Closed- and Open-loop (Slow Oscillations) sleep stimulation (auditory) or recording in full-PSG using OpenBCI for sleep.

see more infos for settings here

A poster with pictures and infographics, lists'n'stuff

• Its a fun project, but with hard science behind in hardware, software and concept, usable for research.
• Different modes: e.g. Stimulation, Recording only (just PSG, no stimulation), record on SD card without real-time monitoring/stimulation
• Setup for OpenBCI sleep recording (125 or 250 Hz sampling rate, 8 or 16 channels, incl. EEG, EOG, EMG and ECG) here
• Build your own sleep lab for under a $1000 and do research-grade recording and reactivation protocols.
• Its free, its open and its closed-loop too, at least for slow waves/slow oscillations.
• Works and tested with all Firmwares for OpenBCI device: v1 v2 v3
• Use your own Electrode Montage (for 8 and 16 channel) stored in a *.tsv to change channel setup, display in the GUI and algorithm
• Targeted & Untargeted Auditory Stimuli Presentation using Configurable Stimuli Playlists (easy to create and mix).
• Reproduce all the published research in this area, e.g. Targeted Memory Reactivation (TMR, e.g Rudoy et al. 2009) during sleep, or Slow wave enhancement (Ngo et al. 2013)
• Stimulate during a specific time point of a slow oscillation, and trigger another stimuli after that.
• Stimulation is activated manually, but disengaged automatically on arousal.
• See live ERPs from stimulation
• Latencies considered in stimulation (below 10 ms signal latency, auditory delay down to 24 ms with normal hardware under 3 ms with specialized sound card, default is 93 ms)
• 100% logging what you did, all markers, Lights-off on, checklist for eye movements
• Lost samples are imputed and logged.
• works with parallel microSD card recording (250 Hz)
• Warning on SD card problems on device
• Handles all kinds of auditory stimuli, peeps, noises, voices and baaaams! (as long as in wav or mp3 format, or what sox can handle)
• Detect accurately your hearing threshold on any PC with Linux (alsa) down to the deciBel, and stimulate accurately as well with online-adjustments of volume.
• Full unfiltered BDF+ (24bit) & CSV export or pre-filtered (High-pass, can choose cut-off frequency, Butterworth, order 1 sample) EDF+(16bit) (live recording, and including all markers)
• Obfuscate your Sham/Stim condition for blinding your experiment.
• Realtime-view, scalable channels, with spindle highlighting.
• Flexible re-referencing
• Simulation of previous Recording for testing and trying things (even without an OpenBCI device)
• Default settings for stimulation in healthy school children (5-12 yrs.) and adults (5-35 yrs.)
• ... lots of other stuff

Tutorial in the making, otherwise ask the author.

software/installation/source_python

1. Example Data for testing the simulation (FREDDY is 8 channel, JINGYI is 16 channel data, settings described in here
2. Example Stimuli (preprocessed) for testing the open and closed loop stimulation of voice and tones. Example protocols for those stimuli see in the subfolder stimulations
3. Binaries, Ubuntu 18.04 LTS x64 compiled using pyinstaller
4. Proof of concept learning Chinese in sleep files for ANKI if you like to learn more chinese.

1. OpenBCI Cyton board (optionally a daisy module) v1 v2 v3
2. EEG electrodes
3. Battery/Power pack
4. Other 'stuff' to record polysomnography
5. Motivation to built a little (you can do it!) ...see tutorial here

• Dual core 1.2 Ghz
• 1.5 GB RAM
• 5 GByte free disk space
• USB 2.0 port
• Audio jack (wireless audio for stimulation not recommended, due to delay) (e.g. a Rasperry Pi3, Pine64, Rock64, etc. are fine too)

• Linux
  • Ubuntu 18.04 LTS (tested), recompiled also tested under Ubunutu 14.04 LTS
  • Debian 9 if source code is recompiled (tested)
• (optional, but recommended) low-latency kernel preferred (will automatically installed with the deploy scripts)
• READY ON THE USB-STICK: setup free USB stick image for bootup in custom Debian live version on any PC soon to follow.

• Lenovo Thinkpad X220, Intel Core i7-2640M, 16 GByte RAM, fast SSD, Ubuntu 18.04 LTS
• Lenovo Thinkpad X220, Intel Core i5-2520M, 16 GByte RAM, fast SSD, Ubuntu 14.04 LTS
• Dell Laptitude, Ubuntu 18.04 LTS

• Lenovo Thinkpad X220, Intel Core i7-2640M, 16 GByte RAM, fast SSD, Ubuntu 18.04 LTS
• Lenovo Thinkpad X220, Intel Core i5-2520M, 16 GByte RAM, fast SSD, Ubuntu 14.04 LTS
• Dell Laptitude, Ubuntu 18.04 LTS
• Debian stretch (9, stable)