1. Transforming transcendence into trait - An electrophysiological approach: The Model of Mindfulness Meditation Aviva Berkovich Ohana 1, Dr Avi Goldstein 1,2, Prof. Joseph Glicksohn 1,3 Background Transitory 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 Methods EEG 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 Matlab software), 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 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 Uses Oral Report Questionnaires After meditation before meditation Interview Questionnaires Alternate Uses 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. Time1 – reflects trait Time 2- reflects state Reflects temporal cognition changes Higher amplitude reflects higher attention Lower amplitude reflects lower automatization Reflects field dependence & spatial cognition changes Reflects creativity Preliminary Baseline Results 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).

2. Transforming transcendence into trait – An electrophysiological approach: The Model of Mindfulness Meditation Aviva Berkovich Ohana The Multidisciplinary Brain Research Center, Bar-Ilan University, ISRAEL