network disorder and guide individualized treatment decisions. We also address the need for research that examines how neuromodulation and other treatments (e.g., laser ablation) affect WM networks, as well as research that leverages larger and more diverse samples, longitudinal designs, and improved magnetic resonance imaging acquisitions. These steps will be critical to ensuring generalizability of current research and determining the extent to which neuroplasticity within WM networks can influence patient outcomes.

Altered white matter organization and its correlations with executive functioning among adolescents with epilepsy

Deficits in executive functions (EF) are a common comorbidity among adolescents with epilepsy. EF deficits were previously correlated with altered connectivity of the fronto-parietal and cingulo-opercular neural networks. The current study investigated white matter integrity in adolescents with epilepsy (n = 29) relative to healthy controls (n = 19). Participants completed questionnaires, neuropsychological testing, and brain magnetic resonance imaging (MRI) that included diffusion tensor imaging (DTI) sequences. On BRIEF parent-report questionnaires, adolescents with epilepsy demonstrated lower working memory and planning abilities than healthy controls. Among adolescents with epilepsy, DTI measurements revealed lower fractional anisotropy (FA) within the right superior longitudinal fasciculus, forceps minor, and the superior frontal segment of the corpus callosum, and higher FA in the left uncinate fasciculus, compared to healthy controls. Better working memory ability in the epilepsy group was associated with higher FA in the superior frontal segment of the corpus callosum. Only in healthy controls, working memory and planning were positively associated with FA values in the left UF, forceps minor and the superior frontal segment of the corpus callosum. The current study complements previous functional studies on the same cohort and suggests that EF impairments among adolescents with epilepsy may be related to the altered anatomical organization of white matter tracts. Combining structural and functional data could potentially enrich the neuropsychological assessment of executive functioning in adolescents with epilepsy.

Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy

Temporal lobe epilepsy (TLE), one of the most common pharmaco-resistant epilepsies, is associated with pathology of paralimbic brain regions, particularly in the mesiotemporal lobe. Cognitive dysfunction in TLE is frequent, and particularly affects episodic memory. Crucially, these difficulties challenge the quality of life of patients, sometimes more than seizures, underscoring the need to assess neural processes of cognitive dysfunction in TLE to improve patient management. Our work harnessed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between cortical areas based on high-resolution MRI analysis. Gradients track region-to-region variations in intracortical lamination and myeloarchitecture, serving as a system-level measure of structural and functional reorganization. Comparing cortex-wide microstructural gradients between 21 patients and 35 healthy controls, we observed a reorganization of this gradient in TLE driven by reduced microstructural differentiation between paralimbic cortices and the remaining cortex with marked abnormalities in ipsilateral temporopolar and dorsolateral prefrontal regions. Findings were replicated in an independent cohort. Using an independent post-mortem dataset, we observed that in vivo findings reflected topographical variations in cortical cytoarchitecture. We indeed found that macroscale changes in microstructural differentiation in TLE reflected increased similarity of paralimbic and primary sensory/motor regions. Disease-related transcriptomics could furthermore show specificity of our findings to TLE over other common epilepsy syndromes. Finally, microstructural dedifferentiation was associated with cognitive network reorganization seen during an episodic memory functional MRI paradigm and correlated with interindividual differences in task accuracy. Collectively, our findings showing a pattern of reduced microarchitectural differentiation between paralimbic regions and the remaining cortex provide a structurally-grounded explanation for large-scale functional network reorganization and cognitive dysfunction characteristic of TLE.

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.

Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia

Our study assessed diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) in pediatric subjects with epilepsy secondary to Focal Cortical Dysplasia (FCD) to improve our understanding of structural network changes associated with FCD related epilepsy. We utilized a data harmonization (DH) approach to minimize confounding effects induced by MRI protocol differences. We also assessed correlations between DTI metrics and neurocognitive measures of the fluid reasoning index (FRI), verbal comprehension index (VCI), and visuospatial index (VSI). Data (n = 51) from 23 FCD patients and 28 typically developing controls (TD) scanned clinically on either 1.5T, 3T, or 3T-wide-bore MRI were retrospectively analyzed. Tract-based spatial statistics (TBSS) with threshold-free cluster enhancement and permutation testing with 100,000 permutations were used for statistical analysis. To account for imaging protocol differences, we employed non-parametric data harmonization prior to permutation testing. Our analysis demonstrates that DH effectively removed MRI protocol-based differences typical in clinical acquisitions while preserving group differences in DTI metrics between FCD and TD subjects. Furthermore, DH strengthened the association between DTI metrics and neurocognitive indices. Fractional anisotropy, MD, and RD metrics showed stronger correlation with FRI and VSI than VCI. Our results demonstrate that DH is an integral step to reduce the confounding effect of MRI protocol differences during the analysis of white matter tracts and highlights biological differences between FCD and healthy control subjects. Characterization of white matter changes associated with FCD-related epilepsy may better inform prognosis and treatment approaches.

Moving towards a taxonomy of cognitive impairments in epilepsy: application of latent profile analysis to 1178 patients with temporal lobe epilepsy

In efforts to understand the cognitive heterogeneity within and across epilepsy syndromes, cognitive phenotyping has been proposed as a new taxonomy aimed at developing a harmonized approach to cognitive classification in epilepsy. Data- and clinically driven approaches have been previously used with variability in the phenotypes derived across studies. In our study, we utilize latent profile analysis to test several models of phenotypes in a large multicentre sample of patients with temporal lobe epilepsy and evaluate their demographic and clinical profiles. For the first time, we examine the added value of replacing missing data and examine factors that may be contributing to missingness. A sample of 1178 participants met the inclusion criteria for the study, which included a diagnosis of temporal lobe epilepsy and the availability of comprehensive neuropsychological data. Models with two to five classes were examined using latent profile analysis and the optimal model was selected based on fit indices, posterior probabilities and proportion of sample sizes. The models were also examined with imputed data to investigate the impact of missing data on model selection. Based on the fit indices, posterior probability and distinctiveness of the latent classes, a three-class solution was the optimal solution. This three-class solution comprised a group of patients with multidomain impairments, a group with impairments predominantly in language and a group with no impairments. Overall, the multidomain group demonstrated a worse clinical profile and comprised a greater proportion of patients with mesial temporal sclerosis, a longer disease duration and a higher number of anti-seizure medications. The four-class and five-class solutions demonstrated the lowest probabilities of a group membership. Analyses with imputed data demonstrated that the four-class solution was the optimal solution; however, there was a weak agreement between the missing and imputed data sets for the four-Class solutions (κ = 0.288, P < 0.001). This study represents the first to use latent profile analysis to test and compare multiple models of cognitive phenotypes in temporal lobe epilepsy and to determine the impact of missing data on model fit. We found that the three-phenotype model was the most meaningful based on several fit indices and produced phenotypes with unique demographic and clinical profiles. Our findings demonstrate that latent profile analysis is a rigorous method to identify phenotypes in large, heterogeneous epilepsy samples. Furthermore, this study highlights the importance of examining the impact of missing data in phenotyping methods. Our latent profile analysis-derived phenotypes can inform future studies aimed at identifying cognitive phenotypes in other neurological disorders.

Neuropsychological Phenotypes in Pediatric Temporal Lobe Epilepsy

OBJECTIVE

Adults with temporal lobe epilepsy (TLE) have been found to have a fairly characteristic pattern of neuropsychological performance, but there is considerably less research and more variability in findings with children. Because the cognitive domains included in most studies with children have been limited, the current study attempted to better characterize the cognitive phenotype of children with TLE using a broader neuropsychological battery.

METHODS

The study included 59 children with TLE (59% male) age 7 to 16 (M = 12.67; SD = 3.12) who underwent comprehensive neuropsychological evaluation. Patient results were grouped into cognitive domains (reasoning, language, visuoperceptual, verbal memory, executive function, and motor function) based upon their test performance. These factor scores were subjected to Ward's hierarchical clustering method with squared Euclidean distance.

RESULTS

Cluster analysis revealed three distinct cognitive profiles: (1) normal functioning (20% of sample); (2) delayed verbal memory and motor weaknesses (61% of the sample); and (3) global impairment (19% of the sample). Cluster 3 had longer epilepsy duration and a higher incidence of hippocampal sclerosis (HS) compared to Cluster 1 (p < .05). There were no significant differences among the three cluster groups on demographic characteristics or remaining clinical characteristics.

CONCLUSIONS

Children with TLE present with distinct cognitive phenotypes ranging from average performance to global impairment. Results partially support previous hypotheses highlighting the cumulative neurobiological burden on the developing brain in the context of chronic epilepsy and provide a preliminary framework for the cognitive domains most vulnerable to the TLE disease process.

Global network alterations of the cognitive phenotypes in pediatric temporal lobe epilepsy

OBJECTIVE

An emerging literature suggests that the neuropsychological sequelae of pediatric temporal lobe epilepsy (TLE) are characterized by a continuum of cognitive phenotypes that range in type and severity. The goal of the present investigation was to better characterize the neuropsychological networks that underlie these phenotypes.

METHODS

The study included 59 patients with TLE who were empirically categorized into three cognitive phenotypes (normal, focal, and generalized impairment). Nine neuropsychological measures representing multiple cognitive domains (i.e., reasoning, language, visouperception, memory, and executive function) were examined by graph theory to characterize the global network properties of the cognitive phenotypes.

RESULTS

Across the cognitive phenotype groups (i.e., normal, focal, generalized impaired) the following findings emerged: (1) the adjacency matrices demonstrated different patterns of association between cognitive measures within the neuropsychological network; (2) global measures including global efficiency (GE) and average clustering coefficient (aCC) showed a stepwise increase across the range of impaired pediatric TLE phenotypes; however, modularity (M) demonstrated the opposite pattern.

IMPRESSIONS

Cognitive networks in pediatric TLE demonstrate stepwise perturbation in underlying neuropsychological networks. Graph theory offers a novel approach to examine cognitive abnormalities in pediatric TLE that may be applied to other pediatric epilepsies.

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.

Investigation of synapses in the cortical white matter in human temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is one of the most common focal pharmacotherapy-resistant epilepsy in adults. Previous studies have shown significantly higher numbers of neurons in the neocortical white matter in TLE patients than in controls. The aim of this work was to investigate whether white matter neurons are part of the neuronal circuitry. Therefore, we studied the distribution and density of synapses in surgically resected neocortical tissue of pharmacotherapy-resistant TLE patients. Neocortical white matter of temporal lobe from non-epileptic patients were used as controls. Synapses and neurons were visualized with immunohistochemistry using antibodies against synaptophysin and NeuN, respectively. The presence of synaptophysin in presynaptic terminals was verified by electron microscopy. Quantification of immunostaining was performed and the data of the patients' cognitive tests as well as clinical records were compared to the density of neurons and synapses. Synaptophysin density in the white matter of TLE patients was significantly higher than in controls. In TLE, a significant correlation was found between synaptophysin immunodensity and density of white matter neurons. Neuronal as well as synaptophysin density significantly correlated with scores of verbal memory of TLE patients. Neurosurgical outcome of TLE patients did not significantly correlate with histological data, although, higher neuronal and synaptophysin densities were observed in patients with favorable post-surgical outcome. Our results suggest that white matter neurons in TLE patients receive substantial synaptic input and indicate that white matter neurons may be integrated in epileptic neuronal networks responsible for the development or maintenance of seizures.

Alterations in Neural Networks During Working Memory Encoding Related to Cognitive Impairment in Temporal Lobe Epilepsy

Objective: The aim of the current study was to investigate the alterations in the neural networks of patients with temporal lobe epilepsy (TLE) during working memory (WM) encoding.

Methods: Patients with TLE (n = 52) and healthy volunteers (n = 35) completed a WM task, during which 34-channel electroencephalogram signals were recorded. The neural networks during WM encoding were calculated in TLE patients with (TLE-WM) and without (TLE-N) WM deficits.

Results: Functional connectivity strength decreased, and the theta network was altered in the TLE-WM group, although no significant differences in clinical features were observed between the TLE-N and TLE-WM groups.

Conclusions: Not all patients with TLE present with cognitive impairments and alterations in the theta network were identified in TLE patients with functional cognitive deficits.

Significance: The theta network may represent a sensitive measure of cognitive impairment and could predict cognitive outcomes among patients with TLE.

Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy

Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.

Prediction of the clinical and naming status after anterior temporal lobe resection in patients with epilepsy

By assessing the cognitive capital, neuropsychological evaluation (NPE) plays a vital role in the perioperative workup of patients with refractory focal epilepsy. In this retrospective study, we used cutting-edge statistical approaches to examine a group of 47 patients with refractory temporal lobe epilepsy (TLE), who underwent standard anterior temporal lobectomy (ATL). Our objective was to determine whether NPE may represent a robust predictor of the postoperative status, two years after surgery. Specifically, based on pre- and postsurgical neuropsychological data, we estimated the sensitivity of cognitive indicators to predict and to disentangle phenotypes associated with more or less favorable outcomes. Engel (ENG) scores were used to assess clinical outcome, and picture naming (NAM) performance to estimate naming status. Two methods were applied: (a) machine learning (ML) to explore cognitive sensitivity to postoperative outcomes; and (b) graph theory (GT) to assess network properties reflecting favorable vs. less favorable phenotypes after surgery. Specific neuropsychological indices assessing language, memory, and executive functions can globally predict outcomes. Interestingly, preoperative cognitive networks associated with poor postsurgical outcome already exhibit an atypical, highly modular and less densely interconnected configuration. We provide statistical and clinical tools to anticipate the condition after surgery and achieve a more personalized clinical management. Our results also shed light on possible mechanisms put in place for cognitive adaptation after acute injury of central nervous system in relation with surgery.

The Impact of Right Temporal Lobe Epilepsy On Nonverbal Memory: Meta-regression of Stimulus- and Task-related Moderators

Nonverbal memory tests have great potential value for detecting the impact of lateralized pathology and predicting the risk of memory loss following right temporal lobe resection (TLR) for temporal lobe epilepsy (TLE) patients, but this potential has not been realized. Previous reviews suggest that stimulus type moderates the capacity of nonverbal memory tests to detect right-lateralized pathology (i.e., faces > designs), but the roles of other task-related factors have not been systematically explored. We address these limitations using mixed model meta-regression (k = 158) of right-lateralization effects (right worse than left TLE) testing the moderating effects of: 1) stimulus type (designs, faces, spatial), 2) learning format (single trial, repeated trials), 3) testing delay (immediate or long delay), and 4) testing format (recall, recognition) for three patient scenarios: 1) presurgical, 2) postsurgical, and 3) postsurgical change. Stimulus type significantly moderated the size of the right-lateralization effect (faces > designs) for postsurgical patients, test format moderated the size of the right-lateralization effect for presurgical-postsurgical change (recognition > recall) but learning format and test delay had no right-lateralization effect for either sample. For presurgical patients, none of the task-related factors significantly increased right-lateralization effects. This comprehensive review reveals the value of recognition testing in gauging the risk of nonverbal memory decline.

Application value of molecular imaging technology in epilepsy

Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.

Behavioral phenotypes of temporal lobe epilepsy

Objective

To identity phenotypes of self‐reported symptoms of psychopathology and their correlates in patients with temporal lobe epilepsy (TLE).

Method

96 patients with TLE and 82 controls were administered the Symptom Checklist 90‐Revised (SCL‐90‐R) to characterize emotional‐behavioral status. The nine symptom scales of the SCL‐90‐R were analyzed by unsupervised machine learning techniques to identify latent TLE groups. Identified clusters were contrasted to controls to characterize their association with sociodemographic, clinical epilepsy, neuropsychological, psychiatric, and neuroimaging factors.

Results

TLE patients as a group exhibited significantly higher (abnormal) scores across all SCL‐90‐R scales compared to controls. However, cluster analysis identified three latent groups: (1) unimpaired with no scale elevations compared to controls (Cluster 1, 42% of TLE patients), (2) mild‐to‐moderate symptomatology characterized by significant elevations across several SCL‐90‐R scales compared to controls (Cluster 2, 35% of TLE patients), and (3) marked symptomatology with significant elevations across all scales compared to controls and the other TLE phenotype groups (Cluster 3, 23% of TLE patients). There were significant associations between cluster membership and demographic (education), clinical epilepsy (perceived seizure severity, bitemporal lobe seizure onset), and neuropsychological status (intelligence, memory, executive function), but with minimal structural neuroimaging correlates. Concurrent validity of the behavioral phenotype grouping was demonstrated through association with psychiatric (current and lifetime‐to‐date DSM IV Axis 1 disorders and current treatment) and quality‐of‐life variables.

Significance

Symptoms of psychopathology in patients with TLE are characterized by a series of discrete phenotypes with accompanying sociodemographic, cognitive, and clinical correlates. Similar to cognition in TLE, machine learning approaches suggest a developing taxonomy of the comorbidities of epilepsy.

Network topology of the cognitive phenotypes of temporal lobe epilepsy

PURPOSE

The neuropsychological complications of temporal lobe epilepsy are characterized by a spectrum of reproducible cognitive phenotypes that vary in the presence, type and degree of impairment. The nature of the disruptions to the neuropsychological networks that underlie these phenotypes remain to be characterized and represent the subject of this investigation.

METHODS

Participants included 30 healthy controls and 104 patients with temporal lobe epilepsy who fell into three cognitive phenotypes (intact, focal impairment, generalized impairment). Eighteen neuropsychological measures representing multiple cognitive domains (language, memory, executive function, visuoperception, motor speed) were examined by graph theory techniques within the control and each epilepsy cognitive phenotype group to characterize their global and local network properties.

RESULTS

Across the control and epilepsy cognitive phenotype groups (intact to focal to generalized impairment), there was: 1) an orderly breakdown in the positive manifold reflected by a stepwise reduction of positive associations among the neuropsychological tests, 2) stepwise abnormal increases in global measures including the normalized clustering coefficient and modularity index, 3) stepwise abnormal decreases in normalized global efficiency, 4) a community structure demonstrating well organized modules within the control group while each epilepsy group showed deviations from controls, and 5) lower strength, compared to controls, across 8 nodes in the focal and generalized impairment groups compared to only 3 nodes in the no-impairment epilepsy group, pointing to the superior integration of local connections in controls.

DISCUSSION

The cognitive phenotypes of temporal lobe epilepsy are characterized by orderly abnormalities in their underlying neuropsychological networks. These findings inform the network perturbations that underlie the taxonomy of cognitive abnormality in temporal lobe epilepsy and provide a model for examination of similar issues in other focal and generalized epilepsies.

Altered communication dynamics reflect cognitive deficits in temporal lobe epilepsy

OBJECTIVE

Although temporal lobe epilepsy (TLE) is recognized as a system-level disorder, little work has investigated pathoconnectomics from a dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested the hypothesis that network communication is abnormal in this condition, studied the interplay between hippocampal- and network-level disease effects, and assessed associations with cognition.

METHODS

We simulated signal spreading via a linear threshold model that temporally evolves on a structural graph derived from diffusion-weighted magnetic resonance imaging (MRI), comparing a homogeneous group of 31 patients with histologically proven hippocampal sclerosis to 31 age- and sex-matched healthy controls. We evaluated the modulatory effects of structural alterations of the neocortex and hippocampus on network dynamics. Furthermore, multivariate statistics addressed the relationship with cognitive parameters.

RESULTS

We observed a slowing of in- and out-spreading times across multiple areas bilaterally, indexing delayed information flow, with the strongest effects in ipsilateral frontotemporal regions, thalamus, and hippocampus. Effects were markedly reduced when controlling for hippocampal volume but not cortical thickness, underscoring the central role of the hippocampus in whole-brain disease expression. Multivariate analysis associated slower spreading time in frontoparietal, limbic, default mode, and subcortical networks with impairment across tasks tapping into sensorimotor, executive, memory, and verbal abilities.

SIGNIFICANCE

Moving beyond descriptions of static topology toward the formulation of brain dynamics, our work provides novel insight into structurally mediated network dysfunction and demonstrates that altered whole-brain communication dynamics contribute to common cognitive difficulties in TLE.

Associations of individual and structural socioeconomic status with cognition and mental distress in pharmacoresistant focal epilepsy

OBJECTIVE

Epilepsy is often associated with low socioeconomic status (SES). People with epilepsy (PWE) also suffer from cognitive dysfunction and mental distress. In the general population, these constraints are related to individual and structural SES. However, in PWE, cognitive dysfunction and mental distress have been mainly attributed to biological factors such as brain lesions or pharmacological treatment, whereas comprehensive studies on possible social determinants are missing. Here, we study associations of individual and structural SES with cognition and mental distress in PWE.

METHODS

We retrospectively studied 340 adult patients with pharmacoresistant focal epilepsy from Berlin treated at a tertiary epilepsy center. Individual SES (education, employment, and income), structural SES (social index of district and neighborhood), and their interactions were examined. Associations between social variables and verbal learning, psychomotor speed, and mental distress were analyzed with multiple regression analyses, controlling for demographic and medical variables and intelligence.

RESULTS

Our sample had lower educational levels and lived more frequently in low SES neighborhoods compared to the general population of Berlin. Thirty percent showed reduced verbal learning, 31% had deficits in psychomotor speed, and 20% revealed significant mental distress. Lower structural SES was related to lower psychomotor speed (ΔR² = 0.9%) and higher mental distress (ΔR² = 1.6%). Employment was related to verbal learning (ΔR² = 0.7%) and psychomotor speed (ΔR² = 1.2%). Income and education were linked to mental distress (ΔR² = 5%). Neighborhood and individual SES covered more than half of the explained variance in mental distress. Furthermore, interactions between individual and structural SES were identified.

CONCLUSION

We confirm cognitive deficits, significant mental distress, and individual and structural social disadvantage in PWE. Our findings indicate that individual and structural SES are related to cognitive and emotional well-being beyond demographic and medical characteristics. As a clinical implication, individual and structural SES should be considered when interpreting neuropsychological findings.

Anatomical Variations, Mimics, and Pitfalls in Imaging of Patients with Epilepsy

Epilepsy is among one of the most common neurologic disorders. The role of magnetic resonance imaging (MRI) in the diagnosis and management of patients with epilepsy is well established, and most patients with epilepsy are likely to undergo at least one or more MRI examinations in the course of their disease. Recent advances in high-field MRI have enabled high resolution in vivo visualization of small and intricate anatomic structures that are of great importance in the assessment of seizure disorders. Familiarity with normal anatomic variations is essential in the accurate diagnosis and image interpretation, as these variations may be mistaken for epileptogenic foci, leading to unnecessary follow-up imaging, or worse, unnecessary treatment. After a brief overview of normal imaging anatomy of the mesial temporal lobe, this article will review a few important common and uncommon anatomic variations, mimics, and pitfalls that may be encountered in the imaging evaluation of patients with epilepsy.

Network, clinical and sociodemographic features of cognitive phenotypes in temporal lobe epilepsy

This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

Behavioral phenotypes of childhood idiopathic epilepsies

OBJECTIVE

To characterize the presence and nature of discrete behavioral phenotypes and their correlates in a cohort of youth with new and recent onset focal and generalized epilepsies.

METHODS

The parents of 290 youth (age = 8-18 years) with epilepsy (n = 183) and typically developing participants (n = 107) completed the Child Behavior Checklist for children aged 6-18 from the Achenbach System of Empirically Based Assessment. The eight behavior problem scales were subjected to hierarchical clustering analytics to identify behavioral subgroups. To characterize the external validity and co-occurring comorbidities of the identified subgroups, we examined demographic features (age, gender, handedness), cognition (language, perception, attention, executive function, speed), academic problems (present/absent), clinical epilepsy characteristics (epilepsy syndrome, medications), familial factors (parental intelligence quotient, education, employment), neuroimaging features (cortical thickness), parent-observed day-to-day executive function, and number of lifetime-to-date Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) diagnoses.

RESULTS

Hierarchical clustering identified three behavioral phenotypes, which included no behavioral complications (Cluster 1, 67% of epilepsy cohort [n = 122]), nonexternalizing problems (Cluster 2, 11% of cohort [n = 21]), and combined internalizing and externalizing problems (Cluster 3, 22% of cohort [n = 40]). These behavioral phenotypes were characterized by orderly differences in personal characteristics, neuropsychological status, history of academic problems, parental status, cortical thickness, daily executive function, and number of lifetime-to-date DSM-IV diagnoses. Cluster 1 was most similar to controls across most metrics, whereas Cluster 3 was the most abnormal compared to controls. Epilepsy syndrome was not a predictor of cluster membership.

SIGNIFICANCE

Youth with new and recent onset epilepsy fall into three distinct behavioral phenotypes associated with a variety of co-occurring features and comorbidities. This approach identifies important phenotypes of behavior problem presentations and their accompanying factors that serve to advance clinical and theoretical understanding of the behavioral complications of children with epilepsy and the complex conditions with which they co-occur.

Clinical utility of structural connectomics in predicting memory in temporal lobe epilepsy

OBJECTIVE

To determine the predictive power of white matter neuronal networks (i.e., structural connectomes [SCs]) in discriminating memory-impaired patients with temporal lobe epilepsy (TLE) from those with normal memory.

METHODS

T1- and diffusion MRI (dMRI), clinical variables, and neuropsychological measures of verbal memory were available for 81 patients with TLE. Prediction of memory impairment was performed with a tree-based classifier (XGBoost) for 4 models: (1) a clinical model including demographic and clinical features, (2) a hippocampal volume (HCV) model, (3) a tract model including 5 temporal lobe white matter association tracts derived from a dMRI atlas, and (4) an SC model based on dMRI. SCs were derived by extracting cortical-cortical connections from a temporal lobe subnetwork with probabilistic tractography. Principal component (PC) analysis was then applied to reduce the dimensionality of the SC, yielding 10 PCs. Multimodal models were also tested combining SCs and tracts with HCV. Each model was trained on 48 patients from 1 epilepsy center and tested on 33 patients from a different center.

RESULTS

Multimodal models that included the SC + HCV model yielded the highest classification accuracy (81%; 0.90 sensitivity; 0.67 specificity), outperforming the clinical model (61%; p < 0.001) and HCV model (66%; p < 0.001). In addition, the unimodal SC model (76% accuracy) and tract model (73% accuracy) outperformed the clinical model (p < 0.001) and HCV model (p < 0.001) for classifying patients with TLE with and without memory impairment. Furthermore, the SC identified that short-range temporal-temporal connections were important contributors to memory performance.

CONCLUSION

SCs and tract-based models are stronger predictors of memory impairment in TLE than HCVs and clinical variables. However, SCs may provide additional information about local cortical-cortical connectivity contributing to memory that is not captured in large association tracts.

Cognitive phenotypes in temporal lobe epilepsy utilizing data- and clinically driven approaches: Moving toward a new taxonomy

OBJECTIVE

To identify cognitive phenotypes in temporal lobe epilepsy (TLE) and test their reproducibility in a large, multi-site cohort of patients using both data-driven and clinically driven approaches.

METHOD

Four-hundred seven patients with TLE who underwent a comprehensive neuropsychological evaluation at one of four epilepsy centers were included. Scores on tests of verbal memory, naming, fluency, executive function, and psychomotor speed were converted into z-scores based on 151 healthy controls (HCs). For the data-driven method, cluster analysis (k-means) was used to determine the optimal number of clusters. For the clinically driven method, impairment was defined as >1.5 standard deviations below the mean of the HC, and patients were classified into groups based on the pattern of impairment.

RESULTS

Cluster analysis revealed a three-cluster solution characterized by (a) generalized impairment (29%), (b) language and memory impairment (28%), and (c) no impairment (43%). Based on the clinical criteria, the same broad categories were identified, but with a different distribution: (a) generalized impairment (37%), (b) language and memory impairment (30%), and (c) no impairment (33%). There was a 82.6% concordance rate with good agreement (κ = .716) between the methods. Forty-eight patients classified as having a normal profile based on cluster analysis were classified as having generalized impairment (n = 16) or an isolated language/memory impairment (n = 32) based on the clinical criteria. Patients with generalized impairment had a longer disease duration and patients with no impairment had more years of education. However, patients demonstrating the classic TLE profile (ie, language and memory impairment) were not more likely to have an earlier age at onset or mesial temporal sclerosis.

SIGNIFICANCE

We validate previous findings from single-site studies that have identified three unique cognitive phenotypes in TLE and offer a means of translating the patterns into a clinical diagnostic criteria, representing a novel taxonomy of neuropsychological status in TLE.

Functional brain network mechanism of executive control dysfunction in temporal lobe epilepsy

Background

Executive control dysfunction is observed in a sizable number of patients with temporal lobe epilepsy (TLE). Neural oscillations in the theta band are increasingly recognized as having a crucial role in executive control network. The purpose of this study was to investigate the alterations in the theta band in executive control network and explore the functional brain network mechanisms of executive control dysfunction in TLE patients.

Methods

A total of 20 TLE patients and 20 matched healthy controls (HCs) were recruited in the present study. All participants were trained to perform the executive control task by attention network test while the scalp electroencephalogram (EEG) data were recorded. The resting state signals were collected from the EEG in the subjects with quiet and closed eyes conditions. Functional connectivity among EEGs in the executive control network and resting state network were respectively calculated.

Results

We found the significant executive control impairment in the TLE group. Compared to the HCs, the TLE group showed significantly weaker functional connectivity among EEGs in the executive control network. Moreover, in the TLE group, we found that the functional connectivity was significantly positively correlated with accuracy and negatively correlated with EC_effect. In addition, the functional connectivity of the executive control network was significantly higher than that of the resting state network in the HCs. In the TLE group, however, there was no significant change in functional connectivity strengths between the executive control network and resting state network.

Conclusion

Our results indicate that the decreased functional connectivity in theta band may provide a potential mechanism for executive control deficits in TLE patients.

Prediction of Memory Impairment in Epilepsy Surgery by White Matter Diffusion

OBJECTIVE

To analyze the relationship between cognitive performance and white matter integrity in patients with temporal lobe epilepsy (TLE) to establish radiologic criteria to help with patient selection for surgery.

METHODS

The study included 19 adults with temporal lobe epilepsy. A tractography analysis of fractional anisotropy and mean diffusivity (MD) of the following fascicles was performed: arcuate fascicle, cingulum, fornix, inferior fronto-occipital fascicle, inferior longitudinal fascicle, parahippocampal fibers of the cingulum, and uncinate fascicle. The Wechsler Memory Scale-Third Edition neuropsychological test was performed to evaluate short- and long-term verbal (Logical Memory I and II subtests) and nonverbal (Visual Reproduction I and II subtests) memory. Relationships between memory scores and diffusion were calculated.

RESULTS

Lower Logical Memory I subtest scores were correlated with lower MD of the right inferior fronto-occipital fascicle, while lower Logical Memory II subtest scores were related to higher values of fractional anisotropy in bilateral cingulum, right uncinate, and right parahippocampal fibers of the cingulum and lower MD in left cingulum fascicle. Finally, lower values in Visual Reproduction I subtest scores were associated with lower values in MD in right cingulum and inferior fronto-occipital fascicles.

CONCLUSIONS

Structural changes of some white matter tracts were associated with deterioration of both short- and long-term memory. These alterations were more associated with verbal memory than with nonverbal memory. These changes mainly consist of an increase in fractional anisotropy and a decrease in MD, which could be interpreted as reorganization phenomena. Diffusion tensor imaging could be a useful tool for cognitive assessment in surgical candidates with temporal lobe epilepsy who are not suitable for neuropsychological testing or in whom their results do not lead to definitive conclusions.

Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) is known to affect large-scale structural networks and cognitive function in multiple domains. The study of complex relations between structural network organization and cognition requires comprehensive analytical methods and a shift towards multivariate techniques. Here, we sought to identify multidimensional associations between cognitive performance and structural network topology in TLE.

METHODS

We studied 34 drug-resistant adult TLE patients and 24 age- and sex-matched healthy controls. Participants underwent a comprehensive neurocognitive battery and multimodal MRI, allowing for large-scale connectomics, and morphological evaluation of subcortical and neocortical regions. Using canonical correlation analysis, we identified a multivariate mode that links cognitive performance to a brain structural network. Our approach was complemented by bootstrap-based hierarchical clustering to derive cognitive subtypes and associated patterns of macroscale connectome anomalies.

RESULTS

Both methodologies provided converging evidence for a close coupling between cognitive impairments across multiple domains and large-scale structural network compromise. Cognitive classes presented with an increasing gradient of abnormalities (increasing cortical and subcortical atrophy and less efficient white matter connectome organization in patients with increasing degrees of cognitive impairments). Notably, network topology characterized cognitive performance better than morphometric measures did.

CONCLUSIONS

Our multivariate approach emphasized a close coupling of cognitive dysfunction and large-scale network anomalies in TLE. Our findings contribute to understand the complexity of structural connectivity regulating the heterogeneous cognitive deficits found in epilepsy.

The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy

OBJECTIVE

The distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.

METHODS

T1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.

RESULTS

The SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.

CONCLUSION

The SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance.

Identifying the neural basis of a language-impaired phenotype of temporal lobe epilepsy

OBJECTIVE

To identify neuroimaging and clinical biomarkers associated with a language-impaired phenotype in refractory temporal lobe epilepsy (TLE).

METHODS

Eighty-five patients with TLE were characterized as language-impaired (TLE-LI) or non-language-impaired (TLE-NLI) based on comprehensive neuropsychological testing. Structural magnetic resonance imaging (MRI), diffusion tensor imaging, and functional MRI (fMRI) were obtained in patients and 47 healthy controls (HC). fMRI activations and cortical thickness were calculated within language regions of interest, and fractional anisotropy (FA) was calculated within deep white matter tracts associated with language. Analyses of variance were performed to test for differences among the groups in imaging measures. Receiver operator characteristic curves were used to determine how well different clinical versus imaging measures discriminated TLE-LI from TLE-NLI.

RESULTS

TLE-LI patients showed significantly less activation within left superior temporal cortex compared to HC and TLE-NLI, regardless of side of seizure onset. TLE-LI also showed decreased FA in the inferior longitudinal fasciculus and arcuate fasciculus compared to HC. Cortical thickness did not differ between groups in any region. A model that included language-related fMRI activations within the superior temporal gyrus, age at onset, and demographic variables was the most predictive of language impairment (area under the curve = 0.80).

SIGNIFICANCE

These findings demonstrate a unique imaging signature associated with a language-impaired phenotype in TLE, characterized by functional and microstructural alterations within the language network. Reduced left superior temporal activation combined with compromise to language association tracts underlies this phenotype, extending our previous work on cognitive phenotypes that could have implications for treatment-planning or cognitive progression in TLE.

Demyelination-Remyelination of the Rat Caudal Cerebellar Peduncle Evaluated with Magnetic Resonance Imaging

Remyelination is common under physiological conditions and usually occurs as a response to a pathological demyelinating event. Its potentiation is an important goal for the development of therapies against pathologies such as multiple sclerosis and white matter injury. Visualization and quantification in vivo of demyelination and remyelination processes are essential for longitudinal studies that will allow the testing and development of pro-myelinating strategies. In this study, ethidium bromide (EB) was stereotaxically injected into the caudal cerebellar peduncle (c.c.p.) in rats to produce demyelination; the resulting lesion was characterized (i) transversally through histology using Black-Gold II (BGII) staining, and (ii) longitudinally through diffusion-weighted magnetic resonance imaging (dMRI), by computing fractional anisotropy (FA) and diffusivity parameters to detect microstructural changes. Using this characterization, we evaluated, in the lesioned c.c.p., the effect of N-butyl-β-carboline-3-carboxylate (β-CCB), a potentiator of GABAergic signaling in oligodendrocytes. The dMRI analysis revealed significant changes in the anisotropic and diffusivity properties of the c.c.p. A decreased FA and increased radial diffusivity (λ_⊥) were evident following c.c.p. lesioning. These changes correlated strongly with an apparent decrease in myelin content as evidenced by BGII. Daily systemic β-CCB administration for 2 weeks in lesioned animals increased FA and decreased λ_⊥, suggesting an improvement in myelination, which was supported by histological analysis. This study shows that structural changes in the demyelination-remyelination of the caudal cerebellar peduncle (DRCCP) model can be monitored longitudinally by MRI, and it suggests that remyelination is enhanced by β-CCB treatment. This article is part of a Special Issue entitled: Honoring Ricardo Miledi - outstanding neuroscientist of XX-XXI centuries.

Cognitive phenotypes in temporal lobe epilepsy are associated with distinct patterns of white matter network abnormalities

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.

The Impacts of Tumor and Tumor Associated Epilepsy on Subcortical Brain Structures and Long Distance Connectivity in Patients With Low Grade Glioma

Low grade gliomas in cerebral cortex often cause symptoms related to higher cerebral functions such as attention, memory and executive function before treatment is initiated. Interestingly, focal tumors residing in one cortical region can lead to a diverse range of symptoms, indicating that the impact of a tumor is extended to multiple brain regions. We hypothesize that the presence of focal glioma in the cerebral cortex leads to alterations of distant subcortical areas and essential white matter tracts. In this study, we analyzed diffusion tensor imaging scans in glioma patients to study the effect of glioma on subcortical gray matter nuclei and long-distance connectivity. We found that the caudate nucleus, putamen and thalamus were affected by cortical glioma, displaying both volumetric and diffusion alterations. The cerebellar cortex contralateral to the tumor side also showed significant volume decrease. Additionally, tractography of the cortico-striatal and cortico-thalamic projections shows similar diffusion alterations. Tumor associated epilepsy might be an important contributing factor to the found alterations. Our findings indeed confirm concurrent structural and connectivity abrasions of brain areas distant from brain tumor, and provide insights into the pathogenesis of diverse neurological symptoms in glioma patients.

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.