Friday 4 January 2013

Representing the meditation process

Most studies of people meditating look at what brainwaves and brain regions are most prominent over the course of an entire meditation session taken as a whole.  Only a few studies have looked at the meditation process itself and what emerges over time, what is referred to as the "meditation scenario." Anyone who has meditated knows that over the course of a session, alertness may vary, topics and stories arise and pass away, diverse sensations are experienced and, if we are lucky, moments of serenity and mindfulness occur.

One of the most interesting EEG studies I have come across comes from engineers in Taiwan (Chang & Lo, 2005; Lui & Lo, 2006).  They propose methods of studying meditation that show great promise, although the technicalities of the methods will likely be intimidating to non-engineers.

In one study (Chang & Lo, 2005) 8-channel recordings (F3, F4, C3, C4, P3, P4, O1 AND O2) were made of Zen meditators at various levels of experience who meditated over a 40 minute period.  (The number of meditators in the experimental group and the number of non-meditators in the control group are not clearly stated.  The description of the type of meditation does not appear to be insight meditation but something similar to concentration meditation in the Theravada tradition.)

Their analysis involved "novel fuzzy-merging strategies and wavelet features," the explanation of which can be obtained by those brave enough to read the article.  In essence, the "cluster-managing strategies" employed in the automated analysis achieved an interpretation close to the result of naked-eye examination of the EEG.

They distinguished five different meditation states:  delta, delta plus theta, theta plus slow alpha, high amplitude alpha, and an amplitude suppressed wave state, which they call phi.  Five different "meditation scenarios" were observed in the meditators studied.

A)  Persistent alpha activity dominates the entire meditation session.  Phi activities of different duration appear intermittently.  The meditators reported flights of thought throughout the meditation session with abrupt shifts to peaceful states accompanied by feelings of light.
B)  Four EEG patterns--alpha, delta, theta and phi--appear rotationally.  Meditators reported switches among sensations of interference of mental activities, alertness and tenseness, subliminal consciousness and feelings of sacred, peaceful light.  
C)  EEG signals of background phi predominate with very few alpha activities and scattered delta.  This occurred with a very experienced meditator.  She reported that she felt energy or light penetrating her head several times, with feelings of serenity and egolessness and liberation from her body and mind.  Thoughts and drowsiness occurred intermittently.
D)  Background phi is sprinkled with alpha rather than delta.  The meditator reported a bright light and feelings of being fully relaxed during the session.
E)  The phi patterns dominates from the beginning of meditation and no other activity is observed to be significant.

In contrast, the scenarios of the control group were characterized by dominant alpha rhythms with delta plus theta or theta appearing occasionally.  In the control group, the delta and theta emerged because the subjects fell asleep, whereas this was not true for the experimental group.  The authors hypothesized that the delta and theta that emerged in the experimental group had to do with subliminal consciousness rather than drowsiness and sleep.  The most striking result was the emergence of the phi pattern in the experimental group, which was correlated with the experience of "blessings" according to the reports of the meditators.

Fig.5 Five meditation scenarios based on evolution
of meditation EEG illustrated by the running grayscale
chart. The gray-scales from the darkest to the
brightest colors indicate, respectively, the alpha plus, delta, delta plus theta, theta plus alpha and phi patterns.

Chang, Kang-Ming, and L. O. PEI-CHEN. "Meditation EEG interpretation based on novel fuzzy-merging strategies and wavelet features." Biomedical Engineering: Applications, Basis and Communications 17.04 (2005): 167-175.

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