Transforming transcendence into trait - An electrophysiological approach:The Model of Mindfulness Meditation
Aviva Berkovich Ohana1, Dr Avi Goldstein1,2, Prof. Joseph Glicksohn1,3
BackgroundTransitory transcendent states share several Common characteristics, including: higher unity Perception with lower self boundaries, highly positive affect, heightened attention and lower automatization, alterations in temporal and spatial cognition and transition to an
exceedingly creative and non-verbal thinking style. These characteristics might become permanent as a result of long training in transcendence–
inducing techniques, such as meditation.
Research Questions ∆ What are the cortical function changes which are induced by the state of Mindfulness Meditation? ∆ Are these state changes converted with practice, and how (linearly or threshold type), into trait?∆ What are the cortical function state and trait differences between long–term meditators of Mindfulness vs. Concentrative Meditation?
Participants
Electrophysiological MethodsEEG recordings: 64-channel geodesic net (EGI); 500 Hz Fs; offline 3-100 Hz bandpass filter and 50 Hz notch; referenced to average reference; artifacts manually excluded. Preliminary EEG analyses: 60 epochs (1024 ms) from baseline 1 and 2
were analyzed for power spectral distribution by
Multi - Taper analysis (custom written Matlabsoftware), log-transformed, and averaged.
Bar-Ilan University, ISRAEL: 1 The Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center; 2 Psychology Department; 3 Criminology Department
Mindfulness (Vipassana)
Meditators
Beginners (<1000 h), n=20
Concentrative (TM)
Meditators
Control
Intermediates (<3000 h), n=30
Advanced (>3000 h), n=25
Matched gender/age, n=30
Advanced (>3000 h), n=20
Baseline
EEG
Time
Production
Simple
CNV
Choice
CNV
EFT
Meditation/
Relaxation15 min
Laboratory Procedure
2.5m Eyes Open ,
2.5m Eyes Closed
Eyes Closed Time
Estimation (X8 trials)
S1 (*)/ 1.5s interval/S2 (tone)/ press to terminate tone (x31)
S1 (number<100)/ 1.5s interval/S2 (number<100)/ press to choose higher number
Embedded Figure
Task (x8 trials)
Alternate UsesOral Report
Questionnaires
After
meditationbefore meditation
InterviewQuestionnaires
Alternate Uses
0
0.5
1
1.5
2
Control Intermediate Advanced
F3-theta-b1F4-theta-b1C3-theta-b1C4-theta-b1T3-theta-b1T4-theta-b1P3-theta-b1P4-theta-b1
Log
(Pow
er)
Group
Baseline 1
A
0
0.5
1
1.5
2
Control Intermediate Advanced
F3-theta-b2F4-theta-b2C3-theta-b2C4-theta-b2T3-theta-b2T4-theta-b2P3-theta-b2P4-theta-b2
Log
(Pow
er)
Group
Baseline 2
B
0
0.5
1
1.5
2
Control Intermediate Advanced
F3-alpha-b1F4-alpha-b1C3-alpha-b1C4-alpha-b1T3-alpha-b1T4-alpha-b1P3-alpha-b1P4-alpha-b1
Log
(Pow
er)
Group
Baseline 1
C
0
0.5
1
1.5
2
Control Intermediate Advanced
F3-alpha-b2F4-alpha-b2C3-alpha-b2C4-alpha-b2T3-alpha-b2T4-alpha-b2P3-alpha-b2P4-alpha-b2
Log
(Pow
er)
Group
Baseline 2
D
Figure 1
We ran a five-way analysis
of variance (ANOVA), having one Grouping factor (control,Intermediate, advanced (n=9;8;8, respectively)), and with repeated measures on 4 within-participant factors: Baseline (1, 2), Band (theta: 4-8 Hz, alpha: 8-13 Hz), Montage (frontal, central, temporal, parietal), and Hemisphere (L, R). The 5-way interaction was found to be significant, F(6, 66) = 3.023, p < .05, adopting the Greenhouse-Geisser p-value.
Figure 1
We ran a five-way analysis
of variance (ANOVA), having one Grouping factor (control,Intermediate, advanced (n=9;8;8, respectively)), and with repeated measures on 4 within-participant factors: Baseline (1, 2), Band (theta: 4-8 Hz, alpha: 8-13 Hz), Montage (frontal, central, temporal, parietal), and Hemisphere (L, R). The 5-way interaction was found to be significant, F(6, 66) = 3.023, p < .05, adopting the Greenhouse-Geisser p-value.
CONTROLbaseline 1
CONTROLbaseline2
ADVANCEDbaseline 1
ADVANCED
baseline 2
-2
-1
0
1
2
Time1 – reflects traitTime 2- reflects state
Reflects temporal
cognition changes
Higher amplitude
reflects higherattention
Lower amplitudereflects lower
automatization
Reflects field
dependence & spatial
cognition changes
Reflects creativity
Preliminary Baseline ResultsFigure 2
Log alpha power distribution over the scalp in baseline 1 and 2 for one control participant and one advanced meditator ( 36y and 32y old males, respectively). The plot shows EEG for n=1 rather than averages, in order to maintain physiological meaning.
Figure 2
Log alpha power distribution over the scalp in baseline 1 and 2 for one control participant and one advanced meditator ( 36y and 32y old males, respectively). The plot shows EEG for n=1 rather than averages, in order to maintain physiological meaning.
∆ We found higher frontal alpha and theta power for both meditation groups vs.
control, as expected (Fig. 1 and 2).
∆ Higher alpha and theta power (over the whole
selected montage) was found for control group
after relaxation, but no significant difference
between before meditation (trait) and after (state) for both meditation groups (Fig. 1).
∆ Interestingly, there was not any significant
difference in slow EEG rhythms between the
intermediate meditators and advanced (34±10.6y; 2011±825h accumulating
experience, and 41±11.3y; 5700±1700h, respectively).
Transforming transcendence into trait – An electrophysiological approach:The Model of Mindfulness Meditation
Aviva Berkovich OhanaThe Multidisciplinary Brain Research Center, Bar-Ilan University, ISRAEL