Hello dear reader! It’s Maria again and my meditation project is picking up speed. I’ve now recorded ~brain waves~ from 20 different people! If I’ve learned anything so far, it’s that in science it’s data or bust. I’ve been soliciting people over email and clipboarding more than a Jehovah’s Witness. If this science thing doesn’t work out, at least I’ll have canvassing skills… For the past couple weeks I’ve gone to so many open meditation sessions that I’ve started to make friends! There are weekly “sits” with the Ann Arbor mindfulness community, University of Michigan, and a local Zen Buddhist temple.
From these communities and around town, I’ve been gathering up people with a large range of meditation experience, from self proclaimed yogis to novices who have never meditated before.
There’s a mind reader in your closet
And so! I decorate the volunteers with sweatbands and wires and let bake for approximately 45 minutes in Greg’s closet. With these headband scalp recordings, the most reliable signal that we can pick up is the alpha wave, a frequency of oscillation that was discovered by Hans Berger in the 1920’s. As a student around my age, he fell off of a horse and in this moment of mortal danger believed that he had spontaneously transmitted his thoughts to his sister. He later became obsessed with proving the physiological basis for “psychic energy” and developed a tool to record the electrical current of the brain from the surface of the scalp using rubber bands and silver foil (not so different from the sweatbands and buttons I’m using this summer).
I’m recording from the frontal, temporal, occipital, and left parietal areas – locations related to vision, complex object recognition, planning, and tactile attention that I have taken from a corresponding EEG and FMRI studies. The goal is to compare the alpha waves from these areas during different tasks. When the eyes are closed and the visual cortex is not receiving information, and the neurons oscillate slowly at the same rate to produce a summed wave called the alpha frequency. In contrast, when they eyes are open and the visual cortex is active and receiving various types of information, the neurons will fire out of phase and no distinct waveform will be observed (Backyard Brains has a stellar visual explanation of this here). Because alpha waves are thought to correspond to the idling state of neurons, I am curious to see if the waves be affected by more than just visual stimuli. Perhaps meditation is more or less “idle” than other states of rest.
A problem that I’ve run into is what to compare meditation to. What is a consistent control that I can measure meditation against? What the heck is your resting state, the state your brain defaults to when you are not consciously concentrating or directing your thoughts like with meditation or math? So far, I’m testing out what the prompt of “eyes closed rest” will bring about in both the EEG data and what they report to have been thinking about during the open-ended task. So far, over half of all participants have explicitly mentioned “what I need to do today” as the content of their thoughts during the rest task.
I am also testing a more specific contrasting task that is a theoretical opposite to meditation: rumination – a psychological state that is associated with depression. In terms of thinking about yourself, meditation is a kind of experiential self focus in the present moment, whereas rumination is often references past experience in a narrative way. I also leave the electrodes on during the survey questions and ask them questions verbally as another comparative task.
Blinking is not sleeping
I wrote a little bit of code to take calculate the amount of time during each task that the brain waves were in a certain frequency i.e. the amount of time alpha waves are present during meditation.
Looking at the data from individual recording sessions so far, you can see that in the frontal region, the delta frequency band has more power on average, but this is actually due to eye blinks and not real delta waves!
The FFT algorithm generates a spectrogram (blue boxes) by converting the electrical signal into frequency components of Hz or cycles per second. Spontaneous blinks, which happen at around 0.3 Hz or 15-20 times per minute are often mistaken for delta frequency waves that occur during deep sleep (0.5 to 3 Hz). Although the difference in signal is from eye muscles and not the brain, it suggests that for some reason people blink differently during different tasks. Eye blinks may not be the biomarker that I’m looking for, but it does indicate that there is some difference between the mind states.
PS: here’s a sneak peek of a little side project of portable EEG recordings.
Since I have been struggling with what to use as a control, I figured that I should see if I can measure all mind states at all times!