Placebo Effects Explained

How the Brain Creates Placebo Effects

A placebo is a substance or treatment that has a positive effect on the body without influencing it as purported. When your doctor prescribes you "a powerful new sleeping pill," taking it will likely make you sleepy, even if what you're swallowing is really just a sugar pill. The pill itself doesn't do anything to induce sleep—it's all in your head. The only thing that has changed is your mental state. You believe that the pill treats insomnia, and hence it does.

Your expectation of what will happen has a real physiological effect—a placebo effect, whose purpose is to reduce the potentially high energy cost of a large prediction error. If the brain makes wrong predictions, this can be costly for the body. So when the body makes an allostatic effort to meet the mind's expectations, it may help to save energy.

This reasoning is based on a predictive processing model, also called the Bayesian brain theory, according to which the brain's job is to make predictions about sensory data, compare them to actual data, and estimate prediction errors to update its model of the world in a way that approximates Bayes' theorem in order to reduce future prediction errors. In the context of placebo hypoalgesia (placebos for pain reduction), this means that the brain predicts a pain stimulus, compares the prediction to incoming nociceptive signals, and estimates a prediction error to make better predictions in the future.

So it's not as simple as: knife cuts skin, skin nociceptors send pain signals to brain, brain creates pain experience. This would be a feed-forward process where the signals ascend linearly from lower to higher processing levels, that is, from the skin to the cortex. In reality, however, ascending processes (bottom-up error signaling) are highly integrated with descending processes (top-down prediction making). What we experience as pain is, in Bayesian terms, the posterior probability of a predicted pain, given a pain stimulus. In other words, pain a statistical combination of prior information (past experience plus current expectation) with incoming sensory data (the pain stimulus), approximating Bayes' law. This is why pain-reducing placebos work.

Your past experiences, including your personal history with doctors and treatments, are parameters of your internal model, and your current expectation is modulated by two factors: magnitude and precision. The greater (higher in magnitude) and the more certain (higher in precision) your expectation of an effect, the stronger a placebo will be. It will be strongest when you are fully convinced that the treatment will work and that its effect will be powerful.

Accordingly, a pill's attributes like size, shape, color, and price as well as a doctor's verbal and nonverbal portrayal of its effect can have a significant impact the magnitude of your expectation and thus on the potency of a placebo. Moreover, if you have consistently experienced a treatment yielding its desired effect, this will significantly impact the precision of your expectation and so, too, the placebo's potency.

References

Anchisi D, Zanon M (2015). A Bayesian Perspective on Sensory and Cognitive Integration in Pain Perception and Placebo Analgesia, PLoS ONE, 10(2): e0117270.

Büchel C, Geuter S, Sprenger C, Eippert F (2014). Placebo analgesia: a predictive coding perspective, Neuron, 81(6): 1223-1239.

Czerniak E, Biegon A, Ziv A, Karnieli-Miller O, Weiser M, Alon U, Citron A (2016). Manipulating the Placebo Response in Experimental Pain by Altering Doctor's Performance Style, Frontiers in Psychology, Vol. 7 (874).

Grahl A, Onat S, Büchel C (2018). The periaqueductal gray and Bayesian integration in placebo analgesia, eLife, 7: e32930.

Jung W-M, Lee Y-S, Wallraven C, Chae Y (2017). Bayesian prediction of placebo analgesia in an instrumental learning model, PLoS One, 12(2): e0172609.