Language lateralization in temporal lobe epilepsy using functional MRI and probabilistic tractography
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Updated: Jul 6, 2026
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Sebastian Rodrigo1, Catherine Oppenheim, Francine Chassoux
1Department of Neuroradiology, Sainte-Anne Hospital Center, Paris-Descartes University, Paris, France. s.rodrigo@ch-sainte-anne.fr
Purpose:
Language functional magnetic resonance imaging (fMRI) is used to noninvasively assess hemispheric language specialization as part of the presurgical work-up in temporal lobe epilepsy (TLE). White matter asymmetries on diffusion tensor imaging (DTI) may be related to language specialization as shown in controls and TLE. To refine our understanding of the effect of epilepsy on the structure-function relationships, we focused on the arcuate fasciculus (ArcF) and the inferior occipitofrontal fasciculus (IOF) and tested the relationship between DTI- and fMRI-based lateralization indices in TLE.
Methods:
fMRI with three language tasks and DTI were obtained in 20 patients (12 right and 8 left TLE). The ArcF, a major language-related tract, and the IOF were segmented bilaterally using probabilistic tractography to obtain fractional anisotropy (FA) lateralization indices. These were correlated with fMRI-based lateralization indices computed in the inferior frontal gyrus (Pearson's correlation coefficient).
Results:
fMRI indices were left-lateralized in 16 patients and bilateral or right-lateralized in four. In the ArcF, FA was higher on the left than on the right side, reaching significance in right but not in left TLE. We found a positive correlation between ArcF anisotropy and fMRI-based lateralization indices in right TLE (p < 0.009), but not in left TLE patients. No correlation was observed for the IOF.
Conclusions:
Right TLE patients with more left-lateralized functional activations also showed a leftward-lateralized arcuate fasciculus. The decoupling between the functional and structural indices of the ArcF underlines the complexity of the language network in left TLE patients.
