Towards a Passive BCI to Induce Lucid Dream
TT OWARDS A P ASSIVE
BCI TO I NDUCE L UCID D REAM
JJC-ICON ’19
Morgane Hamon
UlloLa Rochelle, France [email protected]
Emma Chabani
Institut du Cerveau et de la Moelle épinièreParis, France [email protected]
Philippe Giraudeau
InriaBordeaux, France [email protected]
May 21, 2019 A BSTRACT
Lucid dreaming (LD) is a phenomenon during which the person is aware that he/she dreaming and isable to control the dream content. Studies have shown that only 20% of people can experience luciddreams on a regular basis. However, LD frequency can be increased through induction techniques.External stimulation technique relies on the ability to integrate external information into the dreamcontent. The aim is to remind the sleeper that she/he is dreaming. If this type of protocol is not fullyefficient, it demonstrates how sensorial stimuli can be easily incorporated into people’s dreams. Theobjective of our project was to replicate this induction technique using material less expensive andmore portable. This material could simplify experimental procedures. Participants could bring thematerial home, then have a more ecological setting. First, we used the OpenBCI Cyton, a low-costEEG signal acquisition board in order to record and manually live-score sleep. Then, we designed amask containing two LEDs, connected to a microcontroller to flash visual stimulation during sleep.We asked two volunteers to sleep for 2 hours in a dedicated room. One of the participants declaredhaving a dream during which the blue lights diffused by the mask were embedded into the dreamenvironment. The other participant woke up during the visual stimulation. These results are congru-ent with previous studies. This work marked the first step of a larger project. Our ongoing researchincludes the use of an online sleep stage scoring tool and the possibility to automatically send stimuliaccording to the sleep stage. We will also investigate other types of stimulus induction in the futuresuch as vibro-tactile stimulation that showed great potentials. K eywords Lucid Dream · Induction techniques · Sleep · Visual stimulation · EEG
During a normal night’s sleep, people enter on a cyclical basis different vigilance states: Wakefulness, N1, N2, N3and REM sleep [Silber et al., 2007]. A sleep cycle lasts around 90 minutes, and occurs 4 to 6 times a night. TheN1, N2 and N3 sleep stages are usually grouped as N-REM (Non-REM) as an opposition to the REM sleep. It waslong believed that dreams exclusively occur during REM sleep [Dement and Kleitman, 1957] but this hypothesis hasbeen refuted [Foulkes, 1962]. Awakenings during N-REM sleep showed dreams recall as well [Nielsen et al., 2001].Lucid dreaming (LD) is a phenomenon during which the person is aware that he/she dreaming and is able tocontrol the dream content [LaBerge, 1985]. LD can be used to enhance the dream content, train physical skills[Erlacher and Ehrlenspiel, 2017] or avoid nightmares. That’s why authors have studied the ability to induce LD or in-crease the LD frequency [Gackenbach and LaBerge, 1988]. Thus, this project aims to reproduce induction techniquesto help people experience LD. As EEG amplifiers became less expensive and more portable, we aim at proposing asolution that could be deployed at home. a r X i v : . [ q - b i o . N C ] A p r JC-ICON ’19Figure 1:
Left:
EEG cap with electrodes connected to an OpenBCI Cyton,
Right:
The mask with LEDs and themicro-controller (Arduino UNO)
This pilot study has been conducted during a hackathon, a 48-hours event that occurred in December 2017 . Weused a electroencephalogram (EEG) headset to acquire sleep data like sleep stages. First, we built a EEG cap outof swim cap on which electrodes are sewed (see Fig.2, Left ). They are connected to the OpenBCI Cyton Board,that is sending data to a computer via Bluetooth. The OpenBCI software allows to visualize brainwaves obtainedfrom the electrodes. Sleep stages, arousal, eye movement were deducted from the neural oscillations and were scoredaccording to international criteria [Rechstchaffen and Kales, 1968]. Finally, a mask has been created with two LEDplaced above each eye to send flash light (see Fig.2,
Right ). Lights were controlled by an Arduino Uno connected tothe same computer which runs the openBCI software. We sent visual stimulation when the participant enters in REMsleep. REM stage for Rapid Eye Movements has an EEG activity mainly branded by theta waves (5-7 Hz). There is acomplete muscle atonia.
Two volunteers (1 male 24y, 1 female, 26y), were not naive about lucid dreaming and had already experienced it. Theywere also considered as recallers, who are subjects with high Dream Recall Frequency (DRF): remembering dreamsmore than two nights a week [Cory et al., 1975]. The volunteers were equipped with our EEG headset, our mask andearplugs to help them fall asleep. Subsequently visual stimulations were presented to determine the intensity of theLEDs. Then participants were told they could sleep for about 2 hours. As the system wasn’t live-scoring sleep, sleepstages were monitored by our team and stimuli were sent when needed (REM sleep). The method is pictured in Fig.1.
We observed that the blue flashing light was integrated in dream content for both participants. One participant reportedto be behind a fish tank window and saw blue flashes wondering if it was natural or not but without understand it wasa signal. However it did not trigger lucid dreaming. The second participant woke up right after the first stimulation.These results are congruent with previous studies [LaBerge, 1985], [Paul et al., 2014]. https://mindlabdx.github.io/hack1cerveau/ This pilot study allowed us to better know how and when sending stimuli, an important step towards a passive BCI[Zander and Kothe, 2011]. Our ongoing research will explore different modalities of visual stimulation such as thecolor, the intensity and the frequency in order to determine the best combination to induce LD. Vibro-tactile stimu-lation showed great potentials as well [Stumbrys et al., 2012]. We will also compare different devices to detect sleepstages (an EEG headband with less electrodes and an actimeter). This will be the first step to build a device able toautomatically discriminate sleep stages.
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