By Hrayr Attarian, MD
Music and the Brain: The Harmonies of Our Sleeping Brains.
To sleep, perchance to dream . . . and create music.
A few months back I received an intriguing text from a colleague. She wrote: “K complexes (a unique brain wave that only appears in sleep) are like jazz notes, they are planned and reliably there but also spontaneous and reactive.” Her statement got me thinking about our internal rhythms, especially since it coincided with the March 28, 2019, edition of BBC Inside Science podcast (1). It featured a short interview with Dr. Morten L. Kringelbach of Oxford University, who had found a novel way of looking at the way the sleeping brain functions (1). A professor of neuroscience, Kringelbach stated that the diagram his team produced of sleep-related brain changes was actually put to music by his friend Dr. Milton Mermikides. Are our brains producing music while we sleep? Is the music like jazz in its spontaneity? In order to get more answers, I read Kringelbach’s research paper.
Before describing the complex findings of the publication that appeared in the prestigious Nature Communications journal (2), here is some basic background. For over half a century the objective study of sleep has been limited to looking at brain waves from four to six electrodes (or sensors) pasted at strategic locations on the scalp. Based on the occurrence of various specific brain waves (like the K complex), sleep has been divided into four stages.(3) Stage 1 (N1) is drowsiness or twilight sleep.(3) Stage 2 (N2) is light sleep, Stage 3 (N3) is deep sleep, and Rapid Eye Movement—or REM (R)—is the state in which most dreaming occurs.(3) Because biological functions are very different in R than they are in the other three stages of sleep, the latter are collectively known as NREM sleep, hence, the N preceding the numbers.(3)
Functional Magnetic Resonance Imaging (fMRI) is a way of studying brain function based on how different brain areas behave under various conditions.(2) It is a more accurate and detailed method of studying brain activity in any state of being: wake, sleep, doing mathematical calculations, playing music, etc. Nevertheless, fMRI has the limitation that study subjects must lie in the machine while they are engaging in the activity that is being researched.(2) For the purposes of this article, it means they have to actually sleep for a period of time in the noisy, narrow tunnel while the test is being conducted.(2)
Kringelbach and his colleagues asked 57 healthy volunteers in their early-to-mid 20s to lie down in the fMRI scanner with their eyes closed for 52 minutes each.(2) The subjects were monitored simultaneously with sensors attached to their scalps as is done in traditional sleep testing.(2) Eighteen were able to fall asleep and achieve all three stages: drowsiness, light sleep, and deep sleep. Based on the patterns of how different areas of the brain activated and networked with the others, 19 distinct patterns were detected. The authors called these “whole-brain network states.” Perhaps the most fascinating part of the discovery was the intricate map of transitions from one state to another.(2)
Kringelbach showed this map to Mermikides, Senior Lecturer in Music at the University of Surrey and Professor of Jazz Guitar at the Royal College of Music. Mermikides has been collaborating for a few years now with researchers and creating music out of various sleep patterns.(4) Examples of these are in the below three videos.
Mermikides immediately saw the potential of Kringelbach’s elegant and complex transition plan of the 19 sleep states as a template for musical composition. The result is this short yet captivating piece of music below.
Via email, Mermikides provided the flow diagram below as an illustration of his creative process as well as the following explanation: “These arrows like Morten’s are weighted in that they are not equally likely nor equally bidirectional.”
Kringelbach’s work is innovative and immensely significant. Although still in its infancy, the ability to use fMRI to fully comprehend the complexities of human sleep has implications beyond satisfying human curiosity. Its most important future implication would be the increased accuracy of sleep disorder diagnosis. Similarly, Mermikides’ compositions could also have, in the future, clinical importance—particularly if fMRIs in sufferers of sleep disorders can produce individual musical patterns.
Nocturne III: Restless Legs Syndrome
(Note for Videos 5 and 6: even though these examples are interesting, because they use the limited data obtained from sleep test summaries they are not ready for widespread clinical use.)
Mermikides is enthusiastic about the possibilities of his collaboration with Kringelbach, writing to me in an email:
One thing that could be said is that while my previous musical experiments translated the “surface data” of particular sleeps (be they sleep maps, PSG [polysomnography, a sleep test that monitors eye movements, brain waves, breathing, heart rate, leg movements, and oxygen levels] or EEG [electroencephalography, a test that measures brain waves with sensors attached to various areas of the scalp]), Morten’s work allows me to go deeper, providing a universal template of possibilities. This is directly analogous to the “harmonic maps” which arise within musical styles. These are not particular chord progressions, but a logical chord “tendency” map. They exist for standard jazz, tonal harmony and for particular composers/pieces. The transition model is analogous to having a harmonic (theoretical and/or instinctive) knowledge, a web of possibilities in order to create countless compositions.
It is ironic that the study of human neurologic function may have come full circle with these musical compositions. Early on, in the first decades of the twentieth century, when electrical activities of the nervous system were first discovered, researchers would listen to, as well as look to, signals from the brain, muscle, and nerves.(5,6) In the future we may do the same—but instead of simple sounds we may hear music, both beautiful and disturbing.
1 Chesterton, M. UK pollinating insect numbers, Tracking whales using barnacles, Sleep signals. BBC Inside Science podcast. 2019 Mar 28. https://www.bbc.co.uk/programmes/m0003jr9
2 Stevner ABA, Vidaurre D, Cabral J, Rapuano K, Nielsen SFV, Tagliazucchi E, Laufs H, Vuust P, Deco G, Woolrich MW, Van Someren E, Kringelbach ML. Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep. Nat Commun. 2019 Mar 4;10(1):1035. doi: 10.1038/s41467-019-08934-3.
3 Berry RB, Brooks R, Gamaldo C, Harding SM, Lloyd RM, Quan SF, Troester MT, Vaughn BV. AASM Scoring Manual Updates for 2017 (Version 2.4).J Clin Sleep Med. 2017;13(5):665-666. doi: 10.5664/jcsm.6576.
4 http://www.miltonline.com/soundasleep/. Accessed June 9, 2019.
5 https://imotions.com/blog/history-of-eeg. Accessed June 9, 2019.
6 Kazamel M, Province P, Alsharabati M, Oh S. History of Electromyography (EMG) and Nerve Conduction Studies (NCS): A Tribute to the Founding Fathers. Neurology. 2013;80 (7 Supplement):259
I wish to thank Dr. Innessa Donskoy for the text that started me thinking of this column,
Diane Larowska for sharing the podcast with me, and Drs. Morten Kringelbach and Milton Mermikides for being receptive and sharing with me the musical pieces.