Uncovering Individual Language Vulnerability in Epilepsy Through Functional Connectivity Laterality.
BACKGROUND Language processing is organized in brain networks, generally lateralized to the left hemisphere. In clinical routine, task-based functional MRI (fMRI) is the gold standard for non-invasive evaluation of language lateralization. However, standard fMRI does not account for the individual heterogeneity of language networks. fMRI-based functional connectivity analysis (FCA) has addressed this shortcoming by identifying correlates of dysfunctional language networks in epilepsy patients. In order to individualize FCA, translation of group-based network analysis to individual epilepsy patients is necessary. Here, we introduce the functional connectivity laterality index (LIFC) as a potential clinical parameter. METHODS This retrospective study included adults with unilateral temporal lobe epilepsy (TLE) who underwent task-based fMRI and a control group. To account for individual variations, fMRI was performed at a 3T scanner and processed entirely in native space. Laterality indices were computed from both activation maps and seed-based functional connectivity across frontal, temporal, and combined language regions. Group comparisons and associations with neuropsychological language performance were analysed. RESULTS Forty patients with unilateral TLE and 25 healthy controls were included. Groups were comparable in terms of sex, handedness, imaging findings, and epilepsy duration, although the controls were younger. Classical LI showed predominantly left-lateralization, while LIFC showed mostly bilateral language lateralization. Neuropsychological performance did not differ between TLE-left and TLE-right patients. While a difference in semantic fluency was initially observed, it did not survive correction for multiple comparisons. However, analyses based on functional network organization revealed a critical pattern: Patients with language networks lateralized to the seizure side-as quantified by LIFC-showed significantly poorer semantic fluency and lower composite language scores. This potential clinically relevant result was exclusive to FCA and was not captured by activation data alone. CONCLUSION Our findings suggest an individual vulnerability of language networks to seizure burden, although this uncorrected, exploratory finding requires replication in larger, independent samples. Incorporating functional connectivity measures into presurgical clinical fMRI analysis may enhance our ability to predict and protect language function in patients with TLE by prioritizing further therapies or surgical interventions for those at higher risk of language decline.