Bilingualism and Structural Network Organization in Temporal Lobe Epilepsy: Resilience in Neurologic Disease

Abstract

Background and objectives: There is growing evidence that bilingualism can induce neuroplasticity and modulate neural efficiency, resulting in greater resistance to neurologic disease. However, whether bilingualism is beneficial to neural health in the presence of epilepsy is unknown. We tested whether bilingual individuals with temporal lobe epilepsy (TLE) have improved whole-brain structural white matter network organization.

Methods: Healthy controls and individuals with TLE recruited from 2 specialized epilepsy centers completed diffusion-weighted MRI and neuropsychological testing as part of an observational cohort study. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory. Global analyses compared network integration (path length) and specialization (transitivity) in TLE vs controls and in a 2 (left vs right TLE) × 2 (bilingual vs monolingual) model. Local analyses compared mean local efficiency of predefined frontal-executive and language (i.e., perisylvian) subnetworks. Exploratory correlations examined associations between network organization and neuropsychological performance.

Results: A total of 29 bilingual and 88 monolingual individuals with TLE matched on several demographic and clinical variables and 81 age-matched healthy controls were included. Globally, a significant interaction between language status and side of seizure onset revealed higher network organization in bilinguals compared with monolinguals but only in left TLE (LTLE). Locally, bilinguals with LTLE showed higher efficiency in frontal-executive but not in perisylvian networks compared with LTLE monolinguals. Improved whole-brain network organization was associated with better executive function performance in bilingual but not monolingual LTLE.

Discussion: Higher white matter network organization in bilingual individuals with LTLE suggests a neuromodulatory effect of bilingualism on whole-brain connectivity in epilepsy, providing evidence for neural reserve. This may reflect attenuation of or compensation for epilepsy-related dysfunction of the left hemisphere, potentially driven by increased efficiency of frontal-executive networks that mediate dual-language control. This highlights a potential role of bilingualism as a protective factor in epilepsy, motivating further research across neurologic disorders to define mechanisms and develop interventions.

Figure 1. Illustration of White Matter Connectome Generation and Graph Theory Analysis

(A) Raw diffusion-weighted MRI data were preprocessed and registered to a T1 space. (B) Probabilistic whole-brain tractography was used to construct white matter fiber tracts connecting different brain regions (shown here is tractography from 1 participant for visualization). (C) Data were analyzed in a parcellated anatomic space with regions of interest (ROIs) selected from the Desikan-Killiany atlas, which were registered to each participant's diffusion tensor imaging space. (D) White matter connectivity matrices were generated by assessing pairwise connections between each pair of ROIs and input into a 2-dimensional matrix (shown here is an individual connectome) where each row and column represent an ROI, and the corresponding color is the strength of the structural connectivity between that pair of ROIs. (E) Network render of a structural connectome, which is equivalent to brain graphs, with ROIs representing nodes and white matter connections representing edges. For visualization, a matrix averaged across participants is imposed on a standard brain template using the BrainNet Viewer. (F) Connectivity matrices were analyzed with graph theory analysis to extract 2 global metrics of interest that reflect brain network organization—path length (a measure of network integration) and transitivity (a normalized clustering coefficient; a measure of network specialization).

Figure 2. Network Integration (A) and Specialization (B) in Bilinguals and Monolinguals With L-TLE vs R-TLE

The effect of bilingualism on network organization was dependent on side of seizure focus such that bilingual LTLE showed increased network organization relative to monolingual LTLE. Plotted are AUC of path length and transitivity separately by side of seizure focus (L- vs R-TLE) and language status (bilingual vs monolingual). Boxplot denotes the median (bold bar), first and third quartiles (box limits), and ±1.5 times the interquartile range (whiskers). Bilingual and monolingual TLEs are coded as circles and triangles, respectively. AUC = area under the curve; LTLE = left TLE; RTLE = right TLE; TLE = temporal lobe epilepsy.

Figure 3. Local Efficiency of Predefined (A) Frontal-Executive and (B) Perisylvian Subnetworks in B-LTLE and M-LTLE

A significant interaction between subnetwork and language status such that B-LTLE had higher frontal-executive, but not perisylvian, local efficiency relative to M-LTLE. Panel A visualizes nodes that comprised the frontal-executive subnetwork in coronal and axial views. Panel B visualizes nodes that comprised the perisylvian (i.e., language) subnetwork in sagittal and axial views. Plotted are z scores (relative to healthy controls) of the mean subnetwork efficiency. B-LTLE and M-LTLEs are coded as circles and triangles, respectively. AUC = area under the curve; B-LTLE = bilingual left temporal lobe epilepsy; M-LTLE = monolingual left temporal lobe epilepsy.

Figure 4. Correlations Between Global Network Integration (Path Length) and Specialization (Transitivity) and (A) Executive Function and (B) Language Performance in LTLE

Spearman bivariate correlations between executive function measured by Trails B (panel A) and language function measured by category fluency (panel B) and (left panels) and (right panels) for 13 bilinguals and 30 monolinguals with LTLE. Significant correlations are denoted with *, and marginally significant correlations are denoted with ^. Bilingual and monolingual LTLEs are coded as circles and triangles, respectively. AUC = area under the curve; LTLE = left temporal lobe epilepsy.