“…These concern, for example: (i) methodology for the assessment of brain networks, effects of the pathological process, and cerebral plasticity, based on a qualitative and quantitative longitudinal and multimodal approach; (ii) the accuracy of neurophysiological techniques, especially for the intraoperative cortical and subcortical monitoring, especially of higher-level functions, such as language. To this regard, the application of emerging methods, such as corticocortical evoked potentials, in patients that cannot undergo awake procedures, will extend the feasibility of intraoperative monitoring of language circuits also to the pediatric population (Yamao et al, 1977;Matsumoto et al, 2004;Giampiccolo et al, 2021); (iii) the application of machine learning (ML) technology, based on the identification of specific structural WM biomarkers for the computation of reliable probabilistic atlases based on different convergent factors, such as the presurgical lesion characteristics, the relationships between the lesion type and the local and global network, the functional interactions and outflows, and the possible clinical deficits; (iv) the development of model-based approaches, based on computation of brain network models by integrating data from reference atlases with anatomofunctional connectivity data coming from patient-specific imaging, and electrophysiological recordings (e.g., EEG patterns identified by stereo-EEG recordings). As already described in both the adult and pediatric epilepsy literature, the combined use of brain network model representation (the so-called "virtual epilepsy brain models") with ML De Benedictis et al 10.3389/fnana.2023.1242757 Frontiers in Neuroanatomy 16 frontiersin.org and artificial intelligence methods would allow to approximate the extent and the organization of the epileptogenic zone (EZ), intended as the site of beginning and of the primary organization of epileptic seizures.…”