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Objective: Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug‐resistant epilepsy patients. Epileptic spikes, high‐frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies. Methods: Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug‐resistant epilepsy with seizure‐free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross‐correlation, and phase consistency) were computed for neighboring electrode pairs. Results: Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy. Significance: The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery. [ABSTRACT FROM AUTHOR]

The phenomenon of déjà vu (DV) has intrigued scientists for decades, yet its neurophysiological underpinnings remain elusive. Brain regions have been identified in which morphometry differs between healthy individuals according to the frequency of their DV experiences. This study built upon these findings by assessing if and how neural activity in these and other brain regions also differ with respect to DV experience. Resting‐state fMRI was performed on 68 healthy volunteers, 44 of whom reported DV experiences (DV group) and 24 who did not (NDV group). Using multivariate analyses, we then assessed the (fractional) amplitude of low‐frequency fluctuations (fALFF/ALFF), a metric that is believed to index brain tissue excitability, for five discrete frequency bands within sets of brain regions implicated in DV and those comprising the default mode network (DMN). Analyses revealed significantly lower values of fALFF/ALFF for specific frequency bands in the DV relative to the NDV group, particularly within mesiotemporal structures, bilateral putamina, right caudatum, bilateral superior frontal cortices, left lateral parietal cortex, dorsal and ventral medial prefrontal cortex, and the posterior cingulate cortex. The pattern of differences in fALFF/ALFF measures between the brains of individuals who have experienced DV and those who have not provides new neurophysiological insights into this phenomenon, including the potential role of the DMN. We suggest that the erroneous feeling of familiarity arises from a temporary disruption of cortico‐subcortical circuitry together with the upregulation of cortical excitability. [ABSTRACT FROM AUTHOR]