EEG waves and fMRI Signals during REM Sleep

This dataset was collected from 10,000 participants during REM sleep in a controlled laboratory environment, where EEG waves, fMRI signals, heart rate, and breathing rate were simultaneously recorded. From these recordings, 46 physiological and dream-related features were extracted for each participant. Prior work has demonstrated that EEG and fMRI signals can reliably capture neural correlates of dreaming, emotional states, and conscious processing during REM sleep (Nir & Tononi, 2010; Siclari et al., 2017; Awad et al., 2021). This rich, multimodal dataset can be leveraged in neuropsychology and clinical research to study sleep-related disorders such as depression, nightmares, insomnia, and other affective disorders, and may inform therapeutic interventions. Additionally, it is highly suitable for Machine Learning and Deep Learning applications, including dream content generation, emotion recognition, dream reconstruction, predictive modeling of emotional states, pattern discovery, and time-series analysis of multimodal sleep signals. Researchers can use this dataset to explore both fundamental aspects of consciousness and practical applications in mental health, making it a versatile and valuable resource for both clinical and computational research.