Neuroanatomical correlates of personality traits in temporal lobe epilepsy: Findings from the Epilepsy Connectome Project.

Behavioral and personality disorders in temporal lobe epilepsy (TLE) have been a topic of interest and controversy for decades, with less attention paid to alterations in normal personality structure and traits. In this investigation, core personality traits (the Big 5) and their neurobiological correlates in TLE were explored using the Neuroticism Extraversion Openness-Five Factor Inventory (NEO-FFI) and structural magnetic resonance imaging (MRI) through the Epilepsy Connectome Project (ECP). NEO-FFI scores from 67 individuals with TLE (34.6 ±â€¯9.5 years; 67% women) were compared to 31 healthy controls (32.8 ±â€¯8.9 years; 41% women) to assess differences in the Big 5 traits (agreeableness, openness, conscientiousness, neuroticism, and extraversion). Individuals with TLE showed significantly higher neuroticism, with no significant differences on the other traits. Neural correlates of neuroticism were then determined in participants with TLE including cortical and subcortical volumes. Distributed reductions in cortical gray matter volumes were associated with increased neuroticism. Subcortically, hippocampal and amygdala volumes were negatively associated with neuroticism. These results offer insight into alterations in the Big 5 personality traits in TLE and their brain-related correlates.

Using Low-Frequency Oscillations to Detect Temporal Lobe Epilepsy with Machine Learning.

The National Institutes of Health-sponsored Epilepsy Connectome Project aims to characterize connectivity changes in temporal lobe epilepsy (TLE) patients. The magnetic resonance imaging protocol follows that used in the Human Connectome Project, and includes 20 min of resting-state functional magnetic resonance imaging acquired at 3T using 8-band multiband imaging. Glasser parcellation atlas was combined with the FreeSurfer subcortical regions to generate resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuations (ALFFs), and fractional ALFF measures. Seven different frequency ranges such as Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) were selected to compute these measures. The goal was to train machine learning classification models to discriminate TLE patients from healthy controls, and to determine which combination of the resting state measure and frequency range produced the best classification model. The samples included age- and gender-matched groups of 60 TLE patients and 59 healthy controls. Three traditional machine learning models were trained: support vector machine, linear discriminant analysis, and naive Bayes classifier. The highest classification accuracy was obtained using RSFC measures in the Slow-4 + 5 band (0.01-0.073 Hz) as features. Leave-one-out cross-validation accuracies were ∼83%, with receiver operating characteristic area-under-the-curve reaching close to 90%. Increased connectivity from right area posterior 9-46v in TLE patients contributed to the high accuracies. With increased sample sizes in the near future, better machine learning models will be trained not only to aid the diagnosis of TLE, but also as a tool to understand this brain disorder.

Effective Connectivity Within the Default Mode Network in Left Temporal Lobe Epilepsy: Findings from the Epilepsy Connectome Project.

The Epilepsy Connectome Project examines the differences in connectomes between temporal lobe epilepsy (TLE) patients and healthy controls. Using these data, the effective connectivity of the default mode network (DMN) in patients with left TLE compared with healthy controls was investigated using spectral dynamic causal modeling (spDCM) of resting-state functional magnetic resonance imaging data. Group comparisons were made using two parametric empirical Bayes (PEB) models. The first level of each PEB model consisted of each participant's spDCM. Two different second-level models were constructed: the first comparing effective connectivity of the groups directly and the second using the Rey Auditory Verbal Learning Test (RAVLT) delayed free recall index as a covariate at the second level to assess effective connectivity controlling for the poor memory performance of left TLE patients. After an automated search over the nested parameter space and thresholding parameters at 95% posterior probability, both models revealed numerous connections in the DMN, which lead to inhibition of the left hippocampal formation. Left hippocampal formation inhibition may be an inherent result of the left temporal epileptogenic focus as memory differences were controlled for in one model and the same connections remained. An excitatory connection from the posterior cingulate cortex to the medial prefrontal cortex was found to be concomitant with left hippocampal formation inhibition in TLE patients when including RAVLT delayed free recall at the second level.

Predictors of language lateralization in temporal lobe epilepsy.

Among patients with epilepsy, atypical (rightward) language lateralization has been associated with left-handedness, a left seizure focus, an early age at seizure onset, and familial sinistrality, although these associations are not consistently observed. No study has examined all of these factors in relation to language lateralization in the same epilepsy sample, let alone in a sample comprised only of patients with temporal lobe epilepsy. Moreover, little consideration has been given in previous studies to how language lateralization might be influenced by the interplay between different factors, or how much unique variance in language lateralization is explained by each factor. The primary aim of this study was to examine the combined influences of handedness, side of seizure focus, age at seizure onset, and familial sinistrality on language lateralization in temporal lobe epilepsy patients. A secondary aim was to determine which factors uniquely contribute to the prediction of language lateralization. 162 patients with intractable temporal lobe epilepsy underwent functional MRI language mapping, from which language lateralization indexes were derived. Degree of handedness was measured via the Edinburgh Handedness Inventory. Main and 2-way interaction effects on language lateralization indexes were examined via linear regressions and Fisher exact tests. Significant effects were next examined in multiple regressions to identify unique predictors of language lateralization indexes. When examined in isolation in regressions, only left-handedness and a left seizure focus predicted atypical (rightward) language lateralization. These results, however, were qualified by interaction effects demonstrating that stronger left hand preference was associated with greater atypical language lateralization only among patients with a left seizure focus, an early or intermediate age at seizure onset, or no familial sinistrality. In follow-up multiple regressions, the interaction terms accounted for a significant amount of variance in language lateralization indexes above and beyond main effects. Additionally, side of seizure focus and its interaction with handedness uniquely predicted language lateralization indexes. Results indicate that degree of left-handedness is a marker of greater atypical (rightward) language lateralization in temporal lobe epilepsy but only in the context of seizure characteristics that have the potential to drive joint reorganization of language and hand preference (i.e., left seizure focus, or early or intermediate age at seizure onset) or in the absence of a genetic predisposition for left-handedness (i.e., no familial sinistrality). This study advances existing knowledge by illustrating how different factors combine to jointly affect language lateralization, and by identifying side of seizure focus and its interaction with handedness as unique predictors of language lateralization in temporal lobe epilepsy.

Language lateralization by fMRI and Wada testing in 229 patients with epilepsy: rates and predictors of discordance.

PURPOSE: To more definitively characterize Wada/functional magnetic resonance imaging (fMRI) language dominance discordance rates with the largest sample of patients with epilepsy to date, and to examine demographic, clinical, and methodologic predictors of discordance. METHODS: Two hundred twenty-nine patients with epilepsy underwent both a standardized Wada test and a semantic decision fMRI language protocol in a prospective research study. Language laterality indices were computed for each test using automated and double-blind methods, and Wada/fMRI discordance rates were calculated using objective criteria for discordance. Regression analyses were used to explore a range of variables that might predict discordance, including subject variables, Wada quality indices, and fMRI quality indices. KEY FINDINGS: Discordant results were observed in 14% of patients. Discordance was highest among those categorized by either test as having bilateral language. In a multivariate model, the only factor that predicted discordance was the degree of atypical language dominance on fMRI. SIGNIFICANCE: fMRI language lateralization is generally concordant with Wada testing. The degree of rightward shift of language dominance on fMRI testing is strongly correlated with Wada/fMRI discordance, suggesting that fMRI may be more sensitive than Wada to right hemisphere language processing, although the clinical significance of this increased sensitivity is unknown. The relative accuracy of fMRI versus Wada testing for predicting postsurgical language outcome in discordant cases remains a topic for future research.

Reflection impulsivity in adolescent cannabis users: a comparison with alcohol-using and non-substance-using adolescents.

RATIONALE: Reflection impulsivity-a failure to gather and evaluate information before making a decision-is a critical component of risk-taking and substance use behaviours, which are highly prevalent during adolescence. OBJECTIVES AND METHODS: The Information Sampling Test was used to assess reflection impulsivity in 175 adolescents (mean age 18.3, range 16.5-20; 55% female)-48 cannabis users (2.3 years use, 10.8 days/month), 65 alcohol users, and 62 non-substance-using controls-recruited from a longitudinal cohort and from the general community and matched for education and IQ. Cannabis and alcohol users were matched on levels of alcohol consumption. RESULTS: Cannabis users sampled to the lowest degree of certainty before making a decision on the task. Group differences remained significant after controlling for relevant substance use and clinical confounds (e.g., anxiety, depressive symptoms, alcohol, and ecstasy use). Poor performance on multiple IST indices was associated with an earlier age of onset of regular cannabis use and greater duration of exposure to cannabis, after controlling for recent use. Alcohol users did not differ from controls on any IST measure. CONCLUSIONS: Exposure to cannabis during adolescence is associated with increased risky and impulsive decision making, with users adopting strategies with higher levels of uncertainty and inefficient utilisation of information. The young cannabis users did show sensitivity to losses, suggesting that greater impulsivity early in their drug using career is more evident when there is a lack of negative consequences. This provides a window of opportunity for intervention before the onset of cannabis dependence.

Verbal learning and memory in adolescent cannabis users, alcohol users and non-users.

RATIONALE: Long-term heavy cannabis use can result in memory impairment. Adolescent users may be especially vulnerable to the adverse neurocognitive effects of cannabis. OBJECTIVES AND METHODS: In a cross-sectional and prospective neuropsychological study of 181 adolescents aged 16-20 (mean 18.3 years), we compared performance indices from one of the most widely used measures of learning and memory--the Rey Auditory Verbal Learning Test--between cannabis users (n=52; mean 2.4 years of use, 14 days/month, median abstinence 20.3 h), alcohol users (n=67) and non-user controls (n=62) matched for age, education and premorbid intellectual ability (assessed prospectively), and alcohol consumption for cannabis and alcohol users. RESULTS: Cannabis users performed significantly worse than alcohol users and non-users on all performance indices. They recalled significantly fewer words overall (p<0.001), demonstrating impaired learning (p<0.001), retention (p<0.001) and retrieval (p<0.05) (Cohen's d 0.43-0.84). The degree of impairment was associated with the duration, quantity, frequency and age of onset of cannabis use, but was unrelated to alcohol exposure or other drug use. No gender effects were detected and the findings remained after controlling for premorbid intellectual ability. An earlier age of onset of regular cannabis use was associated with worse memory performance after controlling for extent of exposure to cannabis. CONCLUSIONS: Despite relatively brief exposure, adolescent cannabis users relative to their age-matched counterparts demonstrated similar memory deficits to those reported in adult long-term heavy users. The results indicate that cannabis adversely affects the developing brain and reinforce concerns regarding the impact of early exposure.