A Healthy Human Mind Has Elements of Chaos

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On Oct. 13, 1987, meteorologists in England forecasted that the next couple of days would be slightly breezy [1,2]. Nothing in the maps of the atmospheric pressure they studied looked alarming. Two days later, the worst storm to hit Britain in 300 years made landfall in Cornwall. The gusts reached 120 mph. Seventeen people died.

As Oxford Professor Tim Palmer suggested [1,2], if you were to take these Oct. 13 weather maps and run a computer simulation on them, the difference between the map that results in a storm and the one that leads to normal weather is nearly undetectable, even to the trained eye of a meteorologist.

Weather is a chaotic system [2]. This means two things: (a) a tiny difference in the initial state of a system leads to exponentially large differences with time, and (b) that is why you cannot make accurate long-term predictions [3]. Armed with the latest and greatest artificial intelligence (AI), running on the most powerful computers in the world, using the latest scientific models of the weather available, no one can accurately predict the temperature in Washington, D.C., a year from now [1,2].

Chaotic systems are not identical to random (stochastic) ones. A coin toss is an example of a random system. There is zero predictability in the value of the next coin toss. There is no pattern of any kind in the consecutive results of coin tosses. With chaotic systems, however, we have some short-term predictability, but in the long term, predictability disappears exactly because the systems are exponentially divergent [9].

What does this have to do with mental health? As you read these words, if you measure the electrical activity of your brain with an electroencephalogram (EEG), you will see a chaotic picture [3]. The waves on the EEG will show frequencies from 35 Hz to about 100 Hz (35 to 100 cycles per second), and you would not do very well if you tried to predict the shapes of the future waves. As you go off to sleep in the evening, your EEG waves will become somewhat more predictable. They will look reasonably orderly when you are in deep sleep.

If we look at pathology, the EEG will show more predictability in the wave patterns during an epileptic seizure than in healthy functioning [10]. In that sense, a seizure brings order. So does coma [8]. If you measure the EEG of patients in a persistent vegetative state (PVS), the higher levels of chaoticity correlate with a higher probability of recovery—the more chaos, the better the prognosis [5]. In contrast, the EEG wave patterns will be perfectly predictable when we die—a flat line doesn’t change.

I need to balance the argument, as the text above may suggest an oversimplified conclusion that chaos is health while order is disease. A more accurate statement is that our brains and minds operate in different regimes, and changing from one regime to another can be considered a “phase transition.” An illustration of a phase transition is water at 212°F. Boiling makes water turbulent, which is a chaotic process. Freezing makes the water more orderly. In neuroscience, as in physics, the level of chaoticity tends to increase with the level of energy, which in the brain we refer to as “generalized arousal” [3].

Then, a phase transition in the brain can result in a state with too little chaoticity or too much chaoticity, both of which can be associated with states we consider pathological [9]. Just enough chaoticity, however, could be entirely normal. An example of a pathological state with too much chaoticity is mania, while a pathological state with too little chaoticity is a seizure [9].

As you can see, there is indeed a space for chaos in a healthy and normal brain. This is not news. Walter J. Freeman suggested this in the 1970s [6]. Unfortunately, you are unlikely to hear his name mentioned to students in the graduate programs in clinical psychology or psychiatry.

Chaos theory is not just a set of abstract concepts. It has practical applications in clinical work. In neurology, a computer program based on chaos theory can detect a seizure on an EEG with an accuracy comparable to that of a human epileptologist [6].

Unlike other clinical fields, mainstream clinical psychology and psychiatry continue to operate in a mode where health is associated with order. The authors of the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III), which was released in 1980, insisted on calling mental health conditions "disorders," and the term has been in use ever since. Repeated ubiquitously and taught to generations of psychiatrists and psychologists, this term contributes to the stability of a belief that health is orderly.

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I think that this terminology creates a bias against chaoticity and stochasticity (both can be described as degrees of disorder). Then, our diagnostic processes and therapeutic approaches are based on evaluating how far the patient is from order and how to restore order. This does not correlate with the empirical data on how the brains and minds function in health and pathology [3].

Consider the differential diagnosis process, for example. What you’ll see resembles an algorithm of classification. We have various buckets (categories), including discrete ones, such as major depressive disorder, and continuous ones, such as autism spectrum disorder. The patient presents to a clinician a nuanced, complex tapestry of psychological challenges that are dynamic in nature, context-dependent, and often transient [11].

What DSM and other diagnostic systems suggest we do is carefully pick several buckets from the book that "match" the patient's symptoms and level of functioning. You can’t put a chaotic process into buckets. It doesn't work. You would be more accurate by using other scientific methods to describe such dynamic processes [3].

In physics and philosophy, the term for systems that have long-term predictability is “deterministic.” I think mainstream clinical psychology and psychiatry have been deterministic for the past 100 years. Perhaps Sigmund Freud was one of the powerful theorists who contributed to this state of affairs. He made the principle of “psychic determinism” a cornerstone of psychoanalysis [3]. This was quite normal in the late 1800s and early 1900s. Freud was the child of his time, and the zeitgeist in Europe during that period was indeed deterministic.

Determinism dominated physics in the early 1800s. In 1814, Pierre-Simon Laplace introduced the idea of a demon, which, if it knew the position and momentum of every particle in the universe, could predict the future exactly. Physics started moving away from determinism with Ludwig Boltzmann in 1877. By the 1920s, when quantum mechanics theory was born, strict determinism had become a historical artifact.

We know now that we don’t live in a universe ruled by Laplace’s demon. The future, after all, is unknown. While physics moved on, psychology and psychiatry remained deterministic.

The models of the mind in health and pathology we use today lean toward determinism heavily, and this applies to nearly all schools of psychotherapy and psychiatry.

Freeman's pioneering work on chaos theory in neuroscience and psychology has been continued by his colleagues in the Society for Chaos Theory in Psychology and Life Sciences. In addition, Karl Friston and his colleagues made contributions to this field. What I think we can do in clinical psychology is consider catching up with neurology, cardiology, and other clinical fields that already use chaos theory extensively.

We can translate these ideas into updated models of the brain and mind in health and pathology, and then we can update our diagnostic processes and therapeutic models [3].