Optimizing Magnetoencephalographic Imaging Estimation of Language Lateralization for Simpler Language Tasks

Magnetoencephalographic imaging (MEGI) offers a non-invasive alternative for defining preoperative language lateralization in neurosurgery patients. MEGI indeed can be used for accurate estimation of language lateralization with a complex language task - auditory verb generation. However, since language function may vary considerably in patients with focal lesions, it is important to optimize MEGI for estimation of language function with other simpler language tasks. The goal of this study was to optimize MEGI laterality analyses for two such simpler language tasks that can have compliance from those with impaired language function: a non-word repetition (NWR) task and a picture naming (PN) task. Language lateralization results for these two tasks were compared to the verb-generation (VG) task. MEGI reconstruction parameters (regions and time windows) for NWR and PN were first defined in a presurgical training cohort by benchmarking these against laterality indices for VG. Optimized time windows and regions of interest (ROIs) for NWR and PN were determined by examining oscillations in the beta band (12-30 Hz) a marker of neural activity known to be concordant with the VG laterality index (LI). For NWR, additional ROIs include areas MTG/ITG and for both NWR and PN, the postcentral gyrus was included in analyses. Optimal time windows for NWR were defined as 650-850 ms (stimulus-locked) and -350 to -150 ms (response-locked) and for PN -450 to -250 ms (response-locked). To verify the optimal parameters defined in our training cohort for NWR and PN, we examined an independent validation cohort (n = 30 for NWR, n = 28 for PN) and found high concordance between VG laterality and PN laterality (82%) and between VG laterality and NWR laterality (87%). Finally, in a test cohort (n = 8) that underwent both the intracarotid amobarbital procedure (IAP) test and MEG for VG, NWR, and PN, we identified excellent concordance (100%) with IAP for VG + NWR + PN composite LI, high concordance for PN alone (87.5%), and moderate concordance for NWR alone (66.7%). These findings provide task options for non-invasive language mapping with MEGI that can be calibrated for language abilities of individual patients. Results also demonstrate that more accurate estimates can be obtained by combining laterality estimates obtained from multiple tasks. MEGI.