Meditation: What changes should I look for in an EEG?

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#1

Has anyone here recorded EEG activity during meditation? Chip Audette has written three blog posts about his findings when he recorded EEGs of two meditation sessions: he saw increased activity in the 15–20Hz range in one meditator (speculated to be Trancendental Meditation), and the EEG he recorded of a practitioner of “breathing awareness” meditation showed a decrease in the amplitude of the alpha band, and a decrease in alpha coherence between T5 and O1.

In a non-rigorous look at a spectrograms I generated of a meditator’s EEG, I saw a gradual increase in alpha power over the course of the hour, particularly at F3 and F4, but I’m curious what else to look for when analysing future recordings, and if/how different types of meditation affect the meditator’s EEG activity.

Thanks!


#2

There have been numerous EEG studies of meditators during the past few decades. The results have been summed up in several meta-analyses and review papers that should provide you with a good general overview of what you might look for in a meditator’s EEG.

Here are a couple of review articles to start with:
A systematic review of neurobiological and clinical features of mindfulness meditations

Meditation States and Traits: EEG, ERP, and Neuroimaging Studies
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.418.9158&rep=rep1&type=pdf

Both of these reviews conclude that meditation (or meditational proficiency) correlates with increased alpha and theta amplitude.

Here is a haphazard handful of individual studies which for the most part seem to have come up with broadly similar results:

Changes in EEG and autonomic nervous activity during meditation and their association with personality traits
http://www.sciencedirect.com/science/article/pii/S016787600400162X

Increased theta and alpha EEG activity during nondirective meditation.
http://www.ncbi.nlm.nih.gov/pubmed/19922249

Quantitative change of EEG and respiration signals during mindfulness meditation

Non-linear dynamic complexity of the human EEG during meditation.
http://www.ncbi.nlm.nih.gov/pubmed/12231432

Mindfulness Meditation versus EEG-AlphaNeurofeedback: The Role of EEG-Alpha Enhancement in Attentional Control
http://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=3809&context=etd

There are also references on the Wikipedia article on Brain activity and meditation: https://en.wikipedia.org/wiki/Brain_activity_and_meditation

Good luck, and let us know what you find!


Best neurofeedback frequencies for mindfulness meditation?
#3

All I’ve really understood about the brain’s frequency space during meditation is that it varies. There have been a good amount of studies on the meditative brain, and all show fairly contrasting or at least differing results.

I just plotted my first meditation analysis the other week and it too is different from papers I’ve read, etc. But to my excitement, I could at least distinguish between different meditation styles. (https://mindamachine.wordpress.com/2015/07/10/comparison-of-meditation-styles/)

There are some other interesting things to look at beyond FFT space. You might find this article about EEG microstates interesting. Microstates can help us capture small phase-locking mechanisms that could encode thoughts and memories that surface during meditation.
http://www.scholarpedia.org/article/EEG_microstates (EEG microstates)
http://www.scholarpedia.org/article/Attractor_network (Attractors, the mathematical basis for the theory of memory encoding) - sorry I can only post two links


#4

@Jay_Butera Welcome to the forum, and congratulations on publishing your neuroexplorations!

I have a couple ideas which might make it easier to observe the changes between your different samples. Most processing software incorporates a notch filter to remove 60 Hz mains interference and a 0.5 Hz or 1 Hz highpass filter to remove any DC components from the signal. It looks from the spectrograms like your data may not have been filtered. If this is the case, you may find that you’ll get better visible resolution in the spectrogram by adding highpass and notch filters, so that so much of the colour range isn’t being “used up” by the very low frequencies and 60 Hz interference.

Another suggestion is to record a baseline relaxation period before the meditation. Without this, it can be difficult to tell if the changes between two meditation sessions are really due to the differences in meditation technique, as opposed to other changes in the EEG recording.

I was surprised to see alpha activity stronger at Fpz than at the parietal electrodes. I looked at the image filesnames, and it looks to me like the filenames are correct and the text labels got swapped: the top two spectrograms (labelled Fpz) look like they’re actually from the parietal electrodes, and the bottom ones without much alpha activity are from Fpz.

Thanks for the scholarpedia links. I haven’t run across the site, or the term “microstates”, before — it looks like something I should investigate further!


#5

@curiositry Fantastic advice and observation, thanks.


#6

Here’s an excellent new review article, March 2018.


Review of the Neural Oscillations Underlying Meditation

Objective: Meditation is one type of mental training that has been shown to produce many cognitive benefits. Meditation practice is associated with improvement in concentration and reduction of stress, depression, and anxiety symptoms. Furthermore, different forms of meditation training are now being used as interventions for a variety of psychological and somatic illnesses. These benefits are thought to occur as a result of neurophysiologic changes. The most commonly studied specific meditation practices are focused attention (FA), open-monitoring (OM), as well as transcendental meditation ™, and loving-kindness (LK) meditation. In this review, we compare the neural oscillatory patterns during these forms of meditation.

Method: We performed a systematic review of neural oscillations during FA, OM, TM, and LK meditation practices, comparing meditators to meditation-naïve adults.

Results: FA, OM, TM, and LK meditation are associated with global increases in oscillatory activity in meditators compared to meditation-naïve adults, with larger changes occurring as the length of meditation training increases. While FA and OM are related to increases in anterior theta activity, only FA is associated with changes in posterior theta oscillations. Alpha activity increases in posterior brain regions during both FA and OM. In anterior regions, FA shows a bilateral increase in alpha power, while OM shows a decrease only in left-sided power. Gamma activity in these meditation practices is similar in frontal regions, but increases are variable in parietal and occipital regions.

Conclusions: The current literature suggests distinct differences in neural oscillatory activity among FA, OM, TM, and LK meditation practices. Further characterizing these oscillatory changes may better elucidate the cognitive and therapeutic effects of specific meditation practices, and potentially lead to the development of novel neuromodulation targets to take advantage of their benefits.