Intracranial human brain recordings from multiple implanted depth electrodes using stereo-EEG (sEEG) technology for seizure localization provide unique local field potential signals (LFP) sampled with standard macro- and special micro-electrode contacts. Over one hundred macro- and micro-contact LFP signals localized in particular brain regions were recorded from each sEEG monitoring case as patients engaged in an automated battery of verbal memory and non-verbal gaze movement tasks. Subject eye and vocal responses in both visual and auditory task versions were automatically detected in Polish, Czech, and Slovak languages with accurate timing of the correct and incorrect verbal responses using our web-based transcription tool. The behavioral events, LFP and pupillometric signals were synchronized and stored in a standard BIDS data structure with corresponding metadata. Each dataset contains recordings from at least one battery task performed over at least one day. The same set of 180 common nouns in the three languages was used across different battery tasks and recording days to enable the analysis of selective responses to specific word stimuli.

• MeSH
• Electroencephalography MeSH
• Language MeSH
• Cognition * MeSH
• Humans MeSH
• Brain * physiology   MeSH
• Eye Movements MeSH
• Eye-Tracking Technology MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Dataset MeSH

Epilepsy is a very common disease affecting at least 1% of the population, comprising a number of over 50 million people. As many patients suffer from the drug-resistant version, the number of potential treatment methods is very small. However, since not only the treatment of epilepsy, but also its proper diagnosis or observation of brain signals from recordings are important research areas, in this paper, we address this very problem by developing a reliable technique for removing spikes and sharp transients from the baseline of the brain signal using a morphological filter. This allows much more precise identification of the so-called epileptic zone, which can then be resected, which is one of the methods of epilepsy treatment. We used eight patients with 5 KHz data set and depended upon the Staba 2002 algorithm as a reference to detect the ripples. We found that the average sensitivity and false detection rate of our technique are significant, and they are ∼94% and ∼14%, respectively.

• Keywords
• brain signals, dynamic threshold, epilepsy, morphological filter, ripples, spikes,
• MeSH
• Algorithms MeSH
• Electroencephalography * methods   MeSH
• Epilepsy * diagnosis   MeSH
• Humans MeSH
• Brain Mapping MeSH
• Brain MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.

• MeSH
• Electrodes MeSH
• Electrocorticography * MeSH
• Epilepsy physiopathology   MeSH
• Humans MeSH
• Brain physiology   MeSH
• Fixation, Ocular MeSH
• Memory physiology   MeSH
• Pupil MeSH
• Eye-Tracking Technology MeSH
• Seizures physiopathology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Dataset MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH