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

Abstract

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.

Figure 1. Distribution of language and memory performance across cognitive phenotypes

Mean z scores on measures of language and memory across cognitive phenotypes. Error bars represent SDs. Impairment was defined as 1.5 SD below the mean of healthy controls (represented as horizontal black line). ANT = Auditory Naming Test; BNT = Boston Naming Test; CVLT LDFR = California Verbal Learning Test Long Delayed Free Recall; LM = logical memory; VP = verbal paired associates.

Figure 2. Deep white matter tracts of interest

(A) Coronal and (B) sagittal rendering of the arcuate fasciculus, uncinate fasciculus, fornix, parahippocampal cingulum, and inferior longitudinal fasciculus derived from AtlasTrack projected onto a T1-weighted image for a single individual. The corpus callosum is portrayed in light gray in order to provide additional spatial information.

Figure 3. Surface-based superficial white matter (SWM) abnormalities across cognitive phenotypes

(A) Surface-based mapping of SWM fractional anisotropy (FA) and mean diffusivity (MD) differences across cognitive phenotypes relative to healthy controls (HC) after correcting for multiple comparisons, p_FDR < 0.05. The color bar shows patients with either lower values than controls in blue/cyan or greater value than HC in red/yellow. (B) Post hoc comparison between the language and memory impaired group and the no impairment group in SWM MD. Increases in MD in the language and memory group are shown in red/yellow.

Figure 4. Global network measures

(A) Plots show differences in global efficiency, transitivity, and modularity between healthy controls (HC) and the whole temporal lobe epilepsy (TLE) group across network densities. Shaded areas represent the upper and lower bounds of each measure in HC. (B) Differences in global efficiency, transitivity, and modularity between HC and each cognitive phenotype. Colored circles represent significant difference between HC and patients.

Figure 5. Local efficiency differences within perisylvian regions

(A) Local efficiency differences between healthy controls (HC) and each cognitive phenotype in pars triangularis (pTRI)/pars opercularis (pOPC), superior temporal gyrus (STG), and supramarginal gyrus (SMG). Significant differences from HC are depicted in gray/blue within each region of interest. (B) Differences in local efficiency within the left and right STG between HC and each cognitive phenotype across different network densities. Shaded areas represent the upper and lower bounds in local efficiency for HC.