PEM-43 ITC Dataset

The purpose of the PEM-43 ITC dataset is to examine the brain responses linked to meditation in prenatal patients by collecting ITC images of electroencephalogram (EEG) recordings. 43 subjects were given three different eyes-closed circumstances to record their EEG signals: Resting State (RS), Listening to a Mantra (M), and After Listening to a Mantra (AM). Two trials per condition, each lasting roughly two minutes, were recorded. A 32-channel EEG system sampled at 128 Hz was used to collect the data. In order to facilitate automated label extraction during preprocessing, the raw EEG signals were saved as 32\u00d7N matrices (where N = 15,470 time points). The file names were systematically tagged to encode subject ID, condition (RS, M, AM), and trial number.Inter-Trial Coherence (ITC) characteristics were calculated in three frequency bands: theta (4\u20138 Hz), alpha (8\u201313 Hz), and beta (13\u201330 Hz) in order to investigate neuronal synchronization and cross-trial phase locking. Three sessions were chosen for each subject, with one trial chosen for each condition. This yielded a total of 129 sessions (43 subjects \u00d7 3 conditions), and with ITC computed across three frequency bands, the dataset comprises 387 ITC feature maps. A useful tool for creating EEG-based mental state categorization models and analyzing cognitive states in prenatal care settings, each map depicts frequency-specific phase-locking activity linked to different mental states.