BrainBot on the right track

BrainBot (http://www.brainbot.me/) is a “soon-to-be-released” app that uses the NeuroSky platform to provide feedback to users on their brain state.  This sounds like so many other meditations apps out there, but BrainBot is decidedly different.  For one, the developers went to the trouble of actually researching meditators.  They went trekking through the Himalayas and plugged in meditating monks to the NeuroSky headgear to see what they actually did while mediating.  They also thought about what would be the most useful feedback to a meditator.  Giving positive feedback (“you’re doing great”) would only interfere with meditating.  Giving a reminder or warning (“oops, wandering” or “notice  what is happening, and return to the breath”) actually could be helpful, particularly considering the distinct possibility that the warning would come much faster than the meditator`s unaided awareness of the arising of distraction.  This is very similar to the approach that I developed and wrote about a year ago in my post, “Automating along the road to mindfulness.”

Rohan Dixit, the neuroimaging guy on the BrainBot team, wrote an article (Dixit, 2012) that provides more detailed information about their methodology.  Their initial research involved comparing meditation and baseline epochs from a cohort of 31 long-term mediators from Tibetan and Indian monastic backgrounds.  The question they asked was whether it was possible to distinguish between the baseline and mediation state using the power of multiple frequency bands simultaneously.  Using a single-sensor at the right prefrontal area, as afforded by the NeuroSky headgear, mind-wandering during a resting period was compared to 15 minutes “during which they were asked to perform whatever type of meditation was most familiar.”   Using a classification system based on a support vector machine approach, they found that it was possible to distinguish between the baseline and meditation state at a rate over 75% and over 90% in the “best cases.”

The approach is commendable, but I will register a few quibbles.  The meditation styles were clearly heterogeneous, which suggests that the meditators were not all doing the same thing.  However, the model of meditation (return to the breath when aware of wandering) that the BrainBot uses is that of focused awareness as opposed to open monitoring (awareness of whatever shows up).  In the Ted talk given by Rohan (https://www.facebook.com/BrainBot.me/posts/162738513876839), the BrainBot emits tones continuously, which to me would be distracting.

Dixit, R. (2012, March). Meditation Training and Neurofeedback Using a Personal EEG Device. In 2012 AAAI Spring Symposium Series.

Is there a tipping point for neuroshaping technologies?

Rinzai Zen Master Philip Kapleau in his Zen Dawn in the West, published in 1980, challenged the idea that technological devices should be used to aid meditation.

Kapleau recounts how he was hooked up to a biofeedback machine that cost $200 (approximately $600 in 2014 dollars).  He easily exceeded the parameter for relaxation.  He gave his opinion of it:  "You can achieve relaxation, and far more, with zazen--without spending two hundred dollars for a mechanical toy.  Toys are for children not for adults!"

When asked his opinion of the claim that brainwave feedback could achieve results in far less time than traditional meditation, he exclaimed:  "You must be kidding!  Even if one is able while "plugged in" to ease into a relaxed state, this hardly brings deeper calm or inner peace of mind; it does not answer fundamental questions of existence; it does not transform one's life in any real way, all of which Zen awakening does" (p. 39).  His last dismissive comment on the subject:  "One who regularly plugs into a machine to relax loses the ability to act out of his own deepest resources and instead of being master of the machine becomes its slave.  This is not Zen.  Zen develops freedom, not neurotic dependence" (p. 40).

Kapleau sounds rather cranky, but he raises some interesting issues that may be relevant at this time when a new generation of meditation devices and apps is emerging.  At the time that he wrote, the aim of the use of then available technology was primarily relaxation through enhanced alpha wave production.  More ambitious agendas are likely to be pursued in present and future time with greater sophistication in targeting brainwaves at specific sites.  But does the essence of his critique still stand?  Can technology provide a shortcut on the path of awakening.  Is the quantification available with these technologies a diversion from simply meditating?  Will reliance on these technologies create an unhealthy dependency?  If there is a valid role for these technologies, is there a tipping point beyond which they become a hindrance rather than an aid?

EEG profiles of meditation categories--Travis and Shear

Travis and Shear (2010) point to the potential usefulness of brain patterns as an objective language to discuss procedures and experiences resulting from different meditation practices.  They distinguish three categories: the two commonly accepted categories of focused attention (FA) and open monitoring (OM) meditation and a third category of automatic self-transcending (AST?).  They claim that different meditations can be assigned to these categories based on their eeg profiles.

The FA category is for meditations that involve staying focused on a given object and returning attention to it when the mind wanders.  The OM category is for meditations that involve non-reactive moment-to-moment monitoring of the content of experience.  The AST category is for meditation techniques “designed to transcend their own activity.”

They hypothesize that FA meditations would be characterized by increased activity in the gamma (30-50 Hz.) and beta2 (20-30 Hz.) bands because these bands are associated with highly focused attention to a specific object in the experiential field.   Beta1 (13-30 Hz.), which is associated with creating unity in our experiences, would be found in meditations in all three categories.  Posterior alpha2 (10-12 Hz.) activity should be increased in any type of sitting meditation in which the eyes are closed, since this band is associated with cortical idling.  Alpha1 (8-10), which appears to index level of internalized attention, alertness and expectancy,  should be most evident in any meditation that transcends its own activity.  Frontal midline theta (4-8) activity is a neural index of monitoring inner processes and should be most evident in meditation techniques that involve monitoring ongoing experience without high levels of control or manipulation of the contents of experience.  They note that changes in delta band activity have been noted in some studies of meditation, but not consistently.

For the purposes of summary, I will focus on only the most commonly practiced (and researched) forms of meditation that they discuss.  On the basis of their assumptions, they place loving-kindness-compassion meditation and Zen-3rd ventricle meditation in the FA category; Goenka style vipassana and Zen meditation in the OM category; and Transcendental Meditation in the AST category.

Loving-kindness-compassion meditation has been shown to produce relatively high gamma power, and there is a high positive correlation between gamma power and years of practice.  The Zen–3rd ventricle meditation, which involves focusing on a point near the crown of the head, is associated with higher beta2 activity.  Curiously, Travis and Shear do not discuss concentration meditation on the breath, which is probably the most commonly practiced form of meditation, and is usually classified as FA.

In their discussion of OM, Travis and Shear state that they could only find one study of Vipassana mindfulness meditation, and they rely for their discussion on a description of this study by Cahn and Polich (2006).  The technique studied was a Goenka style body-scan meditation.  Comparisons were made between resting and meditation conditions for 16 individuals who had practiced this style of meditation for an average of 20 years.  In this group, posterior alpha power was higher than central or frontal power with no differences in alpha between the two conditions.  Frontal theta increased during the meditation and occipital gamma power was higher.  A study of monks at three levels of experience doing zazen indicated higher levels of frontal midline theta while meditating among the most experienced monks only.

In the context of their discussion of OM, they also discuss studies of techniques that would usually be considered to be in the FA category (a Vedic form of samadhi meditation and a concentrative Qi-Cong meditation).  In studies of these techniques, higher midline frontal theta was also found along with higher theta coherence.

Travis and Shear’s discussion of AST focuses on Transcendental Meditation.  They recognize that other forms of meditation transcend their technique once automaticity is achieved, but they maintain that TM does this most efficiently.  Studies of TM meditators at different levels of experience suggest that they develop higher global alpha power and frontal alpha1 coherence.  Notably for this type of meditation there does not appear to be much difference between novices and expert.  This might be evidence for Travis and Shear’s claim of the efficiency of the technique.  It might also indicate that the technique does not result in progress.

While the idea that meditation techniques can be classified by EEG profile is very appealing, there was not an adequate basis in the studies available at the time that Travis and Shear wrote their article to make a convincing case.  FA with breath focus was not included in their survey, which strikes me as a very serious omission.  The studies included under the category of OM appear quite diverse from body-scan techniques to zazen to concentrative techniques that would normally be classified as FA.

Please feel free to comment or, if you wish, direct questions and comments to me at drampsych@gmail.com.

Cahn, B. R., & Polich, J. (2006). Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychological bulletin, 132(2), 180.
Travis, F., & Shear, J. (2010). Focused attention, open monitoring and automatic self-transcending: categories to organize meditations from Vedic, Buddhist and Chinese traditions. Consciousness and cognition, 19(4), 1110-1118.

Neurogadgets

An interesting website,neurogadget.com , provides up-to-date information on brain-computer interface devices and research.  It features lots of interesting ideas and promises of devices to be released in the future as well as news about the companies making these devices. 

The response to crowdfunding efforts on Kickstarter and Indiegogo is truly amazing.  I see that Interaxon with their promised Muse exceeded their goals for crowdfunding and went on to raise $6 million in additional funding.  The Muse, however, is yet to be released and is promised for late 2013.  The new Emotiv Insight exceeded the goal for crowdfunding on Kickstarter.  It has five channels ((AF3, AF4, T7, T8, Cz) and does not require saline preparation.  It is to be released sometime in April, 2014.

brain to brain communication via eeg

An interesting application of eeg technology:
http://www.kurzweilai.net/first-human-brain-to-brain-interface?utm_source=KurzweilAI+Daily+Newsletter&utm_campaign=028b7f6ca4-UA-946742-1&utm_medium=email&utm_term=0_6de721fb33-028b7f6ca4-282126465

Carving out categories of meditation

The distinction between focused awareness (FA) meditation and open monitoring (OM) meditation is well established in the literature on meditation (Lutz et al, 2008).  However, it is unlikely that these categories are inclusive of the many different types of meditation that have been practiced.  Travis and Shear (2010) argue that Transcendental Meditation (TM), which is usually classified as a form of FA, warrants a new category as a form of automatic self-transcending meditation (AST?).  In AST, practitioners develop effortlessness in their meditation and so transcend the specific technique that is employed. TM is not the only such technique; in fact, Travis and Shear argue this kind of transcending is common among experienced practitioners of other meditation techniques.  TM, they claim, provides a very efficient technique for developing the desired automaticity.  

In a commentary on Travis and Shear's article, Josipovic (2010) argues that the distinction that they have drawn points to a more basic difference between forms of meditation that are essentially dualistic and involve a "subject-observing-object" orientation and forms of meditation that involve nondual awareness, open awareness or open presence (OP) (Kozhevnikov et al, 2009; Lutz et al., 2007).  In a more recent article, Josipovic (2011) presents evidence based on MRI studies for the distinctiveness of this type of meditation, which he categorizes as nondual awareness (NDA).

In future posts, I will provide more detailed exposition and commentary on Travis and Shear's categories and on Josipovic's category of NDA.

Josipovic, Z., Dinstein, I., Weber, J., & Heeger, D. J. (2011). Influence of meditation on anti-correlated networks in the brain. Frontiers in human neuroscience, 5.
Kozhevnikov, M., Louchakova, O., Josipovic, Z., & Motes, M. A. (2009). The enhancement of visuospatial processing efficiency through Buddhist deity meditation. Psychological Science, 20(5), 645-653.
Lutz, A., Dunne, J. D., & Davidson, R. J. (2007). Meditation and the neuroscience of consciousness: An introduction. The Cambridge handbook of consciousness, 19, 497-549.
Lutz, A., Slagter, H. A., Dunne, J. D., & Davidson, R. J. (2008). Attention regulation and monitoring in meditation. Trends in cognitive sciences, 12(4), 163-169.
Travis, F., & Shear, J. (2010). Focused attention, open monitoring and automatic self-transcending: categories to organize meditations from Vedic, Buddhist and Chinese traditions. Consciousness and cognition, 19(4), 1110-1118.

Neuroshaping consciousness

A distinction should be drawn between traditional neurofeedback and techniques using EEG feedback that are explicitly directed at shaping introspective awareness.

Although the mechanisms underlying neurofeedback are subject to debate, the assumption is made that the brain is not only being affected but, over time, altered by the feedback received.  Conscious awareness of the feedback may or may not be required.  I found with my own clients that often those who tried to understand and control the feedback were less successful than those who simply paid attention to the feedback with a set attitude towards its occurrence (e.g., a positive attitude to positive feedback).

Neuroshaping consciousness is a skill-building tool.  It is primarily directed at revealing processes that are potentially available at a conscious level.  The feedback does not serve to reinforce the occurrence of desired brain states but to alert the user to the presence of certain processes.  The occurrence of these processes may or may not be desired ("wandering," "joy," "anger"), but the conscious awareness of them definitely is. Whatever brain changes that may occur are not a direct result of the feedback received but are assumed to be a product of the development of a consciously mediated skill.

 

Controlling a helicopter with the mind

Interesting experiment using EEG to control a model helicopter:

Brief version:
http://www.iop.org/news/13/jun/page_60302.html

The complete article:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3037732/pdf/nihms266781.pdf

A review of meditation studies

A recent review of meditation studies (Fell et al, 2010) raises issues that are worth considering.

The authors reflect on the inconclusive results from previous studies (Cahn, B.R., Polich, J., 2006).  Meditation takes diverse forms, but the authors feel that during the development of meditation practice some common characteristics are shared and passed through.  They offer two hypotheses.  The first is that every meditative training involves a similar scheme of development.  The second is that the steps are similar, beginning with similar physical demands,  With increasing experience the student focuses on an object with consequent slowing of internal dialogue accompanied by greater relaxation.  With advanced practice, the student undergoes a change in the relationship between thoughts and feelings, and the student starts experiencing mental processes as temporary and transient.  The most advanced step in meditation practice occurs when the meditator achieves certain peak experiences and undergoes permanent changes and alterations of consciousness that last outside of the mediation experiences.

In terms of EEG correlates, the authors maintain that there is a state-related slowing of the alpha rhythm in combination with an increase in alpha power which is localized in frontal regions.  This pattern occurs early on in the development of meditation practice.  The alpha oscillations are thought to reflect an increase in internal attention.

A general increase in theta activity occurs with mediation practice and is associated with more advanced levels.  Sharp bursts or theta trains, proceeded and followed by alpha, have been observed in studies and are thought to distinguish the theta that occurs in meditation from the irregular theta that reflects drowsiness.  This type of theta activity has also been observed to occur after meditation when the meditators opened their eyes and were alert.

Synchronized gamma oscillations have been associated with meditation.  Studies with long-term meditators doing different forms of focused and compassion meditation found high levels of gamma activity.  The authors speculate that gamma activity may provide ideal conditions for cortical plasticity and the formation of neural circuits.

While these generalizations provide a context to look at meditation, the diversity of meditation practices and their neurophysiological correlates warrants examination.  And there is abundant evidence that the differences matter.

Cahn, B. Rael, and John Polich. "Meditation states and traits: EEG, ERP, and neuroimaging studies." Psychological bulletin 132.2 (2006): 180.

Fell, Juergen, Nikolai Axmacher, and Sven Haupt. "From alpha to gamma: Electrophysiological correlates of meditation-related states of consciousness."Medical hypotheses 75.2 (2010): 218-224.

Spatial distribution of alpha power during meditation

Two engineers from the Taiwan group associated with the process study previously reported (Liu & Lo, 2006) investigated the spatial distribution of alpha power during meditation.  They studied Zen-meditation practitioners (the experimental group) and compared them with non-practitioners (the control group).  The technical details of the method are complex.   Here is their summary of the method, which you might want to skip if you are averse to complexity:

"We firstly adopted wavelet transform to decompose EEG signals and reconstruct waves in each frequency band using wavelet coefficients.  From the power ratio, we selected the candidates (normalized alpha-power vectors) for further spatial analysis.  Fuzzy C-means based algorithm was applied to the normalized vectors to explore various brain spatial characteristics during meditation (or, at rest).  Here we evaluated correlation coeffiicents to decide the number of clusters."

They found that (1) the alpha power in the control group decreased dramatically but not in the experimental group, (2) after meditation alpha power in the frontal area of meditators increased more than that of the control subjects (after resting-EEG recording).  The authors speculated that activating the medial prefrontal cortex and the anterior cingulate cortex during meditation may be the reason for increasing frontal alpha power.  

Liu, Chuan-Yi, and Pei-Chen Lo. "Investigation of spatial characteristics of meditation EEG using wavelet analysis and fuzzy classifier." Proceedings of the fifth IASTED International Conference: biomedical engineering. ACTA Press, 2007.

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.