1. Conjunct COST B27 and SAN
Scientific Meeting, Swansea, UK, September 2006

2. Bispectral analysis of the EEG: what does it add to the state versus non-state debate in hypnosis?
Adrian Burgess,
University of Swansea
Helen Crawford,
Virginia Polytechnic Institute & State University

3. Plan of Talk What is bispectral analysis?
State –vs- Non-state theories of Hypnosis
Why is bispectral analysis relevant to the State –vs- Non-state debate?
The EEG bispectrum in hypnosis and waking for high and low susceptible participants

4. What is bispectral analysis?
Bispectral analysis is a Fourier based method for examining the coupling between frequencies in different ranges
The bispectrum is defined as:
Where X(.)=Fourier Transform of the time series x(t) and * indicates the complex conjugate
Bicoherence is the normalised bispectrum:

5. What is bispectral analysis?
Within Channels
Between Channels
1st order
Mean
2nd order
Fourier Spectrum
Coherence
3rd order
Bicoherence
Cross-bicoherence

6. State -vs- Non-state theories of Hypnosis
State theorists believe that hypnosis is an altered state of consciousness,
Non-state theorists believe that hypnotic effects are the product of more-mundane psychological processes such as expectancy & role-play

7. Neurophysiological evidence in favour of the State-Theory
More than 20 years of EEG/ERP research has shown that the hypnotic state is associated neurophysioloigcal changes in
Alpha
Theta
Gamma
ERP (e.g. MMN, Somatosensory ERP) etc….
However, the differences are
quantitative not qualitative
cf other states of consciousness
within the normal range

8. Why is Bispectral Analysis relevant to the State -vs- Non-state debate?
Bispectral Analysis has been shown to be a useful measure of level of consciousness
~1000 research papers on Bispectral Analysis and anaesthesia
The Bispectral Index (BIS®) is a patented technology produced by Aspect Medical Systems that uses
the bicoherence in the EEG
the ratio of EEG power in the delta (1–4 Hz) and beta (13–30 Hz) frequency ranges
the proportion of the EEG that is isoelectric (i.e. electrical silence)
to produce an index of depth of ‘hypnosis’

9. Hypotheses
Participants with high susceptibility to hypnosis will show a significant change in the bispectrum of their EEG between the waking and hypnotic states
Participants with low susceptibility to hypnosis will NOT show a significant change in the bispectrum of their EEG between the waking and hypnotic states

10. Method - Participants Healthy, young, right-handed volunteers
Pre-selected using the Stanford Hypnotic Susceptibility Scale (SHSSC)
12 high susceptible (SHSS-C ≥9)
Age range 20-24
10 women, 2 men
12 low susceptible (SHSS-C ≤4)
9 women, 3 men

11. Method- EEG Recorded EEG from young, healthy volunteers
32-channel Neuroscan Synamps
28 EEG Channels
Sampling rate 500Hz
Bandpass Hz

12. Method- Procedure Waking SHSS-C Hypnotised Pre-induction Eyes Closed
Stanford Hypnotic
Susceptibility Scale
Pre-induction
Eyes Closed
Waking
Pre-induction
Memory test
Hypnotic
Induction
SHSS-C
Post-induction
Eyes Closed
Hypnotised
Post-induction
Memory test

13. Calculation of the bispectrum
Bispectrum was calculated on the Eyes Closed Condition in
Waking (pre-induction)
Hypnosis (post-induction)
Calculated using the MATLAB toolbox ‘Higher Order Spectral Analysis’
Averaged Bispectrum from the mean of ~4 minutes of EEG divided into epochs of 1.024s
Range 0-100Hz with a resolution of ~1Hz.

14. Example of an EEG bispectrum
Alpha Peak (10Hz,10Hz)
Alpha-Delta Coupling (8Hz,2Hz)
Delta Peak (2Hz,2Hz)

15. Topography of the bispctrum

16. Bispectrum by Group and Condition

17. Partial Least Squares Regression
A combination & extension of:
Multiple Regression
PCA
Designed to identify simultaneously
Whether the experimental design has an effect
Where in the data the effect is seen
Used rotated PLS with
Hypnosis -vs- Waking
For High and Low susceptible groups
1000 randomizations
1000 bootstrap samples
Output
Latent variables showing contrasts
i.e. is there an effect?
Saliences showing location of differences
i.e where is the effect
From Lobaugh et al., 2000

18. LV 1; 95.3% cross-block variance, p<0.01
1st Latent variable – PLS of Bispectrum
LV 1; 95.3% cross-block variance, p<0.01
HIGHS LOWS

19. Topography of reliable differences between Waking & Hypnosis
Bispectrum higher in the Waking condition
Midline frontal
Temporo-occipital

20. Reliable differences between Waking & Hypnosis – across all electrodes
Bispectrum higher in the Waking condition

21. Summary
PLS analysis showed significant differences in the bispectrum between waking and hypnosis for the High Susceptible group
Bispectrum was higher in the waking condition esp at high frequencies
Midline frontal
Temporo-occipital sites
What about bicoherence?

22. LV 1; 64.6% cross-block variance, p<0.26
1st Latent variable – PLS of Bicoherence
LV 1; 64.6% cross-block variance, p<0.26
HIGHS LOWS

23. Why the discrepancy?
The only difference between the bispectrum and bicoherence is the normalisation
Normalisation is by the power in the signal at the relevant frequencies
Therefore, the differences between Waking and Hypnosis must be in the Fourier Spectrum
However, with very low power levels, esp at high frequencies, normalisation can give erroneous estimates of bicoherence

24. LV 1; 87.3% cross-block variance, p<0.045
1st Latent variable – PLS of Fourier Spectrum
LV 1; 87.3% cross-block variance, p<0.045
HIGHS LOWS

25. Reliable differences in the Fourier Spectrum by frequency Band
Left-right difference
Ant-Post difference
Global difference
Midline Parietal difference
Ant-Post difference
Ant-Post difference
RED: Waking>Hypnosis BLUE: Hypnosis>Waking

26. Reliable differences in the Fourier Spectrum by frequency

27. Summary Frequency Band Waking > Hypnosis Hypnosis > Waking Delta
Right side
Left Side
Theta
Frontal Midline
Occipital
Alpha
Global -
Beta
Midline Parietal
Gamma

28. Final Summary
High susceptibles show significantly greater Bispectral values in the waking condition than in hypnosis, esp
High frequencies
Midline frontal
Temporo-occipital sites
There are no differences in Bicoherence
The differences in the Bispectrum are due to differences in the power spectra of the EEG
Calculation of the Bispectrum is problematic

29. Conclusion
Q. Does bispectral analysis add anything to the state versus non-state debate in hypnosis apart from complexity?
Probably not
But, with improved estimation of bicoherence it might
But, PLS analysis of the FFT was helpful in elucidating the EEG power differences seen between the waking and Hypnotic states seen in High Susceptibles
Ho hum

30. Thank you