REBUS

The REBUS Model

Understanding Psychedelics- What’s the model?

Andy Meijer has a strong fascination for the breadth and variety of consciousness experienced by humans. To explore this, he obtained his BA in Psychobiology at the University of Amsterdam, after which he did a pre-master to do his MSc in Clinical Neuropsychology at Leiden University. Working with psychotic patients during his internship and afterwards volunteering in a Hospice, he further developed his passions; understanding and spreading evidence-based knowledge about the therapeutic potential of altered states of consciousness, exploring what it means to be conscious, and awareness of the finality of said consciousness.

Edited by
Patrick Wentorp
Lucca Jaeckel

Published February 2020

Photo by Robina Weermeijer on Unsplash

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“Maybe psilocybin will work at least as well, that’s my prediction,” Carhart-Harris says. “But imagine that psilocybin is more effective? That’s really quite…” he trails off. “That would be something.” – Carhart-Harris on a comparative study of psilocybin and an anti-depressant.

Our understanding of the brain, specifically in regards to the field of neurobiology, has evolved rapidly since the development of imaging techniques such as PET, MEG, and perhaps most notably (f)MRI. On the basis of recent results gained and ideas coined with help from these techniques the conception of our brain as an interpreting machine has gradually shifted to a view in which it is seen more as a prediction machine. The theoretical framework for this is called predictive coding1 (Saga Briggs wrote a MIND blog post about it2). Predictive coding can be seen as the recently leading paradigm by which the brain is currently understood and studied, as it is able to explain many perceptual curiosities3 and aspects of experience and behaviour. Another hot topic within neurobiology, especially those parts of it related to psychotherapy and psychiatry, is of course the second wave of psychedelic research a.k.a. the psychedelic renaissance4. With a growing scientific base and FDA-‘breakthrough therapy’ status already being designated to specific treatment models in the United States, it seems to be just a matter of time before psychedelic therapy will be incorporated as one of psychiatrists’ or psychotherapists’ tools. Until recently, however, no venture had been made to integrate the impressive results obtained by psychedelic research with predictive coding. In other words, we lacked an overarching theoretical model explaining the effects of psychedelic therapy on the brain, beyond the level of structures and receptors.

REBUS & the Anarchic Brain

Robin Carhart-Harris and Karl Friston, two leading neuroscientists from England, have attempted to formulate such an overarching model, integrating their own theories of the entropic brain5 and the free-energy principle6 within the framework of predictive coding1. They name this model: RElaxed Beliefs Under pSychedelics & the anarchic brain, or REBUS in short7. This blog post will start by outlining the main theoretical underpinnings of this model and connect these concepts in order to give an explanation of the REBUS model that enables us to formulate some critical views and thoughts.

The Building Blocks

Hierarchical Predictive Coding

It was stated in the introduction that our view of the brain is shifting, namely from interpreter to predictor “machines”. Machine analogies – particularly computer analogies – are often used by scientists when they speak of parts of the body, to visualise function. Although brains are clearly not “machines”, particularly not trivial machines, even for something as complex as the brain the analogy makes heuristic sense since neurons, simply put, are ‘on’ or ‘off’. Machines are usually based upon mathematics, so how does one translate the biology of the brain into such an abstract language? In other words: what does it mean to “methodically” see the brain as a prediction machine? The more we learn about the brain, the more we realise that our perceived reality is constructed from estimation and error, based on input3. Predictive coding is exactly that; as we get older, we become more familiar with the way the world works and we gain more relative certainty that specific events have specific results which are consistent over time and repeatable. After years of ‘data-gathering’ and model formation, our brain constantly generates explanatory models about expected input, predicting the causes and origins of our surroundings and experiences and testing this against actual input. These models, of which the higher-order ones we may call our “worldviews” or “beliefs”, are updated in a Bayesian8 manner depending on the measure of our surprise when something unexpected occurs. In mathematical models of brain activity, surprise is conceptualized as prediction error, i.e. the difference between what the brain predicted to happen and the incoming sensory information. The hierarchical aspect is that this prediction process is happening at multiple ‘levels’ of brain organisation simultaneously. During model formation and testing at the different cortical levels the higher level, or top-down9, beliefs or predictions can influence our, bottom-up9, perceptions and explain away or rationalise part of the experienced surprise a.k.a. prediction error. What is of importance here is that existing models have a certain ‘weight’, which could be rephrased as its strength or certainty. The larger the weight of the belief, the more likely it will be able to explain away any surprise. As an example, most people are familiar with the ‘chair-with-clothes’ effect: in your dark bedroom, for a split second, your chair looks like a person standing in the room. This visage instantly reverts back to just a chair with clothing on it. This instant flip is hierarchical predictive coding at work, or your higher-order cortex telling your perceptual system it must be wrong, since the door was locked. The incoming prediction-error is explained away, updating your perception with existing knowledge of what is in that specific location.

Free-Energy Principle

Friston expanded the theory of predictive coding by hypothesising that any given organism will try to reduce the amount of uncertainty or surprise, herein called free-energy, it experiences throughout life6. Since a biological organism can change the input it receives through acting on its environment, it is possible to avoid states in which it would experience such uncertainty or surprise. Said uncertainty could force the organism to change its models about the world; to avoid this could be preferable, as updating models is usually an energetically costly and uncomfortable undertaking. In other words, when applied to humans; a person can limit her- or himself to an environment which is most congruent with beliefs held about the world to avoid states of large surprise (or, to relate back to predictive coding, prediction-error). Note that this limiting can be external, but also internal e.g. changing the narrative.

Entropic brain hypothesis

Carhart-Harris, based on data from his research with psilocybin, proposed a theory of how different states of consciousness relate to each other. Specifically, he proposed that the experienced quality or information richness of subjective experience is directly related to the measure of entropy in the brain5 (Steven Osborne wrote a MIND blog post10). Put simply, entropy here means the measure of random activity or disorder. Applied to the brain, one ought to mention that it shows synchronous activity of brain cells but of course also random or asynchronous activity. Following this basic notion of synchrony and asynchrony, the measure of brain entropy is the amount in which the activity of cells in the brain is unpredictable a.k.a. how much random or spontaneous activity there is. In short, Carhart-Harris’s entropic brain hypothesis states that rigid states of consciousness such as depression and obsessive-compulsive disorder (in which thought loops and rumination occur) are on one end of the spectrum of brain entropy, exhibiting a low measure of entropy, whereas vibrant states of consciousness such as early psychosis and the psychedelic drug state are on the other end of the spectrum, thus, showing a high level of brain entropy. As an example: to be able to think of a new plan or strategy when presented with an unknown problem requires some creative thinking to be able to think outside of your normal frame of reference. When you would be completely lacking entropy, it would be hard to have an original thought beyond what already existed to solve the new problem. However, on the other end of the spectrum with a maximally entropic brain, there would be no cohesion of thought and it would be impossible to constructively act on all the creative and bizarre ideas floating around your mind since your brain would be thusly disorganized. Carhart-Harris’s hypothesis is that the adult human brain normally pushes down its measure of entropy, away from a point known as criticality11, into sub-criticality. Therein, criticality can be seen as the ‘perfect balance’ between order and disorder in the brain; exactly between the two examples just given. Simultaneously, he demonstrates psychedelics have the potential to push the brain from sub-criticality into a state closer to actual criticality using data obtained from participants in psilocybin trials5,11,12.

Recap

To summarize, hierarchical predictive coding explains how higher-order beliefs can, depending on their ‘weight’, modulate or constrain the interpretation of sensory data. Moreover, according to the free-energy principle, organisms aim to minimize their subjective uncertainty and for this they may act upon their environment to further minimize their free-energy a.k.a. exposure to uncertainty during their lifetime. Lastly, Carhart-Harris’s entropic brain hypothesis was mentioned which states that neuronal entropy is directly related to the ‘richness’ of subjective experience, and how psychedelics increase entropy.

Building with the Blocks

So, how does this all fit together? Carhart-Harris and Friston propose that a key neural mechanism to which psychedelic therapy owes its therapeutic effect is a weakening of the higher-order beliefs held by a person4. By increasing entropy and thereby stimulating creative thought, entrenched patterns of thought become weakened as the brain is able to communicate more freely within itself, letting more information ‘flow upstream’. Therein, the free-energy principle is temporarily broken down; people are able to break free from their energy-efficient world-view. Through this, one’s world-view can be reweighted to find a new optimum from which to operate instead of being limited to an overly rigid predictive model. Imagine the following: a person experiences a violent traumatic event during their youth. The belief ‘people are inherently good’ gets destroyed; so large was the surprise. The years thereafter it is the belief ‘people usually have bad intentions’ that becomes the guiding principle of this person. Throughout the years, this belief strengthens more and more, as anything falsifying this thought is explained away (another large world-view shift has gotten too demanding) and often enough it is confirmed. At 45, the person notices that it is hard to get close to people and build up relationships since the belief has become so entrenched it has become blocking. Upon realising this the person tries to work on it but since it is related to a childhood event and years of ‘practice’, this proves difficult. In this example, the aforementioned concepts come forward. To explicate them: the hierarchical predictive coding model describes the updating of beliefs after the traumatic event. The years after, the free-energy principle is at work, taking away uncertainty about who is ‘good’ and who is ‘bad’ to employ a (short-term) energy efficient strategy, namely categorizing everyone as bad. Over time, back to predictive coding, this belief becomes stronger and even starts to explain away positive things that people who the person cares about do. Now what? Now, psychedelic therapy comes into play. By its proposed action on higher order belief systems and general rigidity of mind, our person is able to ‘take a step back’ and observe this belief and its underpinnings from a distanced perspective; from an altered state of consciousness. In its weakened state, the belief is able to be updated or, better said, to be ‘re-weighted’. It is as if the fingers of an overprotective parent are pried loose because fears have been assuaged. The belief has been relaxed, under psychedelics, granting opportunity for other beliefs to be considered, more importantly: for other perceptual information to enter consciousness, without the strict compression and control of the debilitating belief. As an anecdotal example, patient reports are nice to take a look at. After treatment with psilocybin, during one of Carhart-Harris’s own studies, one person said12:

“I felt so much lighter, like something had been released, it was an emotional purging, the weight and anxiety and depression had been lifted.”

Note the description of the ‘release’, and coincidentally the ‘weight’. When seen in light of REBUS, this corresponds quite well to the weakened weighting of a limiting belief.

A Critical Review

Intuitively, the model certainly seems compelling. However, it is still young and thus it will remain to be seen if it will stand the test of empirical science. I intentionally use the term ‘intuitively’, since the model itself entails quite a bit more neurobiological argumentation whilst the links between the biological constructs and the mind are in some degree speculative. The arguments have a slight tendency to rest a bit upon how it ‘would make sense’ to work instead of concrete scientific evidence. Moreover, since REBUS is set up as a global and unified model for brain function and mental states, its claim to explain all changes and phenomena which occur in personalities and psychiatry is quite bold – and overly general. This is something to be appreciated, though, as the model is the first of its kind and meant to serve a specific scientific purpose which invites attempts at falsification.

The model recognizes the fact that the link between large scale cognitive/heuristic changes (e.g. personality changes, changes in political views) must have some biological underpinnings but that these have not been elucidated so far. This fact in itself perhaps shows that the model is a starting point and not yet an exhaustive model for what exactly happens in the brain related to the mind, both from an experiential and simultaneously from a neurobiological point.

It remains to be seen what merits the model will have for guiding research and practice. It is certainly exciting to see leading neurobiological theories being used to explain possible mechanisms of psychedelic therapy. An ever increasing amount of scientific evidence suggests that psychedelics may be effective instruments which, if properly applied in a controlled therapeutic setting, can help treat numerous psychopathologies and facilitate personal development. A unifying model that can structure and inform the avenues of scientific inquiry is therefore a valuable asset in the current academic climate. With REBUS being the first of such unifying models, and having only been out a few months, the reaction of other leading neurobiological research centres is something to look forward to. How will a theoretical model support or advance psychotherapists who have to work with individuals who suffer from very distinct (and not just general) problems? Is there value in this model for understanding oneself through this model, for self-knowledge? If we apply this framework to broader society, what are the implications?

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References

1.   Huang, Y., & Rao, R.P.N. (2011). Predictive Coding. Wiley Interdisciplinary Reviews: Cognitive Science 2, 580-593.

2.   Briggs, S. (2018). How Predictive Coding Is Changing Our Understanding of the Brain. MIND Foundation Blog.

3.   Hohwy, J., Roepstorff, A., Friston, K. (2008). Predictive Coding Explains Binocular Rivalry: An Epistemological Review. Cognition 108, 687-701.

4.   Pollan, M. (2018). How to Change Your Mind. The New Science of Psychedelics. Penguin Press.

5.   Carhart-Harris, R.L, Leech, R., Hellyer, P.J., Shanahan, M., Feilding, A., Tagliazucchi, E., Chialvo, D.R., Nutt, D. (2014). The Entropic Brain: A Theory of Conscious States Informed by Neuroimaging Research with Psychedelic Drugs. Frontiers in Human Neuroscience 8.

6.   Friston, K. (2010). The Free-Energy Principle: A Unified Brain Theory? Nature Reviews Neuroscience 11, 127–138.

7.   Carhart-Harris, R.L. & Friston, K.J. (2019). REBUS and the Anarchic Brain: Towards a Unified Model of the Brain Action of Psychedelics. Pharmacological Reviews 71, 316-344.

8.    Spiegelhalter, D. & Rice, K. (2009). Bayesian Statistics. Retrieved from: http://www.scholarpedia.org/article/Bayesian_statistics.

9.   OpenPsyc. (2015). Bottom-up vs. Top-down Processing. Retrieved from: http://openpsyc.blogspot.com/2014/06/bottom-up-vs-top-down-processing.html?m=0.

10.  Osborne, S. (2018). Entropy as More than Chaos in the Brain: Expanding Field, Expanding Minds. MIND Foundation Blog.

11.  Tagliazucchi, E., Carhart-Harris, R., Leech, R., Nutt, D., Chialvo, D.R. (2014). Enhanced Repertoire of Brain Dynamical States During the Psychedelic Experience. Human Brain Mapping 35, 5442-5456.

12.  Roseman, L., Demetriou, L., Wall, M.B., Nutt, D.J., Carhart-Harris, R.L. (2018). Increased Amygdala Responses to Emotional Faces After Psilocybin for Treatment-Resistant Depression. Neuropharmacology 142, 263-269.