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Updated: Jan 27, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Cognitive phenotypes in temporal lobe epilepsy are associated with distinct patterns of white matter network
Anny Reyes1, Erik Kaestner1, Naeim Bahrami1
1From the San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology (A.R.); Center for Multimodal Imaging and Genetics (A.R., E.K., N.B., A.B., C.R.M.) and Department of Psychiatry (C.R.M.), University of California, San Diego; Department of Neurology (M.H., B.M.P.), University of California, San Francisco; UCSF Comprehensive Epilepsy Center (M.H., B.M.P.), San Francisco; Matthews Neuropsychology Section (B.H.), University of Wisconsin-Madison; and UCSD Comprehensive Epilepsy Center (C.R.M.), San Diego, CA.
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.
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