Mar 292017

An interesting feature of Power Spectral Density (PSD) graphs of EEG recordings is the peaks that sometimes appear in the spectrum. Below are two examples of spectra with peaks:

PSD lb S23

In both graphs, we note that power density varied across the beta band, manifesting itself as peaks. In the upper graph there is a double peak near the top of the beta band, around 28-30 Hz. In the lower graph, there is an additional peak near 17 Hz, as well as a strong peak near the boundary of the theta and alpha bands (about 8.5 Hz). Using only the absolute mean power across either the theta or alpha bands would not have done justice to the size of this peak.

While the best way to capture the significance of the peaks would be to mathematically integrate the Power Spectral Density over the width of the peak, this could be a challenging undertaking. I chose instead to do a semi-quantitative analysis using visual inspection of each PSD graph, along with a graphical key to assign a score from 0 to 3 indicating the “prominence” of the peak. A score of zero means that there is no peak, a score of 3 indicates a very strong peak and scores 1 and 2 correspond to intermediate conditions. The key was built using screenshots of PSD graphs from the sample.

Key for scoring alpha and beta peaks:

key for scoring peaks

Alpha peaks consistently appeared around 7-12 Hz. The beta peaks I was interested in were near the top of the beta band 26-32 Hz. I scored each graph and plotted the values for beta (front sensors) and alpha (back sensors) vs hours of meditation experience:

peak beta lf vs hrs peak beta rf vs hrs


peak alpha lb vs hrs peak alpha rb vs hrs

While these plots suggest that the most prominent peaks (score=3) occur for practitioners with several thousand hours of meditation experience, they show that less prominent peaks can also be associated with extensive meditation practice.

This part of the investigation suggests that prominent (scored as 3) beta peaks in the front and alpha peaks in the back appear among more experienced practitioners but not among novices. On the other hand, there are also experienced meditators who do not show the prominent peaks. So we cannot say that we have found a definitive ‘signature’ of zazen meditation.

Mar 292017

The previous study which used average mean band power over meditation intervals of 10-15 minutes did not reveal a strong correlation with meditation experience. However, a recording made on the 3rd day of a 7-day sesshin showed a linear increase in beta and gamma power over a single round of meditation. Should we be looking not at the average over a whole period, but rather focus on a “best” interval near the end of the period?

beta FP2 Day 0

What would happen if we selected a 2-minute interval near the end of the period and used the mean absolute power for that short interval as a measure of the meditation?

To find out, I reexamined the EEG recordings for each of the thirty subjects in the sample, selecting a “best” 2-minute interval near the end of the meditation. Results for beta power at the front sensors are shown below:

 best2 beta lf vs hrs  best2 beta rf vs hrs

Results for alpha power at the back sensors gives us the following:

 best2 alpha lb vs hrs best2 alpha rb vs hrs

It looks as if our analysis using “best 2-minute” intervals doesn’t provide any more suggestion of a correlation between band power and hours of meditation as the previous analysis using the whole interval of meditation.

Further investigation was in order. Instead of using the mean absolute power over selected intervals, I chose to examine peaks in the Power Spectral Density graphs as another avenue of research.

Mar 292017

Meditation practice can be described as skill development—the more hours one practices, the more adept one becomes. to me, it seems plausible that time on the cushion with focused attention has resulted in development. Sometimes my motivation flags and I wonder whether I am wasting my time, but overall, I feel that my practice of zazen has strengthened my awareness of habits of the mind, my recognition of conscious choice and my ability to return to clarity. I presume that my practice is not that different from the practice of others.

So what evidence is there for skill development, beyond anecdotal reporting?

I believe that there must be physiological correlates of meditation that can be measured and that changes over time should be observable. If this is true, then we would expect to see observable differences between novices and expert practitioners of meditation.

Previously, I had found an increase in beta and gamma power in my own brainwaves during individual meditation sessions and a hint of possible increase in beta and gamma during the course of a 7-day meditation retreat. However, a brief look at the brainwaves of four long-time practitioners revealed no particular commonality.

To investigate this further, I extracted EEG data from recordings of 30 subjects. The recordings had been made in different contexts over the course of a two-year period; some were during or immediately after meditation retreats, others were made outside of formal retreats. Some recordings were made in studies where subjects were asked to meditate during part of the session and not meditate at other times. In all cases, data was extracted from segments during which subjects were asked to “count their breaths” or “meditate” or “do zazen.” The reason for merging data from several diverse investigations was to increase the number of subjects in the sample.

Prior to participation in any of these studies, subjects were asked to estimate the total number of hours of their meditation experience over their whole life. A paper form was given to each subject which included a table to aid in making the estimate. The table had columns for the average time of daily meditation and the number of years of this daily practice. It also included the number of meditation retreats the subject had participated in and the average number of retreat days and hours per day of meditation during the retreat. All the numbers were converted to hours and totaled. While this was a challenging exercise for people, it did help to ascertain a rough estimate for meditation experience.

Among these thirty subjects, experience reported ranged from 1 hour to 36,000 hours. It would be interesting if the EEG patterns for highly trained meditators were substantially different from those of novices. I initiated an effort to find out.

Subject hours of meditation experience

The next step was to quantify results from the EEG recordings. Using the Physiology Viewer application, I identified an interval of roughly 10-15 minutes with a stable EEG signal for each meditating subject. I chose the absolute mean value of EEG power for each of the standard frequency bands (delta, theta, alpha, beta and gamma). I decided to focus first on alpha power, with the goal of displaying a graph of power vs. hours of meditation experience.

Since the range of experience was so large, I chose the horizontal axis to be the logarithm (base 10) of the number of hours rather than a linear scale of hours. The values for absolute band power measured by the Muse are logarithms which can be negative (when the power values are less than 10), so I decided to plot the inverse log (base 10 exponential) of the absolute band power on the vertical axis. This way all ordinate values would be positive. Below are the results for each of the four sensors (lf, rf, lb, rb) for the alpha band.

 Alpha power lf vs hrs  Alpha power rf vs hrs
 Alpha power lb vs hrs  Alpha power rb vs hrs

The characteristic that most stands out is much stronger alpha power at the back sensors (lb and rb) compared to the front (lf and rf). This suggests that if we want to use the alpha signal as a correlate to practice, we should focus on the back electrodes (TP9 and TP10).

Examining the bottom two graphs, we see no appreciable difference between subjects with ~10,000 hours of experience vs those with ~1,000 hours. Comparing subjects having less than 100 hours of experience (three subjects) with subjects having more (twenty-seven subjects) may suggest that more experienced practitioners had stronger alpha power, but the correlation is weak. Unfortunately our sample included only three people with less than 100 hours experience. If we were to find half a dozen novices with strong alpha, then any correlation with experience would disappear. We just don’t know from the available data.

There are several highly experienced subjects in this sample who show no particularly strong alpha signal at the rear sensors. This particular measurement leaves our original question unanswered. Strong alpha power at locations TP9 and TP10 does not seem to be a predictable effect of long term meditation practice.

What about beta or gamma power? An earlier finding indicated that beta and gamma power increased in my own brainwaves over the course of a 7-day retreat. To find out, I did a similar analysis as above for the beta and gamma bands. Results for beta are shown below (gamma results were similar):

beta power lf vs hrs  beta power rf vs hrs
 beta power lb vs hrs  beta power rb vs hrs

As in the case of alpha power, we see that subjects with the most experience in meditation exhibit a wide range of beta power: some show more than novices; others show comparable values. In any case, power in the beta band at either front or back sensors is not a good predictor of meditation experience.

There are several possible explanations for this lack of correlation, for example,

  1. The hours of meditation experience reported by subjects on our questionnaire is not a reliable independent variable–our estimates of how many minutes of meditation per day, days per year, and number of meditation retreats are extremely rough, especially when trying to recall many years in the past.
  2. Sitting on a cushion and “meditating” can mean different things to different people. Even within a single tradition (i.e., Zen), teachers have guided students with different instructions. Students have had varying degrees of success in applying those instructions.
  3. The limited number of four sensors in the Muse headband may be insufficient to register the electrical signature of meditation.
  4. Perhaps none of the EEG frequency bands used in this part of the investigation (alpha, beta, gamma) reflect meditation expertise.
  5. Perhaps the choice of using 10-15 minute intervals of meditation and averaging power over the whole interval was not the best strategy. Maybe it took several minutes for meditators to “get into the groove,” in which case, it might be more revealing to select a shorter interval (‘best’?) near the end of the meditation session.

The next part of the investigation examined power over these selected ‘best’ intervals.

Mar 052017

A young meditation practitioner (26-year-old, female) joined the September 2016 7-day sesshin at Tahoma Monastery. She had some previous meditation experience, but this was her first time training with Shodo Harada Roshi. Her brainwaves were recorded once while not meditating, and on three occasions while doing zazen. Between September and February, she averaged 4 hrs/day of meditation practice. Recordings were made on:

Sep 7, 2016 – sitting quietly, but not meditating
Sep 7, 2016 – zazen before September osesshin (~600 hours previous meditation experience)
Sep 17, 2016 – zazen after September osesshin (~50 hours additional meditation)
Feb 22, 2017 – zazen after February osesshin (~1300 accumulated hours of meditation experience)

The following features stand out:

  1. Peaks in the alpha band, recorded at the left rear electrode (TP9) grow stronger with each subsequent zazen period. While not evident in the recording of the non-meditative condition, these peaks appear more pronounced in each successive meditation recording.
  2. The frequency of eye blinks while meditating is much less than when not meditating. In addition, there seems to be a trend of decreasing eye blink frequency with greater meditation experience.
  3. At the front sensors (FP1 and FP2) there seems to be growing power in the higher frequency (beta and gamma) bands relative to a lower frequency band (theta) with greater meditation experience.

Peaks in the alpha band become more prominent with zazen practice

First, let us examine the Power Spectral Density charts at the left back sensor (TP9) .

When subject is not meditating, there is no significant peak in the alpha band.

In the first recording, subjects were instructed to meditate for 20 minutes, then to stop meditating for 5 more minutes. When asked if she was able to NOT meditate during the final five minutes, the subject said,

“I think so. I was just trying to think really fast about anything, about things I was trying to remember, to remember things, to recall. And then the whole time I was just making stuff up.”

Small peaks are visible in the alpha band during zazen meditation (before osesshin)

At the end of the period, the subject remarks,

“That was really hard. It made me nervous.”


The next recording was made a week later, at the end of osesshin.

Alpha peaks begin to appear after the osesshin.

Investigator: Have you noticed a change in the quality of your meditation during week?

Subject: Definitely. Completely. I feel like I kind of earned how to meditate, actually. I don’t know. It’s not like I haven’t done it before. But now it’s starting to click now.

Investigator: Was there a kind of a key idea you that you used, or a technique you adjusted to do it?

Subject: Learning how to relax.

Investigator: How to relax?

Subject: Yeah. That’s really hard for me.

The final recording was made 5 months later after a second osesshin. The subject had practiced meditation about 4 hours per day in the intervening time.

Two distinctive peaks appear in the alpha band (5 months after the previous recording).

Investigator: How has this sesshin been going for you?

Subject: It’s been going up and down.

Investigator: How about this particular sitting right now?

Subject: I couldn’t really get into the breathing like I wanted. I couldn’t fully relax. Physically, sitting is still hard for me.

Investigator: So with your breathing, what were you aiming for?

Subject: Comfortable. Something more round. Sort of, that doesn’t feel so forced.

Investigator: But you weren’t finding that in is this round?

Subject: I didn’t really sink into it, but it wasn’t terrible.

Note that there are two distinct peaks two peaks in the alpha band as opposed to just one seen in most other subjects.The significance of this is unknown.

Similar results were obtained for the right back sensor (TP10) :

No alpha peak for the non-meditating condition.


Slight alpha peak during zazen meditation.


Small peaks in the alpha band during zazen (after sesshin).


Pair of clear alpha peaks after the February 2017 osesshin.

Eye blinks become less frequent with meditation practice

The Muse headband automatically records eye blinks. Eye blinks were anti-correlated with meditation–that is, the stronger a person’s meditation focus, the less frequently they blink their eyes. Below are the results for the present practitioner, subject S23:

Frequent eye blinking when not meditating.


Less frequent eye blinks when doing zazen (same recording as above).


After the September osesshin, eye blinking is substantially reduced.


After the February osesshin, eye blinking has nearly ceased.

Higher frequency bands develop greater power relative to lower frequency bands with greater meditation experience

Radar charts of relative band power for each of the four recordings suggested that higher frequency bands began to dominate lower frequency bands on successive recordings of meditation, after a week-long osesshin and then again after a second osesshin five months later.

Delta frequency appears to predominate, but this probably due to frequent eye blinking (see spectrogram below).

Higher frequencies (gamma and beta) appear at left front electrode (FP1).

Greater power of beta and gamma in frontal region compared to rear.

Beta and Gamma frequencies predominate.

Frequent blinking masquerades as a delta band signal as can be seen in the correlation between the low frequency patches (below 4 Hz) in yellow-orange of the spectrogram below on which the eye blink signal has been superimposed.

Eye blinks result in registering low-frequency (delta) oscillations so were therefore ignored in the subsequent analysis. See also the post, Sleuthing a delta wave mystery.

To get a better handle on the increase in high frequency oscillations with greater practice, we defined a new parameter which represents the ratio between a stand-in for high frequency (beta power) and a stand-in for low frequency (theta power). Values were normalized to be positive. Results are given below.

Ratio of beta to theta power when not meditating

Ratio of beta to theta power during zazen before first osesshin

Ratio of beta to theta power during zazen after the first osesshin

Ratio of beta to theta power during zazen after the second osesshin five months later

The ratio of beta to theta power seems to support the hypothesis of increasing high frequency oscillations in the frontal area with greater zazen practice.

Mar 052016

During one EEG recording session, a subject was asked to first meditate by following her breath for 7 minutes, then to start worrying about something for the next 7 minutes. She chose to worry about work. We see in the spectrogram below, around t=420 seconds (7-min), there is a distinct increase in low frequency oscillations at the delta and theta levels.

spectrogram of meditating, then worrying

A spectrogram is in effect a three-dimensional graph: time on the horizontal axis, frequency on the vertical axis and color patches to indicate the amplitude of each frequency component at successive times. Here we see greater intensity (indicated by orange and red color) in the lower frequencies after the 420-second mark.

We can also use radar charts to examine the relative power for each of the five frequency bands. the following two charts apply to the initial 7-minutes of meditating and to the next 7-minutes of worrying.

following breath



What is going on here? Why should the relative delta power be so strong when the subject is worrying? Aren’t delta waves associated with deep sleep?

Before continuing, we should examine the possible effects of certain artifacts in the EEG signal, especially those due to blinking the eyes. Motor impulses to the eye muscles produce electrical signals that are picked up by the EEG sensors, but these signals tell us nothing about activity in the cortex.


One possible explanation of the exceptionally high amplitude of low frequencies is that during the interval of worrying the subject blinked frequently while in the preceding interval of following her breath, she blinked only occasionally.

To explore this further, we made a recording in which another subject (S1) blinked deliberately at a rate of about once every two seconds for 20 seconds. Below are the spectrogram and immediately below it the time series graph of eye blinks. During this 40-second interval of interest, the subject blinked 11 times in 20 seconds.

spectrogram for eye blinks

It is quite clear that eye blinks result in low frequency oscillations that are readily visible in the corresponding spectrogram.

Could it be that our worrying subject was blinking her eyes more frequently during worrying than she was while meditating? Selecting time series plots of eye blinks for intervals of meditating (following the breath) and worrying, we see a distinct difference.

 S3-rec66-following-blink-PSD  S3-rec66-worrying-blink-PSD

This seems to be the most plausible explanation of the high levels of delta oscillations observed: our subject blinked her eyes much more often when worrying than when meditating. These signals probably originated in eye muscles rather than in neurons in the brain.

Jan 272016

Alpha waves are generally defined as neural oscillations in the range of 7.5 Hz to 12.5 Hz. They represent the strongest electrical signals on the scalp and were first discovered by German neurologist Hans Berger in 1924). Alpha waves originate in the occipital lobe (back of the head). They are especially prominent during a state of relaxation with the eyes closed.

Due to their characteristically high power, alpha waves are the easiest EEG signals to pick up.

In order to determine the precise frequency of alpha waves as well as other neural oscillations, we implemented Power Spectral Distribution (PSD) graphs. These graphs plot the spectrum of a given EEG signal, i.e., the intensity of the signal (Db/Hz) vs. its frequency (Hz). The y-axis is logarithmic with a range from 0.1 to 100 and the x-axis is linear in frequency.

The example below shows the spectrum of the signal from the left back sensor (TP9) during a four-minute period of zazen (counting the breath).

PSD lb

The tip of the most pronounced peak falls at 8.18 Hz, at the bottom end of the alpha band.

The alpha peak is apparent in all four sensors, most prominently in the left back (TP9) sensor but also in the right back (TP10), and the sensors left front (FP1) and right front (FP2), as seen below.

 PSD lf  PSD rf
 PSD lb  PSD rb

Note that the alpha rhythm is stronger in the region near the ears (lb, rb) than in the front (lf, rf).

For a single individual (myself) over a period of twelve months, this peak has been stable during zazen practice. Across 34 sessions, the mean frequency has been 8.2 Hz with a standard deviation of 0.2 Hz.

In recordings of other people, the same peak can be seen, but at slightly different frequencies. The alpha band feature is quite robust: it seems to occur in most people, especially if they are relaxing. It occurs reliably when a person’s eyes are closed, and can also occur with eyes open as long as the eyes are relatively still and not moving about.

Among 11 different individuals of wide-ranging meditation experience, the range of the alpha peak was from 8.1 Hz to 11.0 Hz.  The mean frequency was determined to be 9.4 Hz with a standard deviation of 0.8 Hz. Thus the spread of the alpha peak frequencies across different individuals is over four times as wide (0.8 Hz vs. 0.2 Hz) as the spread of frequencies for a single individual.

Returning to the original recording of one individual, we see segments for three separate conditions: reading, following the breath, and counting the breath (eyes open for all three segments). Below is a spectrogram of the full session.


The alpha power is stronger during meditation (following or counting the breath) than it is during reading. This is indicated by the strong horizontal yellow line at frequency 8 Hz for the meditation conditions and its near absence during reading.

The PSD charts for each of these three intervals, measured at the left back (lb) sensor provides more detail on the predominate frequencies.

PSD for counting breath

PSD for following breath

PSD for counting breath

Values for alpha peaks are reading: 4 dB/Hz; following (eyes open): 32 dB/Hz and counting (eyes open): 40 dB/Hz.

A strong alpha peak is not necessarily a signature of meditation, but reading definitely suppresses the alpha oscillations compared to two kinds of meditation with eyes open.

Our next task will be to use Power Spectral Density graphs to examine other regions of the frequency spectrum, in delta, theta, beta and gamma bands.

Jul 182015

We have seen examples where the respiration rates for experienced meditators are lower than those for novices. What about patterns of inhalations and exhalations? Plotting the average respiration waveform for a novice (<200 hrs) and an expert meditator (>5,000 hrs), we see that the exhalation time is 50% longer than the inhalation time for novice and 70% longer for the expert.


comparison of respiration waveforms

Ratio of exhalation to inhalation time for novice is 1.5 while for expert is 1.7.

Furthermore, the expert breathes much more deeply than the novice, as indicated by the difference in pressure from the bottom of the exhalation to the top of the inhalation.


Jul 172015

The plots below show electrocardiogram and respiration signals for a 20-second segment of meditation.

Heartbeat and respiration

Heartbeat and Respiration during meditation. Note the increase in amplitude of the ECG signal during exhalations.

During exhalations, the amplitude of the waves in the upper plot (the sharp spikes in the electrocardiogram, known as R-waves) increase while they decrease during inhalations.

A comparison of ECG signals for a novice and an experienced meditator are shown below.

novice meditator

Heartbeat and respiration for Subject 8, a relatively inexperienced meditator. Amplitude of R-wave increases by ~10% during exhalations.


experienced meditotor

Heartbeat and respiration for a highly trained meditator. Amplitude of R-wave increases by ~50% during exhalations.


For novice meditators, this effect was small (roughly 10% change in R-wave amplitude, as shown in the upper figure, above). For highly trained meditators the effect was quite pronounced (roughly 50% as shown in the lower figure, above).

The amplitude of the R-wave is an indicator of the strength of the signal from the heart when the left ventricle is forcing blood out to the rest of the body. The electrical resistance of the body between the heart and the ECG electrode on the surface of the skin changes as the lungs fill with air and then collapse. After consulting with a cardiorespiratory expert (an anesthesiologist), I have concluded that this dramatic change in R-wave magnitude reflects the deeper breathing of the trained meditator—as the intrathoracic cavity collapses during exhalation, the gap between the heart and the outer surface of the body (where the ECG signal is measured) shrinks, thereby reducing electrical resistance and resulting in an increased amplitude of the R-wave.

Jul 162015

In the following plot of respiration during meditation, we see a regular repetition of inhalations and exhalations with a wave-like quality.

Recording of breath during Zazen meditation

My breath recorded on the 7th day of a meditation retreat.

Selecting a range of cycles, we can average the values centered around the peaks to extract a waveform that represents the entire range. Averaging over 12 cycles, we get the following:

Respiration waveform

Average waveform of the breath for subject S1 (myself) at the end of a 7-day meditation retreat

An interesting aspect of this waveform is that the exhalations are almost twice as long as the inhalations. Here, one complete cycle is 19 seconds long which corresponds to 3.2 breaths/minute. Compare this with the waveform for reading:

Reading waveform

Average waveform of the breath for subject S1 quietly reading

Jun 132015

A few years ago I realized that during Zen meditation, while paying attention to my breath, I was also aware of my heart beating. I started counting heartbeats during my inhalations and exhalations and found that during an inhalation, there were about four beats and during the exhalation roughly 8-10 beats. I thought it would be interesting to match a fixed number of beats, say ten with each exhalation, and maintain the synchronization during the meditation period. The synchronized rhythm felt pleasurable—having both the heart and lungs involved seemed to help me to maintain a clear mind. This experience was my motivation for recording an electrocardiogram (ECG) of heart rhythm simultaneously with respiration.


Jun 112015

For the past 15 years or so, I have maintained a daily meditation practice. My morning routine includes yoga stretching and 20-25 minutes of sitting meditation. During meditation, I usually start by counting my breaths. If and when my mind quiets down, I transition to following my inhalations and exhalations, and being aware of bodily sensations and sounds in the environment. Some days I’ll sit again just before bed. I find this routine is good for maintaining perspective on the concerns that come up during the day. It helps reduce frenetic mental activity and brings me to a place of calm.

In addition to daily practice, for several years I have participated in 7-day intensive meditation retreats, or sesshins, three or four times a year at the Tahoma Zen Monastery in Freeland, Washington. The daily schedule of sesshins includes about 7 hours of formal sitting zazen meditation plus “applied” zazen in activities such as chanting, silent meals, work, exercise and listening to a dharma talk by the Roshi, or Zen teacher. I find that after several days of meditation, such as during sesshin, my mind grows distinctly more calm. Generally, by the 3rd or 4th day, I experience periods of clarity in which the usual random jumping from one thought to another ceases and gives way to simple awareness free from internal dialog.

When I am not meditating, I tend to identify with my thoughts and feelings. The desire for a cup of coffee is MY desire. The insomnia is MY regret. The cramp in my leg is MY pain. Opinions about presidential politics are MY opinions. For me, counting breaths is a tool for disengaging from the identification process: desires, aversions, pain and opinions are what they are but the additional step of making them mine is optional. Meditation seems to reduce the feeling of drivenness of mental activity. If I find myself unable to maintain the count of breaths, it’s usually because I have become hooked on some random thought and caught on following a chain of connections from one thing to the next, far removed from the present moment. By gently returning to the awareness of the breath over and over again, these excursions gradually become less enticing.

Each day of a sesshin at Tahoma has a Golden Hour from 6:00 – 7:00 pm in which participants sit without changing posture for the full hour. Typically, I find that during Golden Hour the first 2-3 days, my practice is rather disrupted—I am pulled around by all kinds of thoughts. But by the 4th or 5th day, I can sometimes experience a clear mind. Occasionally I try to monitor this quality, by starting my count at the beginning of the hour and trying to maintain it for the full hour. Usually for the first few days of a sesshin, this is impossible—I frequently lose track of the count. But toward the end of a sesshin, I can sometimes count my breaths without interruption. The advantage of this technique is that I am less able to tell myself I am meditating when in fact I’m engaged in reverie.

I was surprised to find that I was having only 170-190 breaths in 60 minutes, or about 3 breaths per minute. It seemed much less than when I’m doing other things and not meditating.

One aspect of zazen instruction is deep breathing—on each exhalation to expel all the air from the lungs before taking an inhalation. Naturally, the inhalation brings in more air after a complete exhalation than it would during shallow breathing. I was interested in this experience of deep breathing at a slower rate and wanted to measure it with a recording device and see the data in a graph.