Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Induction of self awareness in dreams through frontal low current stimulation of gamma activity

Nature Neuroscience volume 17, pages 810–812 (2014)Cite this article

Subjects

Abstract

Recent findings link fronto-temporal gamma electroencephalographic (EEG) activity to conscious awareness in dreams, but a causal relationship has not yet been established. We found that current stimulation in the lower gamma band during REM sleep influences ongoing brain activity and induces self-reflective awareness in dreams. Other stimulation frequencies were not effective, suggesting that higher order consciousness is indeed related to synchronous oscillations around 25 and 40 Hz.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: EOG, EMG and EEG data from a single subject before, during and after 40-Hz stimulation.
Figure 2: Grand average FFT power ratios of activity during (phase II) versus activity before stimulation (phase I) for the different stimulation conditions: sham (N = 30), 2 Hz (N = 31), 6 Hz (N = 19), 12 Hz (N = 18), 25 Hz (N = 26), 40 Hz (N = 44), 70 Hz (N = 21) and 100 Hz (N = 18).
Figure 3: Selected contrasts of mean scores (s.e.) for the LuCiD factors insight, dissociation and control (N = 207).

References

  1. Edelman, G.M. Proc. Natl. Acad. Sci. USA 100, 5520–5524 (2003).

    Article  CAS  Google Scholar 

  2. Hobson, A. & Voss, U. Conscious. Cogn. 20, 993–997 (2011).

    Article  Google Scholar 

  3. Voss, U., Holzmann, R., Tuin, I. & Hobson, A. Sleep 32, 1191–1200 (2009).

    Article  Google Scholar 

  4. Hobson, J.A. Nat. Rev. Neurosci. 10, 803–813 (2009).

    Article  CAS  Google Scholar 

  5. Dresler, M. et al. Sleep 35, 1017–1020 (2012).

    Article  Google Scholar 

  6. Kortelainen, J. et al. Br. J. Anaesth. 109, 782–789 (2012).

    Article  CAS  Google Scholar 

  7. Kanai, R., Paulus, W. & Walsh, V. Clin. Neurophysiol. 121, 1551–1554 (2010).

    Article  Google Scholar 

  8. Marshall, L., Helgadottir, H., Molle, M. & Born, J. Nature 444, 610–613 (2006).

    Article  CAS  Google Scholar 

  9. Voss, U., Schermelleh-Engel, K., Windt, J., Frenzel, C. & Hobson, A. Conscious. Cogn. 22, 8–21 (2013).

    Article  Google Scholar 

  10. Steriade, M., Contreras, D., Amzica, F. & Timofeev, I. J. Neurosci. 16, 2788–2808 (1996).

    Article  CAS  Google Scholar 

  11. Cardin, J.A. et al. Nature 459, 663–667 (2009).

    Article  CAS  Google Scholar 

  12. Bojak, I. & Liley, D. Neurocomputing 70, 2085–2090 (2007).

    Article  Google Scholar 

  13. Crick, F. & Koch, C. Nat. Neurosci. 6, 119–126 (2003).

    Article  CAS  Google Scholar 

  14. Brown, R.E., Basheer, R., McKenna, J., Strecker, R. & McCarley, R. Physiol. Rev. 92, 1087–1187 (2012).

    Article  CAS  Google Scholar 

  15. Buzsáki, G. & Draguhn, A. Science 304, 1926–1929 (2004).

    Article  Google Scholar 

  16. Ferrarelli, F. et al. Arch. Gen. Psychiatry 69, 766–774 (2012).

    Article  Google Scholar 

  17. Brunelin, J. et al. Am. J. Psychiatry 169, 719–724 (2012).

    Article  Google Scholar 

  18. Cordes, J. et al. Neuropsychobiology 54, 87–99 (2006).

    Article  CAS  Google Scholar 

  19. Anticevic, A. et al. Biol. Psychiatry 75, 595–605 (2014).

    Article  Google Scholar 

  20. Stumbrys, T., Erlacher, D. & Schredl, M. Conscious. Cogn. 22, 1214–1222 (2013).

    Article  Google Scholar 

  21. Franke, G.H. Die Symptom-Checkliste von Derogatis (Beltz, 1992).

  22. Buysse, D.J., Reynolds, C. III, Monk, T., Berman, S. & Kupfer, D. Psychiatry Res. 28, 193–213 (1989).

    Article  CAS  Google Scholar 

  23. Lagerlund, T.D., Sharbrough, F., Busacker, N. & Cicora, K. Electroencephalogr. Clin. Neurophysiol. 95, 178–188 (1995).

    Article  CAS  Google Scholar 

  24. Nunez, P. & Srninivasan, R. Electric Fields of the Brain (Oxford University Press, 2006).

  25. Dmochowski, J.P., Datta, A., Biskon, M., Su, Y. & Parra, L.C. J. Neural Eng. 8, 046011 (2011).

    Article  Google Scholar 

  26. Neuling, T., Wagner, S., Wolters, C.H., Zaehle, T. & Herrmann, C.S. Front. Psychiatry 3, 83 (2012).

    Article  Google Scholar 

  27. Schroeder, M.J. & Barr, R.E. Clin. Neurophysiol. 112, 2075–2083 (2001).

    Article  CAS  Google Scholar 

  28. Gratton, G., Coles, M.G.H. & Donchin, E. Electroencephalogr. Clin. Neurophysiol. 55, 468–484 (1983).

    Article  CAS  Google Scholar 

  29. Addison, P. Physiol. Meas. 26, R155–R199 (2005).

    Article  Google Scholar 

Download references

Acknowledgements

We thank A. Antal and C. Stephani for technical advice, S. Weyn Banningh for data collection, J. Windt for helpful discussions, K. Schermelleh-Engel for advice on statistical procedures, C. Frenzel for technical assistance during preliminary work, and A. Melnikova and C. Naefgen for help with data acquisition of pilot data. This work was supported by the German Science Foundation (DFG Vo 650/5-1).

Author information

Authors and Affiliations

  1. Department of Psychology, J.W. Goethe-University Frankfurt, Frankfurt, Germany

    Ursula Voss

  2. Department of Clinical Sleep Research, VITOS Hochtaunus Klinik, Friedrichsdorf, Germany

    Ursula Voss & Ansgar Klimke

  3. GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany

    Romain Holzmann

  4. Harvard Medical School, Boston, Massachusetts, USA

    Allan Hobson

  5. Department of Clinical Neurophysiology, University Medical Center, Göttingen, Germany

    Walter Paulus & Michael A Nitsche

  6. Department of Psychology, Bonn University, Bonn, Germany

    Judith Koppehele-Gossel

  7. Department of Psychiatry, Duesseldorf University, Duesseldorf, Germany

    Ansgar Klimke

Authors
  1. Ursula Voss
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Romain Holzmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Allan Hobson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Walter Paulus
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Judith Koppehele-Gossel
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ansgar Klimke
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Michael A Nitsche
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

U.V., W.P. and M.A.N. designed the study. R.H. developed the filter algorithms and conducted the analyses. J.K.-G. and U.V. collected the data, U.V., R.H., M.A.N., W.P., A.K. and A.H. wrote the manuscript. All of the authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Ursula Voss.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Study Design

Double-blind repeated measures tACS stimulation (30 s duration, each) in REM sleep over 4 non-consecutive nights. Frequency of stimulation (sham, 2, 6, 12, 25, 40, 70, and 100 Hz) was counterbalanced across subjects and across nights. The experimenter operating the tACS device did not interact with the subjects. The experimenter conducting the interview stayed outside the monitoring room during stimulation, unable to identify the stimulation condition (for sham stimulation, the push button on the tACS device was activated but current was not applied). Extensive exploration gave no indication of subjective discomfort or awareness of stimulation in any subject.

Supplementary Figure 2 Montage and Stimulation Potentials

a) Montage of 22-channel EEG (bandpass filtered: 0.3 – 120 Hz, sampling rate: 512 Hz) and sites of tACS electrode placement (a, b, c, d). tACS electrodes a and b, as well as c and d were connected pair-wise. The AC current flowed mainly sagitally between a and c, respectively b and d. The combined impedances of the paired tACS electrodes were kept below 5 kΩ. EEG electrodes were referenced to Cz instead of mastoids because of the close proximity of the latter to the tACS electrodes c and d. b) Measured scalp surface potentials applied during one arbitrarily chosen maximum of a 40 Hz sinusoidal tACS stimulation in a single subject, with all polarities reverting every 12.5 milliseconds (voltage scale given in relative units). See Online Methods for details. c) Mathematically derived dura potential (CSD estimate). The dura potential indicates the effect of the stimulation current entering the skull, spreading from fronto-temporal to parieto-occipital regions, as well.

Supplementary Figure 3 Empirical Model of Dream Consciousness

Positions on the indicated primary-to-secondary consciousness axis are based on the logarithm of ratios of mean scores in lucid and non-lucid dreams. All factors have been identified as components of dream consciousness. Lucid dreams, which are thought to add elements of secondary consciousness, are characterized by increased ratings in reflective INSIGHT, CONTROL, and DISSOCIATION; and, to a lesser extent, by access to MEMORY, as well as NEGATIVE and POSITIVE EMOTIONS. THOUGHT and REALISM do not differentiate between lucid and non-lucid dreams. The graph is based on the laboratory scores shown in Fig. 4 of Voss et al.9 (LuCiD scale). For validation purposes, mean scores of the dream reports under sham condition in the current sample were compared to those of the original study on the basis of which these factors were constructed9. Scores of both studies compared well, suggesting reliable subjective ratings in the current study (INSIGHT: t = 0.91, p = 0.366; CONTROL: t = 0.46, p = 0.647; THOUGHT: t = 1.20, p = 0.231; REALISM: t = 1.08, p = 0.283; MEMORY: t = 1.59, p = 0.133; DISSOCIATION: t = 0.73, p = 0.470; NEGATIVE EMOTION: t = 1.49, p = 0.139; POSITIVE EMOTION: t = 0.39, p = 0.700, df = 106, all n.s.).

Supplementary Figure 4 Sample EEG Recordings During tACS

EEG and EMG data recorded during sham condition (top) and with tACS stimulation of 12 Hz (center), respectively 40 Hz (bottom). The EEG at site Fpz is shown unfiltered while the EMG is filtered to demonstrate that subject remained in REM sleep throughout stimulation; awakening (sham: t = 220 s, 12 Hz: t = 195 s, 40 Hz: t = 215 s) is signaled by a marked change in the EMG. Note also that the EEG samples shown are not corrected for ocular artefacts. The horizontal accolades schematically indicate the phases defined in the main text, namely, before stimulation (I), during stimulation (II), as well as after forced awakening (IV). During phase II, the tACS current is applied for 30 s generating the very large amplitudes indicated as a solid blue block in the unfiltered EEG (center and bottom frames). Phases I, II, and III (not indicated here) cover REM sleep, and phase IV corresponds to wakefulness

Supplementary Figure 5 Grand Average EEG Power vs. Frequency

Grand average FFT power was computed as a function of the EEG frequency (resolution = 1 Hz) for indicated stimulation conditions: sham (N = 30), 2 Hz (N = 31), 6 Hz (N = 19), 12 Hz (N = 18), 25 Hz (N = 26), 40 Hz (N = 44), 70 Hz (N = 21), and 100 Hz (N = 18). Averaging took place over frontal and temporal electrode sites (Fp1, Fp2, Fpz, F3, F4, Fz, F7, F8, T3, T4, T5, and T6), over stimulation sequences, and over subjects. The dips in power mark those frequencies for which a notch filter was applied. Phases I & II correspond to REM sleep, phase IV to wakefulness.

Supplementary Figure 6 Additional Mean LuCiD Scores vs. Stimulus

Mean scores (±1 s.e.) are shown for the LuCiD factors THOUGHT, REALISM, MEMORY, NEGATIVE EMOTION, and POSITIVE EMOTION. Significant contrasts from MANOVA (N = 207) exist only for REALISM (sham vs. 2 Hz: p = 0.032, 2 Hz vs. 100 Hz: p = 0.0097) and for MEMORY (sham vs. 70 Hz: p = 0.035, 40 Hz vs. 70 Hz: p = 0.009). In accordance with previous laboratory data9, THOUGHT and REALISM are reported in a similar pattern across all stimulation conditions. Albeit not reaching statistical significance, ratings for both NEGATIVE and POSITIVE EMOTION appear to decrease linearly with increasing stimulus frequency (as indicated by dashed lines).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 and Supplementary Tables 1–4 (PDF 753 kb)

Supplementary Methods Checklist (PDF 465 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Voss, U., Holzmann, R., Hobson, A. et al. Induction of self awareness in dreams through frontal low current stimulation of gamma activity. Nat Neurosci 17, 810–812 (2014). https://doi.org/10.1038/nn.3719

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3719

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing