Dreamento is an open-source Python package for dream engineering using sleep electroencephalography wearables. It provides real-time functions including data visualization, power-spectrum analysis, automatic sleep scoring, sensory stimulation (visual, auditory, tactile), text-to-speech communication, and event annotation. Offline functions support post-processing and integration with other modalities like electromyography. Developed primarily for lucid dreaming studies, Dreamento can also be applied to other sleep research areas such as closed-loop auditory stimulation and targeted memory reactivation for memory consolidation.
Lucid dreaming, a rare sleep state where the dreamer becomes aware of dreaming, offers a testable model for psychosis. Recent EEG and fMRI data show that brain areas activated during lucid dreaming overlap strikingly with regions impaired in psychotic patients who lack insight into their condition. This parallel suggests that insight into dreaming and insight into psychosis share similar neural correlates, opening new avenues for therapeutic approaches and testing antipsychotic medication.
During lucid REM sleep, performing a dreamed hand movement activates the sensorimotor cortex in the same way as an actual movement. By combining fMRI and NIRS with polysomnography, the study used eye signals as temporal markers to link neural activity to specific dream content. This provides first evidence that the contents of REM-associated dreams can be visualized by neuroimaging, overcoming the previous impossibility of experimentally controlling spontaneous dream activity.
Lucid dreaming, a state in which dreamers are consciously aware and can control their dreams, is rare and unstable, making it difficult to study in the lab. New developments in wearable brain-sensing devices, large-scale research partnerships, citizen science projects, and artificial intelligence are now making it easier to decode and investigate this phenomenon.