The Brain as a Trickster
By: Mirela C. C. Ramacciotti
You’re probably familiar with the saying: “Our minds play tricks on us.” If we take this to mean tricks like the ones a magician’s bound to play, there seems to be more reason today to believe that the mind—and its puppet master, the brain—is indeed a trickster. It can turn reality into illusions and makes us believe that illusions are reality. Let me show you an example. It’s an anecdote about how reality is constructed.
As a researcher, I’m part of a few research groups and in one of them, dedicated to language teaching, multilingualism and neuroscience, the messaging app is a very much used tool. In one of the messages, a Master’s candidate showed all her devastation at being absent from a fellow candidate’s examination. She had even driven to the university to attend the event in person, just to learn that it had already happened—two hours before. She seemed inconsolable because she realized that her brain had read the information she wanted instead of what her fellow candidate had actually posted on the app.
Now, let me break it down so that you can understand the trick and the trickster here. First, her Master’s exam was scheduled for the following week and she assumed that both events—being defenses—would happen at the same time. This is the information she wanted to read. It is a plausible assumption and offers a way to save precious cognitive resources of attention that, in her case, were much in need. However, to her dismay, the events were not at the same time, and this prediction error was a blow to her sensitive nerves. Second, being in the countdown for her own defense exam left her with fewer resources for the kind of attention that confers the precision signal needed to process a message—especially in busy feeds—to analyze its implications which, in her case, meant rescheduling her daily activities to accommodate the commitment made.
So, let’s line up facts to infer meaning. In the anecdote, the message posted by the fellow Master’s candidate about his defense was an event she wanted to go to. To that end, she reserved time in her busy schedule to be there. She did not attend to the timing because she assumed it would be the same as that of her own defense—to happen a few hours later. As our brains are masters in saving resources for precious metabolic needs, her brain diverted resources to the actions needed—attending the event that was going to happen—leaving her with few cognitive resources to process information by comparing and contrasting it with the knowledge she already had about defense timings. Thus, by relying on her previously generated model based on the timing of her own Master’s defenses at their university, she glossed over the details because she did not attend to them. Of course, this was all unconsciously done, but it was done and produced results. The brain does play some tricks behind the scenes. However, as in a magic show, the result is usually positive. In the following lines, you will see why.
This article is based on how illusions and reality are created and what the brain does when processing information and allocating attention. The backdrop is the theme of the current issue: Predictive Processing. The setting is our brain and on stage is our attention. By the end, I hope to have offered you a concise, informative, and interesting account of how the brain manages attention for learning to take place.
Predictive Processing—PP, for short—is one of many ways, with slight differences, to name a recent theoretical framework. It explains what the brain does to make sense of the signals (internal or external) it receives. The trickster (the brain) is indeed constructing reality the whole time, as it attempts to find the best explanation of the causes of the signals (or stimuli) we get all the time. This is heavy work.
To minimize the burden, the brain generates models that let it make a coherent whole out of the input we get. In a way, we are trying to minimize the chaos that living means. The models are formed by sets of predictions that change over time according to the different experiences we get. In a sense, they are how our brains store and structure the knowledge about the world we live in so that we can live better. Rest assured that most of it lies within the unconscious. But it explains the fact that the brain accounts for 20% of the metabolic intake that we process daily.
Back to the PP framework, the brain generates predictions just like a scientist generates hypotheses. And instead of running experiments in a laboratory, the brain tests the hypotheses generated in a process—which is an active construction—called perception. When what gets perceived matches the hypothesis, bingo! The model generated is a good fit for the data we get. This means that the brain can keep the model for other uses. When this happens, probabilities for the predictions made yield above-chance results. Again like the scientist, our brains are computing probabilities the whole time—the trickster is indeed knowledgeable.
However, when the hypothesis does not get confirmed, we know that a prediction error has occurred. In fact, such errors can be taken as a mismatch signal between what was predicted and what was experienced. That is good because it shows that the brain is not operating in a box, i.e., isolated from context. Errors mean that there is something to be learned. And, much as each experiment is unique but may be reproduced if the elements are gathered and programmed with fidelity to yield best results, each experience renders a chance to reproduce the model with a correction—thanks to the prediction error—to update our sense-making of the world. That also accounts for how learning is truly an individual trajectory; each one of us is able to make predictions. These will depart from distinct genetic starting points—as, for example, some people are more anxious about timings while others take a more laid-back attitude—but our unique experiences confer on us different opportunities to create and update our internal models so that we can learn and live better.
In the above anecdote, the prediction error occurred when my colleague unconsciously misread the time information of her peer’s Master’s defense, glossing over relevant data. This most probably happened because her brain was operating on the model of “all Master’s defenses are scheduled in the same time slot,” which was a best guess given the circumstances she was in. Because the brain is programmed to use resources optimally, that is, allocating resources to where they are most needed, errors are important signals. They show the brain that some adjustment to the generated model is needed so that resources are not misspent over and over again.
Back to the anecdote, I bet that the next time she schedules a slot to attend a peer’s defense, this instance will be remembered and used wisely to update her model about the timing of defenses—as in “defenses may be scheduled at different times”—so that predictions are made to save her time and spare her from anxiety. In a nutshell, she has created a prior to guide her perception of important events that merit her attention, like a friend’s defense exam. Priors, or best guesses, work to optimize inferences, channeling attention to what is most relevant, meaningful, and worthy of our consideration.
Now is the time to talk about optimization as it has relevance to our main topic here: attention. When we optimize something, the focus is on the process. In other words, it is the “how” instead of the “what.” This is what happens when we attend to something: we optimize how we process input that may be useful to construct our internal model about the cause of certain things. Attention, then, is how we process things, never the “thing” itself. Therefore, if by paying attention to something we process it optimally, attention is what gives precision to our inferences. By allocating attention to what we deem relevant, we make our internal models more precise and save up precious energy for other processes.
Let’s now reconstruct the initial anecdote using all the vocabulary that was in bold to test your attention. Our central character did not pay attention to the relevant timing of the defense because she predicted that it would be at the same as hers. Her internal model for defenses vouched for such a prior in her perception of that external input. However, by not paying attention, she encountered an imprecision. Because her attentional resources were compromised with her own upcoming defense, the attention she would have given to the timing of her peer’s defense was not there to issue the precision signal to update her internal model. That was a crucial difference for the necessary revision in her model of defense timings. Thus, she unconsciously made a prediction error. As she realized her error and felt poorly about it, her generated model, upon learning from this experience, now allows her to optimize her predictions to encompass different timings for defense sessions.
Now, if you have read the paragraph above in a smooth swoop, you have understood PP and attention. Congrats, your trickster is in shipshape!
If you want to know more in a light mode:
- The Nuffield Centre for Clinical Neuroscience. (2019). The Bayesian brain. Available at [link]
- Psyched! (2023). Predictive coding: Why our brain is constantly predicting the future. (05:26). https://www.youtube.com/watch?v=5eSxcygk8UM
- PBS. (2023). Your brain: Perception deception. Full Documentary. NOVA.. (53:32). https://www.youtube.com/watch?v=HU6LfXNeQM4
Or do some heavy-lifting:
- Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press.
- Feldman, H., & Friston, K. J. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4, 215.
- Friston, K. J. (2019). Waves of prediction. PLoS Biology, 17(10), e300042. https://doi.org/10.1371/journal.pbio.3000426
Mirela C. C. Ramacciotti is presently engaged as an external lecturer on the topic of Mind, Brain, and Education at the Graduate Level Course with the Psychology Department at the University of São Paulo. She holds a PhD in Neuroscience and Behavior and another in Human Communication Disorders.