Neuroanatomical correlates of cognitive phenotypes in temporal lobe epilepsy

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.

Statistical learning in epilepsy: Behavioral and anatomical mechanisms in the human brain

OBJECTIVE

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe (MTL) in the healthy brain. This leads to the hypothesis that statistical learning (SL) may be impaired in patients with epilepsy (PWE) involving the temporal lobe, and that this impairment could contribute to their varied memory deficits. In turn, studies done in collaboration with PWE, that evaluate the necessity of MTL circuitry through disease and causal perturbations, provide an opportunity to advance basic understanding of SL.

METHODS

We implemented behavioral testing, volumetric analysis of the MTL substructures, and direct electrical brain stimulation to examine SL across a cohort of 61 PWE and 28 healthy controls.

RESULTS

We found that behavioral performance in an SL task was negatively associated with seizure frequency irrespective of seizure origin. The volume of hippocampal subfields CA1 and CA2/3 correlated with SL performance, suggesting a more specific role of the hippocampus. Transient direct electrical stimulation of the hippocampus disrupted SL. Furthermore, the relationship between SL and seizure frequency was selective, as behavioral performance in an episodic memory task was not impacted by seizure frequency.

SIGNIFICANCE

Overall, these results suggest that SL may be hippocampally dependent and that the SL task could serve as a clinically useful behavioral assay of seizure frequency that may complement existing approaches such as seizure diaries. Simple and short SL tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

Cognitive decline in adult-onset temporal lobe epilepsy: Insights from aetiology

PURPOSE

To identify patients with adult-onset temporal lobe epilepsy (TLE) at risk of developing cognitive decline. Detecting which patients, aetiologies, or factors are most closely related with memory decline would allow us to identify patients that would eventually benefit from more specific treatment.

METHODS

Single centre, retrospective analysis of a prospectively followed-up cohort study, including all patients with the diagnosis of adult-onset TLE during 2013, with a minimum follow-up of five years. Memory and cognitive decline were analysed at 5 years and at last follow-up.

RESULTS

Of 89 initially selected patients, 71 were included. After 5 years, 11/71 (15.5%) patients suffered cognitive decline, of which 1/71 (4%) developed dementia. At last follow-up (range 65-596 m) a total of 34/71 (47.8%) patients were diagnosed with cognitive decline, specifically either memory decline or dementia. Cognitive decline at 5 years was related to: 1. Age at onset: 62.65 years (SD 9.04) in the group with cognitive decline vs 50.33 y. (SD 13.02 in the group without cognitive decline; p=0.004); 2. Onset as status epilepticus (3/6 in patients with memory decline vs 8/65 in patients without cognitive decline; p=0.04); 3. Immune aetiology: 42% compared with unknown (10%) and structural (10%) aetiologies; p=0.036; 4. Hippocampal sclerosis on MRI: 5/11 patients with cognitive decline vs 9/51 patients without cognitive decline; p=0.035. Cognitive decline was not related to seizure frequency, sex, or age (p=0.78; p=0.40; p=0.95, respectively).

CONCLUSIONS

Older age at epilepsy onset, onset as status epilepticus, immune aetiology, and hippocampal sclerosis are risk factors for developing cognitive decline in patients with adult-onset temporal lobe epilepsy.

Morphological and metabolic asymmetries of the thalamic subregions in temporal lobe epilepsy predict cognitive functions

Both morphological and metabolic imaging were used to determine how asymmetrical changes of thalamic subregions are involved in cognition in temporal lobe epilepsy (TLE). We retrospectively recruited 24 left-TLE and 15 right-TLE patients. Six thalamic subnuclei were segmented by magnetic resonance imaging, and then co-registered onto Positron emission tomography images. We calculated the asymmetrical indexes of the volumes and normalized standard uptake value ratio (SUVR) of the entire and individual thalamic subnuclei. The SUVR of ipsilateral subnuclei were extensively and prominently decreased compared with the volume loss. The posterior and medial subnuclei had persistently lower SUVR in both TLE cases. Processing speed is the cognitive function most related to the metabolic asymmetry. It negatively correlated with the metabolic asymmetrical indexes of subregions in left-TLE, while positively correlated with the subnuclei volume asymmetrical indexes in right-TLE. Epilepsy duration negatively correlated with the volume asymmetry of most thalamic subregions in left-TLE and the SUVR asymmetry of ventral and intralaminar subnuclei in right-TLE. Preserved metabolic activity of contralateral thalamic subregions is the key to maintain the processing speed in both TLEs. R-TLE had relatively preserved volume of the ipsilateral thalamic volume, while L-TLE had relatively decline of volume and metabolism in posterior subnucleus.

The relationship between mood and anxiety and cognitive phenotypes in adults with pharmacoresistant temporal lobe epilepsy

OBJECTIVE

Patients with temporal lobe epilepsy (TLE) are often at a high risk for cognitive and psychiatric comorbidities. Several cognitive phenotypes have been identified in TLE, but it is unclear how phenotypes relate to psychiatric comorbidities, such as anxiety and depression. This observational study investigated the relationship between cognitive phenotypes and psychiatric symptomatology in TLE.

METHODS

A total of 826 adults (age = 40.3, 55% female) with pharmacoresistant TLE completed a neuropsychological evaluation that included at least two measures from five cognitive domains to derive International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) cognitive phenotypes (i.e., intact, single-domain impairment, bi-domain impairment, generalized impairment). Participants also completed screening measures for depression and anxiety. Psychiatric history and medication data were extracted from electronic health records. Multivariable proportional odds logistic regression models examined the relationship between IC-CoDE phenotypes and psychiatric variables after controlling for relevant covariates.

RESULTS

Patients with elevated depressive symptoms had a greater odds of demonstrating increasingly worse cognitive phenotypes than patients without significant depressive symptomatology (odds ratio [OR] = 1.123-1.993, all corrected p's < .05). Number of psychotropic (OR = 1.584, p < .05) and anti-seizure medications (OR = 1.507, p < .001), use of anti-seizure medications with mood-worsening effects (OR = 1.748, p = .005), and history of a psychiatric diagnosis (OR = 1.928, p < .05) also increased the odds of a more severe cognitive phenotype, while anxiety symptoms were unrelated.

SIGNIFICANCE

This study demonstrates that psychiatric factors are not only associated with function in specific cognitive domains but also with the pattern and extent of deficits across cognitive domains. Results suggest that depressive symptoms and medications are strongly related to cognitive phenotype in adults with TLE and support the inclusion of these factors as diagnostic modifiers for cognitive phenotypes in future work. Longitudinal studies that incorporate neuroimaging findings are warranted to further our understanding of the complex relationships between cognition, mood, and seizures and to determine whether non-pharmacologic treatment of mood symptoms alters cognitive phenotype.

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.

Outpatient visit behavior in patients with epilepsy: Generalized Epilepsy is more frequently non-attendance than Focal Epilepsy

BACKGROUND

Patients with epilepsy (PWE), especially those with Idiopathic Epilepsy (GE), are at a high risk of disadvantage caused by non-adherence. It has been suggested that medical visit behavior may be a surrogate indicator of medication adherence. We hypothesized that patients with IGE would adhere poorly to visits.

METHODS

This was a retrospective study of PWE who visited the Department of Psychiatry and Neurology at Hokkaido University Hospital between January 2017 and December 2019. Demographic and clinical information on PWE were extracted from medical records and visit data from the medical information system. Non-attendance of outpatient appointments was defined as "not showing up for the day of an appointment without prior notice." Mixed-effects logistic regression analysis was conducted with non-attendance as the objective variable.

RESULTS

Of the 9151 total appointments, 413 were non-attendances, with an overall non-attendance rate of 4.5%. IGE was a more frequent non-attendance than Focal Epilepsy (FE) (odds ratio (OR) 1.94; 95% confidence interval (CI) 1.17-3.21; p = 0.010). History of public assistance receipt was associated with higher non-attendance (OR 2.04; 95% CI 1.22-3.43; p = 0.007), while higher education (OR 0.64; 95% CI 0.43-0.93; p = 0.021) and farther distance to a hospital (OR 0.33; 95% CI 0.13-0.88; p = 0.022), and higher frequency of visits (OR 0.18; 95% CI 0.04-0.86; p = 0.031) were associated with fewer non-attendances. In a subgroup analysis of patients with GE, women were associated with fewer non-attendance (OR 0.31; 95% CI 0.14-0.72; p = 0.006).

CONCLUSIONS

GE was more frequent in the non-attendance group than in the FE group. Among patients with GE, females were found to have non-attendance less frequently; however, there was no clear difference in the odds of non-attendance between Juvenile Myoclonic Epilepsy (JME) and IGE other than JME.

Investigating the Impact of Epilepsy on Cognitive Function: A Narrative Review

It has been noted that people who have epilepsy have an increased propensity for cognitive dysfunction. We explored 25 relevant articles on PubMed and Cochrane Library after implementing inclusion criteria. Different factors have been postulated and studied that may cause cognitive dysfunction in these patients; structural brain abnormalities, polypharmacy of antiepileptic medication, and neuropsychiatric disorders are the most common causes. Cognitive assessments such as Montreal Cognitive Assessment (MOCA) and Mini-Mental State Exam (MMSE) are the mainstay tools used to diagnose the degree of cognitive decline, and alterations in EEG (electroencephalogram) parameters have also been noted in people with cognitive decline. The mechanisms and treatments for cognitive decline are still being studied, while attention has also been directed toward preventive and predictive methods. Early detection and treatment of cognitive impairment can help minimize its impact on the patient's quality of life. Regular cognitive assessments are essential for epileptic patients, particularly those on multiple antiepileptic drugs. While proper management of epilepsy and related comorbidities would reduce cognitive decline and improve the overall quality of life for people with epilepsy.

Statistical learning in epilepsy: Behavioral, anatomical, and causal mechanisms in the human brain

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe in the healthy brain. This leads to the hypothesis that statistical learning may be impaired in epilepsy patients, and that this impairment could contribute to their varied memory deficits. In turn, epilepsy patients provide a platform to advance basic understanding of statistical learning by helping to evaluate the necessity of medial temporal lobe circuitry through disease and causal perturbations. We implemented behavioral testing, volumetric analysis of the medial temporal lobe substructures, and direct electrical brain stimulation to examine statistical learning across a cohort of 61 epilepsy patients and 28 healthy controls. Behavioral performance in a statistical learning task was negatively associated with seizure frequency, irrespective of where seizures originated in the brain. The volume of hippocampal subfields CA1 and CA2/3 correlated with statistical learning performance, suggesting a more specific role of the hippocampus. Indeed, transient direct electrical stimulation of the hippocampus disrupted statistical learning. Furthermore, the relationship between statistical learning and seizure frequency was selective: behavioral performance in an episodic memory task was impacted by structural lesions in the medial temporal lobe and by antiseizure medications, but not by seizure frequency. Overall, these results suggest that statistical learning may be hippocampally dependent and that this task could serve as a clinically useful behavioral assay of seizure frequency distinct from existing neuropsychological tests. Simple and short statistical learning tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

Changes in perfusion, and structure of hippocampal subfields related to cognitive impairment after ECT: A pilot study using ultra high field MRI

BACKGROUND

Electroconvulsive therapy (ECT) in patients with major depression is associated with volume changes and markers of neuroplasticity in the hippocampus, in particular in the dentate gyrus. It is unclear if these changes are associated with cognitive side effects.

OBJECTIVES

We investigated whether changes in cognitive functioning after ECT were associated with hippocampal structural changes. It was hypothesized that 1) volume increase of hippocampal subfields and 2) changes in perfusion and diffusion of the hippocampus correlated with cognitive decline.

METHODS

Using ultra high field (7 T) MRI, intravoxel incoherent motion and volumetric data were acquired and neurocognitive functioning was assessed before and after ECT in 23 patients with major depression. Repeated measures correlation analysis was used to examine the relation between cognitive functioning and structural characteristics of the hippocampus.

RESULTS

Left hippocampal volume, left and right dentate gyrus and right CA1 volume increase correlated with decreases in verbal memory functioning. In addition, a decrease of mean diffusivity in the left hippocampus correlated with a decrease in letter fluency.

LIMITATIONS

Due to methodological restrictions direct study of neuroplasticity is not possible. MRI is used as an indirect measure.

CONCLUSION

As both volume increase in the hippocampus and MD decrease can be interpreted as indirect markers for neuroplasticity that co-occur with a decrease in cognitive functioning, our results may indicate that neuroplastic processes are affecting cognitive processes after ECT.

Development and application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE): Initial results from a multi-center study of adults with temporal lobe epilepsy

[Correction Notice: An Erratum for this article was reported online in Neuropsychology on Sep 15 2022 (see record 2023-01997-001). In the original article, there was an error in Figure 2. In the box at the top left of the figure, the fourth explanation incorrectly stated, "Generalized impairment = At least one test < -1.0 or -1.5SD in three or more domains." The correct wording is "Generalized impairment = At least two tests < -1.0 or -1.5SD in each of three or more domains." All versions of this article have been corrected.] Objective: To describe the development and application of a consensus-based, empirically driven approach to cognitive diagnostics in epilepsy research-The International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) and to assess the ability of the IC-CoDE to produce definable and stable cognitive phenotypes in a large, multi-center temporal lobe epilepsy (TLE) patient sample.

METHOD

Neuropsychological data were available for a diverse cohort of 2,485 patients with TLE across seven epilepsy centers. Patterns of impairment were determined based on commonly used tests within five cognitive domains (language, memory, executive functioning, attention/processing speed, and visuospatial ability) using two impairment thresholds (≤1.0 and ≤1.5 standard deviations below the normative mean). Cognitive phenotypes were derived across samples using the IC-CoDE and compared to distributions of phenotypes reported in existing studies.

RESULTS

Impairment rates were highest on tests of language, followed by memory, executive functioning, attention/processing speed, and visuospatial ability. Application of the IC-CoDE using varying operational definitions of impairment (≤ 1.0 and ≤ 1.5 SD) produced cognitive phenotypes with the following distribution: cognitively intact (30%-50%), single-domain (26%-29%), bi-domain (14%-19%), and generalized (10%-22%) impairment. Application of the ≤ 1.5 cutoff produced a distribution of phenotypes that was consistent across cohorts and approximated the distribution produced using data-driven approaches in prior studies.

CONCLUSIONS

The IC-CoDE is the first iteration of a classification system for harmonizing cognitive diagnostics in epilepsy research that can be applied across neuropsychological tests and TLE cohorts. This proof-of-principle study in TLE offers a promising path for enhancing research collaborations globally and accelerating scientific discoveries in epilepsy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Establishing the cross-cultural applicability of a harmonized approach to cognitive diagnostics in epilepsy: Initial results of the International Classification of Cognitive Disorders in Epilepsy in a Spanish-speaking sample

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.

Ocular motility as a measure of cerebral dysfunction in adults with focal epilepsy

OBJECTIVE

Using objective oculomotor measures, we aimed to: (1) compare oculomotor performance in patients with drug-resistant focal epilepsy to healthy controls, and (2) investigate the differential impact of epileptogenic focus laterality and location on oculomotor performance.

METHODS

We recruited 51 adults with drug-resistant focal epilepsy from the Comprehensive Epilepsy Programs of two tertiary hospitals and 31 healthy controls to perform prosaccade and antisaccade tasks. Oculomotor variables of interest were latency, visuospatial accuracy, and antisaccade error rate. Linear mixed models were performed to compare interactions between groups (epilepsy, control) and oculomotor tasks, and between epilepsy subgroups and oculomotor tasks for each oculomotor variable.

RESULTS

Compared to healthy controls, patients with drug-resistant focal epilepsy exhibited longer antisaccade latencies (mean difference = 42.8 ms, P = 0.001), poorer spatial accuracy for both prosaccade (mean difference = 0.4°, P = 0.002), and antisaccade tasks (mean difference = 2.1°, P < 0.001), and more antisaccade errors (mean difference = 12.6%, P < 0.001). In the epilepsy subgroup analysis, left-hemispheric epilepsy patients exhibited longer antisaccade latencies compared to controls (mean difference = 52.2 ms, P = 0.003), while right-hemispheric epilepsy was the most spatially inaccurate compared to controls (mean difference = 2.5°, P = 0.003). The temporal lobe epilepsy subgroup displayed longer antisaccade latencies compared to controls (mean difference = 47.6 ms, P = 0.005).

SIGNIFICANCE

Patients with drug-resistant focal epilepsy exhibit poor inhibitory control as evidenced by a high percentage of antisaccade errors, slower cognitive processing speed, and impaired visuospatial accuracy on oculomotor tasks. Patients with left-hemispheric epilepsy and temporal lobe epilepsy have markedly impaired processing speed. Overall, oculomotor tasks can be a useful tool to objectively quantify cerebral dysfunction in drug-resistant focal epilepsy.

Corpus callosum thickness: A predictive factor for the first drug efficiency of self-limited epilepsy with centrotemporal spikes (selects)?

OBJECTIVE

To investigate the existence of a possible linkage between the thickness of corpus callosum (CC) regions and the first antiepileptic drug response in patients with Selects.

MATERIALS AND METHODS

CC thickness of 68 patients with Selects and 42 healthy controls between 4 and 12 years of age were measured using brain magnetic resonance imaging (MRI). Clinical and EEG features of newly diagnosed Selects patients were recorded. Patients were divided into two groups: good-response (patients without seizures within 24 weeks) and poor-response (patients with ≥ 1 seizure within 24 weeks). Thickness of CC was compared between patients (good-response and poor-response groups).and healthy controls.

RESULTS

The thicknesses of genu and isthmus were significantly reduced in the Selects group than healthy controls. Isthmus and splenium were significantly thinner in poor responders than those in the good-response group (p = 0.005 and p < 0.001, respectively). The total number of seizures was negatively correlated with the thickness of the body, isthmus, and splenium (p < 0.001). There was no significant difference in CC thickness of the children with and without electrical status epilepticus in sleep (ESES). The thickness of the isthmus and splenium were significantly thinner in patients receiving ≥ 2 antiepileptic drugs (p = 0.002 and p = 0.001, respectively).

CONCLUSIONS

Our study highlights the notable differences in areas of CC in Selects patients. These changes may help uncover the underlying cause of seizure recurrence and antiepileptic drug (AED) response. Different thinner parts of CC may be a protective mechanism to prevent seizure spread to other brain regions. CC thickness can be used as a new radiologic biomarker for predicting first AED response and seizure recurrence in Selects patients.

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.

Cognitive phenotypes in frontal lobe epilepsy

OBJECTIVE

Neuropsychological profiles are heterogeneous both across and within epilepsy syndromes, but especially in frontal lobe epilepsy (FLE), which has complex semiology and epileptogenicity. This study aimed to characterize the cognitive heterogeneity within FLE by identifying cognitive phenotypes and determining their demographic and clinical characteristics.

METHOD

One hundred and six patients (age 16-66; 44% female) with FLE completed comprehensive neuropsychological testing, including measures within five cognitive domains: language, attention, executive function, processing speed, and verbal/visual learning. Patients were categorized into one of four phenotypes based on the number of impaired domains. Patterns of domain impairment and clinical and demographic characteristics were examined across phenotypes.

RESULTS

Twenty-five percent of patients met criteria for the Generalized Phenotype (impairment in at least four domains), 20% met criteria for the Tri-Domain Phenotype (impairment in three domains), 36% met criteria for the Domain-Specific Phenotype (impairment in one or two domains), and 19% met criteria for the Intact Phenotype (no impairment). Language was the most common domain-specific impairment, followed by attention, executive function, and processing speed. In contrast, learning was the least impacted cognitive domain. The Generalized Phenotype had fewer years of education compared to the Intact Phenotype, but otherwise, there was no differentiation between phenotypes in demographic and clinical variables. However, qualitative analysis suggested that the Generalized and Tri-Domain Phenotypes had a more widespread area of epileptogenicity, whereas the Intact Phenotype most frequently had seizures limited to the lateral frontal region.

SIGNIFICANCE

This study identified four cognitive phenotypes in FLE that were largely indistinguishable in clinical and demographic features, aside from education and extent of epileptogenic zone. These findings enhance our appreciation of the cognitive heterogeneity within FLE and provide additional support for the development and use of cognitive taxonomies in epilepsy.

Dynamic functional connectivity in modular organization of the hippocampal network marks memory phenotypes in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is a network disorder with a high incidence of memory impairment. Memory processing ability highly depends on the dynamic coordination between distinct modules within the hippocampal network. Here, we investigate the relationship between memory phenotypes and modular alterations of dynamic functional connectivity (FC) in the hippocampal network in TLE patients. Then, 31 healthy controls and 66 TLE patients with hippocampal sclerosis were recruited. The patients were classified into memory-intact (MI, 35 cases) group and memory-deficit (MD, 31 cases) group, each based on individual's Wechsler Memory Scale-Revised score. The sliding-windows approach and graph theory analysis were used to analyze the hippocampal network based on resting state functional magnetic resonance imaging. Temporal properties and modular metrics were calculated. Two discrete and switchable states were revealed: a high modularized state (State I) and a low modularized state (State II), which corresponded to either anterior or posterior hippocampal network dominated pattern. TLE was prone to drive less State I but more State II, and the tendency was more obvious in TLE-MD. Additionally, TLE-MD showed more widespread alterations of modular properties compared with TLE-MI across two states. Furthermore, the dynamic modularity features had unique superiority in discriminating TLE-MD from TLE-MI. These findings demonstrated that state transitions and modular function of dissociable hippocampal networks were altered in TLE and more importantly, they could reflect different memory phenotypes. The trend revealed potential values of dynamic FC in elucidating the mechanism underlying memory impairments in TLE.

Neuropsychiatric and Cognitive Comorbidities in Epilepsy

PURPOSE OF REVIEW

This article discusses psychiatric and cognitive comorbidities of epilepsy over the lifespan and illustrates opportunities to improve the quality of care of children and adults with epilepsy.

RECENT FINDINGS

One in 3 people with epilepsy have a lifetime history of psychiatric disorders, and they represent an important prognostic marker of epilepsy. Contributors are diverse and display a complex relationship. Cognitive comorbidities are also common among those living with epilepsy and are increasingly recognized as a reflection of changes to underlying brain networks. Among the cognitive comorbidities, intellectual disability and dementia are common and can complicate the diagnostic process when cognitive and/or behavioral features resemble seizures.

SUMMARY

Comorbidities require consideration from the first point of contact with a patient because they can determine the presentation of symptoms, responsiveness to treatment, and the patient's day-to-day functioning and quality of life. In epilepsy, psychiatric and cognitive comorbidities may prove a greater source of disability for the patient and family than the seizures themselves, and in the case of essential comorbidities, they are regarded as core to the disorder in terms of etiology, diagnosis, and treatment.

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.

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.

Decomposing MRI phenotypic heterogeneity in epilepsy: a step towards personalized classification

In drug-resistant temporal lobe epilepsy (TLE), precise predictions of drug response, surgical outcome, and cognitive dysfunction at an individual level remain challenging. A possible explanation may lie in the dominant "one-size-fits-all" group-level analytical approaches that does not allow parsing inter-individual variations along the disease spectrum. Conversely, analyzing inter-patient heterogeneity is increasingly recognized as a step towards person-centered care. Here, we utilized unsupervised machine learning to estimate latent relations (or disease factors) from 3 T multimodal MRI features (cortical thickness, hippocampal volume, FLAIR, T1/FLAIR, diffusion parameters) representing whole-brain patterns of structural pathology in 82 TLE patients. We assessed the specificity of our approach against age- and sex-matched healthy individuals and a cohort of frontal lobe epilepsy patients with histologically-verified focal cortical dysplasia. We identified four latent disease factors variably co-expressed within each patient and characterized by ipsilateral hippocampal microstructural alterations, loss of myelin and atrophy (Factor-1), bilateral paralimbic and hippocampal gliosis (Factor-2), bilateral neocortical atrophy (Factor-3), bilateral white matter microstructural alterations (Factor-4). Bootstrap analysis and parameter variations supported high stability and robustness of these factors. Moreover, they were not expressed in healthy controls and only negligibly in disease controls, supporting specificity. Supervised classifiers trained on latent disease factors could predict patient-specific drug-response in 76 ± 3% and postsurgical seizure outcome in 88 ± 2%, outperforming classifiers that did not operate on latent factor information. Latent factor models predicted inter-patient variability in cognitive dysfunction (verbal IQ: r = 0.40 ± 0.03; memory: r = 0.35 ± 0.03; sequential motor tapping: r = 0.36 ± 0.04), again outperforming baseline learners. Data-driven analysis of disease factors provides a novel appraisal of the continuum of interindividual variability, which is likely determined by multiple interacting pathological processes. Incorporating interindividual variability is likely to improve clinical prognostics.

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.

Quantitative analysis of cerebellar lobule morphology and clinical cognitive correlates in refractory temporal lobe epilepsy patients

PURPOSE

This study was conducted to explore the cerebellar substructure volumetric alterations in refractory unilateral temporal lobe epilepsy (TLE) patients and the relationship with clinical factors and cognitive scores.

METHODS

A total of 48 unilateral refractory TLE patients and 48 age- and gender-matched normal controls (NCs) were retrospectively studied. All subjects underwent high-resolution magnetic resonance imaging (MRI) and automatically segmented volumetric brain information was obtained using volBrain and Data Processing Assistant for Resting-State fMRI (DPARSF) separately. Clinical seizure features and cognitive scores were acquired by a structured review of medical records.

RESULTS

The total volumes (TVs) of bilateral crus I, crus II, and IX were significantly smaller in the refractory unilateral TLE epilepsy patients. The gray matter volumes (GMVs) of cerebellar lobules showed lateralized reduction in ipsilateral III, IX, and contralateral crus II. Contralateral crus II GMV showed significant negative correlation with the duration of epilepsy (r = -0.31, p = 0.035) and positive association with the cognitive scores including long-term memory (LTM) (r = 0.39, p = 0.017), short-term memory (STM) (r = 0.51, p = 0.001) verbal comprehension index (VCI) (r = 0.37, p = 0.024), and perceptual organization index (POI) (r = 0.36, p = 0.030). The voxel-based morphometry (VBM) analysis proved similar results. The contralateral crus I GMV was significantly smaller in the generalized onset group (t = 2.536, p = 0.015).

CONCLUSIONS

The lobules of the cerebellar in refractory TLE patients manifest different volumetric change characteristics. Crus II contralateral GMV is negatively correlated with the duration of epilepsy and positively associated with the cognitive scores.

Connectome biomarkers of drug-resistant epilepsy

Drug-resistant epilepsy (DRE) considerably affects patient health, cognition, and well-being, and disproportionally contributes to the overall burden of epilepsy. The most common DRE syndromes are temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal epilepsy related to cortical malformations. Both syndromes have been traditionally considered as "focal," and most patients benefit from brain surgery for long-term seizure control. However, increasing evidence indicates that many DRE patients also present with widespread structural and functional network disruptions. These anomalies have been suggested to relate to cognitive impairment and prognosis, highlighting their importance for patient management. The advent of multimodal neuroimaging and formal methods to quantify complex systems has offered unprecedented ability to profile structural and functional brain networks in DRE patients. Here, we performed a systematic review on existing DRE network biomarker candidates and their contribution to three key application areas: (1) modeling of cognitive impairments, (2) localization of the surgical target, and (3) prediction of clinical and cognitive outcomes after surgery. Although network biomarkers hold promise for a range of clinical applications, translation of neuroimaging biomarkers to the patient's bedside has been challenged by a lack of clinical and prospective studies. We therefore close by highlighting conceptual and methodological strategies to improve the evaluation and accessibility of network biomarkers, and ultimately guide clinically actionable decisions.

Cognitive disorders in epilepsy II: Clinical targets, indications and selection of test instruments

This is the second of two narrative reviews on cognitive disorders in epilepsy (companion manuscript: Cognitive disorders in epilepsy I: Clinical experience, real-world evidence and recommendations). Its focus is on the clinical targets, indications, and the selection of neuropsychological test instruments. Cognitive assessment has become an essential tool for the diagnosis and outcome control in the clinical management of epilepsy. The diagnostics of basic and higher brain functions can provide valuable information on lateralized and localized brain dysfunctions associated with epilepsy, its underlying pathologies and treatment. In addition to the detection or verification of deficits, neuropsychology reveals the patient's cognitive strengths and, thus, information about the patient reserve capacities for functional restitution and compensation. Neuropsychology is an integral part of diagnostic evaluations mainly in the context of epilepsy surgery to avoid new or additional damage to preexisting neurocognitive impairments. In addition and increasingly, neuropsychology is being used as a tool for monitoring of the disease and its underlying pathologies, and it is suited for the quality and outcome control of pharmacological or other non-invasive medical intervention. This narrative review summarizes the present state of neuropsychological assessments in epilepsy, reveals diagnostic gaps, and shows the great need for education, homogenization, translation and standardization of instruments.

The association of cognitive phenotypes with postoperative outcomes after epilepsy surgery in patients with temporal lobe epilepsy

INTRODUCTION

The concept of cognitive phenotypes has been developed to categorize the heterogeneity of neuropsychological profiles in patients with temporal lobe epilepsy (TLE). This study examines the utility of cognitive phenotypes derived from clinical criteria in the prediction of postoperative outcomes.

METHODS

Scores from 9 standardized neuropsychological tests were used to sample preoperative performance in 4 core domains (intellectual, memory, language, & executive function) in 445 patients with TLE (206 right: 236 left). Patients were grouped into 3 clinical phenotypes using clinical criteria: 1. intact cognition, 2. isolated memory and/or language impairment, and 3. widespread impairment. Patients who did not meet the criteria for these phenotypes were characterized as having a mixed profile phenotype.

RESULTS

Approximately half of the sample had intact cognitive function, with one-quarter demonstrating isolated impairments in language and memory function. The remainder demonstrated widespread impairment or a mixed pattern of cognitive impairments. The clinically derived cognitive phenotypes were associated with demographic and clinical characteristics. Patients with widespread cognitive impairments had an earlier onset of seizures than those with other cognitive phenotypes. They also reported higher levels of depression. Higher levels of anxiety were reported in those with isolated memory/language impairments. Phenotypes were not associated with postoperative seizure outcome or postoperative declines in verbal memory or language function, but an intact phenotype was associated with a greater risk of decline in visual learning than right-sided surgery.

CONCLUSIONS

Distinct cognitive phenotypes in TLE can be identified using clinical criteria and may reflect neurodevelopmental influences and mood in addition to progression of the disease. Phenotype may be a more powerful predictor of postoperative decline in visual memory than laterality of surgery.

Subcortical nuclei volumes are associated with cognition in children post-convulsive status epilepticus: Results at nine years follow-up

PURPOSE

The purpose of the present study was to investigate the relationship between subcortical nuclei volume and cognition in children with post-convulsive status epilepticus (CSE).

METHODS

Structural T1-weighted magnetic resonance imaging (MRI) scans (Siemens Avanto, 1.5 T) and neuropsychological assessments (full-scale intelligence quotient (FSIQ) and Global Memory Scores (GMS)) were collected from subjects at a mean 8.5 years post-CSE (prolonged febrile seizures (PFS), n = 30; symptomatic/known, n = 28; and other, n = 12) and from age- and sex-matched healthy controls (HC). Subjects with CSE were stratified into those with lower cognitive ability (LCA) (CSE+, n = 22) and those without (CSE-, n = 48). Quantitative volumetric analysis using Functional MRI of the Brain Software Library (FSL) (Analysis Group, FMRIB, Oxford) provided segmented MRI brain volumes. Univariate analysis of covariance (ANCOVA) was performed to compare subcortical nuclei volumes across subgroups. Multivariable linear regression was performed for each subcortical structure and for total subcortical volume (SCV) to identify significant predictors of LCA (FSIQ <85) while adjusting for etiology, age, socioeconomic status, sex, CSE duration, and intracranial volume (ICV); Bonferroni correction was applied for the analysis of individual subcortical nuclei.

RESULTS

Seventy subjects (11.8 ± 3.4 standard deviation (SD) years; 34 males) and 72 controls (12.1 ± 3.0SD years; 29 males) underwent analysis. Significantly smaller volumes of the left thalamus, left caudate, right caudate, and SCV were found in subjects with CSE+ compared with HC, after adjustment for intracranial, gray matter (GM), or cortical/cerebellar volume. When compared with subjects with CSE-, subjects with CSE+ also had smaller volumes of the left thalamus, left pallidum, right pallidum, and SCV. Individual subcortical nuclei were not associated, but SCV was associated with FSIQ (p = 0.005) and GMS (p = 0.014). Intracranial volume and etiology were similarly predictive.

CONCLUSIONS

Nine years post-CSE, SCV is significantly lower in children who have LCA compared with those that do not. However, in this cohort, we are unable to determine whether the relationship is independent of ICV or etiology. Future, larger scale studies may help tease this out.

Graph Theory Analysis of Functional Connectivity Combined with Machine Learning Approaches Demonstrates Widespread Network Differences and Predicts Clinical Variables in Temporal Lobe Epilepsy

Understanding how global brain networks are affected in epilepsy may elucidate the pathogenesis of seizures and its accompanying neurobehavioral comorbidities. We investigated functional changes within neural networks in temporal lobe epilepsy (TLE) using graph theory analysis of resting-state connectivity. Twenty-seven TLE presurgical patients (age 41.0 ± 12.3 years) and 85 age, gender, and handedness equivalent healthy controls (HCs; age 39.7 ± 16.9 years) were enrolled. Eyes-closed resting-state functional magnetic resonance image scans were analyzed to compare network properties and functional connectivity (FC) changes. TLE subjects showed significantly higher global efficiency, lower clustering coefficient ratio, and lower shortest path lengths ratio than HCs, as an indication of a more synchronized, yet less segregated network. A trend of functional reorganization with a shift of network hubs to the contralateral hemisphere was noted in TLE subjects. Support vector machine (SVM) with linear kernel was trained to separate between neural networks in TLE and HC subjects based on graph measurements. SVM analysis allowed separation between TLE and HC networks with 80.66% accuracy using eight features of graph measurements. Support vector regression (SVR) was used to predict neurocognitive performance from graph metrics. An SVR linear predictor showed discriminative prediction accuracy for four key neurocognitive variables in TLE (absolute R value range: 0.61-0.75). Despite TLE, our results showed both local and global network topology differences that reflect widespread alterations in FC in TLE. Network differences are discriminative between TLE and HCs using data-driven analysis and predicted severity of neurocognitive sequelae in our cohort.

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.

Cognition and epilepsy: Cognitive screening test

Cognitive deficits often occur in people with epilepsy (PWE). However, in Brazil, PWE might not undergo neurocognitive evaluation due to the low number of validated tests available and lack of multidisciplinary teams in general epilepsy outpatient clinics.

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.

Macroscale and microcircuit dissociation of focal and generalized human epilepsies

Thalamo-cortical pathology plays key roles in both generalized and focal epilepsies, but there is little work directly comparing these syndromes at the level of whole-brain mechanisms. Using multimodal imaging, connectomics, and computational simulations, we examined thalamo-cortical and cortico-cortical signatures and underlying microcircuits in 96 genetic generalized (GE) and 107 temporal lobe epilepsy (TLE) patients, along with 65 healthy controls. Structural and functional network profiling highlighted extensive atrophy, microstructural disruptions and decreased thalamo-cortical connectivity in TLE, while GE showed only subtle structural anomalies paralleled by enhanced thalamo-cortical connectivity. Connectome-informed biophysical simulations indicated modest increases in subcortical drive contributing to cortical dynamics in GE, while TLE presented with reduced subcortical drive and imbalanced excitation-inhibition within limbic and somatomotor microcircuits. Multiple sensitivity analyses supported robustness. Our multiscale analyses differentiate human focal and generalized epilepsy at the systems-level, showing paradoxically more severe microcircuit and macroscale imbalances in the former.

Metabolic correlates of cognitive impairment in mesial temporal lobe epilepsy

PURPOSE

The purpose of the study was to determine the correlations between brain metabolism and cognitive impairment in patients with drug-resistant mesial temporal lobe epilepsy (MTLE).

METHODS

[¹⁸F]-FluoroDeoxyGlucose positron emission tomography ([¹⁸F]-FDG-PET) and neuropsychological assessment were performed in 97 patients with MTLE (53 females, 15-56 years old, mean: 31.6 years, standard deviation (SD) = 10.4) with unilateral hippocampal sclerosis (HS, 49 left). We compared brain metabolism and gray matter volume (GMV) between patients with cognitive impairment (intelligence quotient (IQ) and memory index <80) and patients with normal cognition, using statistical parametric mapping (SPM), in the whole population then in right and left HS (RHS, LHS) separately.

RESULTS

Intelligence quotient (40-121, mean: 83.7 ± 16.9) and memory index (45-133, mean: 80.7 ± 19.3) were impaired in 43% and 51% of the patients, respectively, similarly in RHS and LHS. We did not find any correlations between IQ and clinical factors related to epilepsy; however, there was a significant correlation between low memory index and early age of onset in LHS (p = 0.021), and widespread epileptogenic zone in the whole population (p = 0.033). Impaired IQ correlated with extratemporal hypometabolism, involving frontoparietal networks implicated in the default mode network (DMN), predominantly in the midline cortices. Metabolic asymmetry regarding HS lateralization included the precuneus (pC) in LHS and the anterior cingulate cortex (ACC) in RHS, both areas corresponding to key nodes of the DMN. Memory index correlated with the same frontoparietal networks as for IQ, with an additional involvement of the temporal lobes, which was ipsilateral in RHS and contralateral in LHS. A diffuse decrease of GMV including the ipsilateral hippocampus correlated with cognitive impairment; however, the structural alterations did not match with the hypometabolic areas.

CONCLUSIONS

Cognitive impairment in MTLE correlates with extratemporal hypometabolism, involving the mesial frontoparietal networks implicated in the DMN and suggesting a disconnection with the affected hippocampus. Asymmetric alterations of connectivity may sustain the predominant ACC and pC metabolic decrease in patients with cognitive impairment.

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.

Cortical thickness in childhood left focal epilepsy: Thinning beyond the seizure focus

OBJECTIVE

Structural brain differences are found in adults and children with epilepsy, yet pediatric samples have been heterogeneous regarding seizure type, magnetic resonance imaging (MRI) findings, and hemisphere of seizure focus. This study examines whether cortical thickness and surface area differ between children with left-hemisphere focal epilepsy (LHE) and age-matched typically developing (TD) peers. We examined whether age differentially moderated cortical thickness between groups and if cortical thickness was associated with duration of epilepsy, seizure frequency, or neuropsychological functioning.

METHODS

Thirty-five children with LHE and 35 TD children completed neuropsychological testing and 3T MR imaging. Neuropsychological measures included general intelligence and executive functioning. All MRIs were normal. Surface-based morphometric processing and analyses were conducted using FreeSurfer 6.0. Regression analyses compared age by cortical thickness differences between groups. Correlational analyses examined associations between cortical thickness in these areas with neuropsychological functioning or epilepsy characteristics.

RESULTS

Left-hemisphere focal epilepsy displayed decreased cortical thickness bilaterally compared to TD controls across 6 brain regions but no differences in surface area. Moderation analyses revealed quadratic relationships between age and cortical thickness for left frontoparietal-cingulate and right superior frontal regions. Higher performance intelligence quotient (IQ) (PIQ) and verbal IQ (VIQ) and fewer parent reported executive function problems were associated with greater cortical thickness in TD children.

SIGNIFICANCE

Children with LHE displayed thinner cortex extending beyond the hemisphere of seizure focus. The nonlinear pattern of cortical thickness across age occurring in TD children is not evident in the same manner in children with LHE. These differences in cortical thickness patterns were greatest in children 8-12 years old. Greater cortical thickness was associated with higher IQ and fewer executive control problems in daily activities in TD children. Thus, differences in cortical thickness in the absence of differences in surface area, suggest cortical thickness may be a sensitive proxy of subtle neuroanatomical changes that are related to neuropsychological functioning.

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.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

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.

Impact of surgical intervention on seizure and psychiatric symptoms in patients with temporal lobe epilepsy

Temporal lobe epilepsy (TLE), a common form of localisation-related epilepsy, is characterised by focal seizures and accompanied by variety of neuropsychiatric symptoms. This form of epilepsy proves difficult to manage as many anticonvulsant and psychotropic medications have little to no effect on controlling the seizure and neuropsychiatric symptoms respectively. The authors, report a patient with TLE and recurrent seizures that were refractory to multiple classes of antiepileptic therapy. Additionally, she exhibited psychosis, depression and irritability that required antipsychotic medication. After several years of poorly controlled seizure disorder, the patient underwent anterior temporal lobectomy and amygdalohippocampectomy, which proved beneficial for seizure control, as well as her neuropsychiatric symptoms. While it is common to treat refractory temporal lobe epilepsy with surgical interventions, there is little literature about it also treating the neuropsychiatric symptoms. This case underscores both the neurological and psychiatric benefits following surgical intervention for patients with TLE.

Temporal lobe epilepsy is associated with distinct cognitive phenotypes

Neuropsychological assessment is critical for understanding the impact of seizures on cognition and informing treatment decisions. While focus is often placed on examining groups based on seizure type/epilepsy syndrome, an alternate approach emphasizes empirically derived groups based solely on cognitive performance. This approach has been used to identify cognitive phenotypes in temporal lobe epilepsy (TLE). The current study sought to replicate prior work by Hermann and colleagues (2007) and identify cognitive phenotypes in a separate, larger cohort of 185 patients with TLE (92 left TLE, 93 right TLE). Cluster analysis revealed 3- and 4-cluster solutions, with clusters differentiated primarily by overall level of performance in the 3-cluster solution (Low, Middle, and High performance) and by more varying cognitive phenotypes in the 4-cluster solution (Globally Low, Low Executive Functioning/Speed, Low Language/Memory, and Globally High). Differences in cognitive performance as well as demographic and clinical seizure variables are presented. A greater proportion of the patients with left TLE were captured by Cluster 3 (Low Language/Memory) than by the other 3 clusters, though this cluster captured only approximately one-third of the overall group with left TLE. Consistent with prior findings, executive functioning and speed emerged as additional domains of interest in this sample of patients with TLE. The current results extend prior work examining cognitive phenotypes in TLE and highlight the importance of identifying the comprehensive range of potential cognitive profiles in TLE.

Music training is neuroprotective for verbal cognition in focal epilepsy

Focal epilepsy is a unilateral brain network disorder, providing an ideal neuropathological model with which to study the effects of focal neural disruption on a range of cognitive processes. While language and memory functions have been extensively investigated in focal epilepsy, music cognition has received less attention, particularly in patients with music training or expertise. This represents a critical gap in the literature. A better understanding of the effects of epilepsy on music cognition may provide greater insight into the mechanisms behind disease- and training-related neuroplasticity, which may have implications for clinical practice. In this cross-sectional study, we comprehensively profiled music and non-music cognition in 107 participants; musicians with focal epilepsy (n = 35), non-musicians with focal epilepsy (n = 39), and healthy control musicians and non-musicians (n = 33). Parametric group comparisons revealed a specific impairment in verbal cognition in non-musicians with epilepsy but not musicians with epilepsy, compared to healthy musicians and non-musicians (P = 0.029). This suggests a possible neuroprotective effect of music training against the cognitive sequelae of focal epilepsy, and implicates potential training-related cognitive transfer that may be underpinned by enhancement of auditory processes primarily supported by temporo-frontal networks. Furthermore, our results showed that musicians with an earlier age of onset of music training performed better on a composite score of melodic learning and memory compared to non-musicians (P = 0.037), while late-onset musicians did not differ from non-musicians. For most composite scores of music cognition, although no significant group differences were observed, a similar trend was apparent. We discuss these key findings in the context of a proposed model of three interacting dimensions (disease status, music expertise, and cognitive domain), and their implications for clinical practice, music education, and music neuroscience research.

Language function in childhood idiopathic epilepsy syndromes

PURPOSE

To examine the impact of diverse syndromes of focal and generalized epilepsy on language function in children with new and recent onset epilepsy. Of special interest was the degree of shared language abnormality across epilepsy syndromes and the unique effects associated with specific epilepsy syndromes.

METHODS

Participants were 136 youth with new or recent-onset (diagnosis within past 12 months) epilepsy and 107 healthy first-degree cousin controls. The participants with epilepsy included 20 with Temporal Lobe Epilepsy (TLE; M age = 12.99  years, SD = 3.11), 41 with Benign Epilepsy with Centrotemporal Spikes (BECTS; M age = 10.32, SD = 1.67), 42 with Juvenile Myoclonic Epilepsy (JME; M age = 14.85, SD = 2.75) and 33 with absence epilepsy (M age = 10.55, SD = 2.76). All children were administered a comprehensive test battery which included multiple measures of language and language-dependent abilities (i.e., verbal intelligence, vocabulary, verbal reasoning, object naming, reception word recognition, word reading, spelling, lexical and semantic fluency, verbal list learning and delayed verbal memory). Test scores were adjusted for age and gender and analyzed via MANCOVA.

RESULTS

Language abnormalities were found in all epilepsy patient groups. The most broadly affected children were those with TLE and absence epilepsy, whose performance differed significantly from controls on 8 of 11 and 9 of 11 tests respectively. Although children with JME and BECTS were less affected, significant differences from controls were found on 4 of 11 tests each. While each group had a unique profile of language deficits, commonalities were apparent across both idiopathic generalized and localization-related diagnostic categories.

DISCUSSION

The localization related and generalized idiopathic childhood epilepsies examined here were associated with impact on diverse language abilities early in the course of the disorder.

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.

Structural covariance networks relate to the severity of epilepsy with focal-onset seizures

PURPOSE

The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions.

METHODS

Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance.

RESULTS

Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively.

CONCLUSIONS

These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.

Cognition and dementia in older patients with epilepsy

With advances in healthcare and an ageing population, the number of older adults with epilepsy is set to rise substantially across the world. In developed countries the highest incidence of epilepsy is already in people over 65 and, as life expectancy increases, individuals who developed epilepsy at a young age are also living longer. Recent findings show that older persons with epilepsy are more likely to suffer from cognitive dysfunction and that there might be an important bidirectional relationship between epilepsy and dementia. Thus some people with epilepsy may be at a higher risk of developing dementia, while individuals with some forms of dementia, particularly Alzheimer's disease and vascular dementia, are at significantly higher risk of developing epilepsy. Consistent with this emerging view, epidemiological findings reveal that people with epilepsy and individuals with Alzheimer's disease share common risk factors. Recent studies in Alzheimer's disease and late-onset epilepsy also suggest common pathological links mediated by underlying vascular changes and/or tau pathology. Meanwhile electrophysiological and neuroimaging investigations in epilepsy, Alzheimer's disease, and vascular dementia have focused interest on network level dysfunction, which might be important in mediating cognitive dysfunction across all three of these conditions. In this review we consider whether seizures promote dementia, whether dementia causes seizures, or if common underlying pathophysiological mechanisms cause both. We examine the evidence that cognitive impairment is associated with epilepsy in older people (aged over 65) and the prognosis for patients with epilepsy developing dementia, with a specific emphasis on common mechanisms that might underlie the cognitive deficits observed in epilepsy and Alzheimer's disease. Our analyses suggest that there is considerable intersection between epilepsy, Alzheimer's disease and cerebrovascular disease raising the possibility that better understanding of shared mechanisms in these conditions might help to ameliorate not just seizures, but also epileptogenesis and cognitive dysfunction.

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

OBJECTIVE

The purpose of this study was to evaluate the relation between cognitive performance and white matter (WM) integrity in patients with temporal lobe epilepsy (TLE) with mesial temporal sclerosis (MTS).

METHODS

We included 26 patients with TLE (10 right, 16 left onset) as well as 24 healthy controls matched for age, gender, and years of education. In addition to quantitative hippocampal volume and transverse relaxation (T2) evaluation, whole-brain WM was analyzed using fractional anisotropy (FA) maps, derived from the diffusion tensor model. Average FA values were obtained from 38 regions of interest (ROI) of the main WM fascicles using an atlas-based approach. All subjects underwent extensive coFignitive assessments, Wechsler Adult Intelligence Scale (WAIS-IV) and Wechsler Memory Scale (WMS-IV). Fractional anisotropy was correlated with neuropsychological scores, and group effects were evaluated. Finally, patients were clustered based on their cognitive performance to evaluate if clinical and structural variables relate to specific cognitive profiles.

RESULTS

Patients had differential alterations in the integrity of the WM dependent on seizure laterality and presence of hippocampal sclerosis. Patients with TLE showed, on average, lower scores in most of the cognitive assessments. Correlations between cognition and WM followed specific trajectories per group with TLE, particularly in Left-TLE, in which we found a marked association between cognitive abilities and WM abnormalities. Cluster analysis of cognitive performance revealed three cognitive profiles, which were associated with the degree and spread of WM abnormalities.

SIGNIFICANCE

White matter diffusion characteristics differ between patients, particularly in relation to seizure laterality and hippocampal damage. Moreover, WM abnormalities are associated with cognitive performance. The extent of WM alterations leads to disrupted cerebral intercommunication and therefore negatively affects cognition.