• Yordanka Nikolova Yordanova, Jérôme Cochereau, Hugues Duffau, and Guillaume Herbet.
• Department of Neurosurgery, 'Percy' Military Hospital, 101 avenue Henri Barbusse, 92140, Clamart, France; National Institute for Health and Medical Research (INSERM), U1051, Team "Plasticity of the Central Nervous System, Human Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier, France. Electronic address: yn.yordanova@gmail.com.
• Neuroimage. 2019 Feb 1; 186: 628-636.

ObjectiveTo infer the face-based mentalizing network from resting-state functional MRI (rsfMRI) using a seed-based correlation analysis with regions of interest identified during intraoperative cortical electrostimulation.MethodsWe retrospectively included 23 patients in whom cortical electrostimulation induced transient face-based mentalizing impairment during 'awake' craniotomy for resection of a right-sided diffuse low-grade glioma. Positive stimulation sites were recorded and transferred to the patients' preoperative normalized MRI, and then used as seeds for subsequent seed-to-voxel functional connectivity analyses. The analyses, conducted with an uncorrected voxel-level p-value of 0.001 and a false-discovery-rate cluster-level p-value of 0.05, allowed identification of the cortical structures, functionally coupled with the mentalizing-related sites.ResultsTwo clusters of responsive stimulations were identified intraoperatively - one in the right dorsolateral prefrontal cortex (dlPFC, n = 13) and the other in the right inferior frontal gyrus (IFG, n = 10). A whole group level analysis revealed that stimulation sites correlated mainly with voxels located in the pars triangularis of the IFG, the dorsolateral and dorsomedial prefrontal cortices, the temporo-parietal junction, the posterior superior temporal sulcus, and the posterior inferior temporal/fusiform gyrus. Other analyses, taking into consideration the location of the responsive sites (IFG versus dlPFC cluster), highlighted only minor differences between both groups.ConclusionsThe present study successfully demonstrated the involvement of a large-scale neural network in the face-based mentalizing that strongly matches networks, classically identified using task-based fMRI paradigms. We thus validated the combination of rsfMRI and stimulation mapping as a powerful approach to identify functional networks in brain-damaged patients.Copyright © 2018. Published by Elsevier Inc.

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