Note: The following are excerpts from The Neuroscience of You by Chantel Prat, PhD.
Passages marked 'MV' are my comments for context, clarity, or readability.
For a surprising—but fun—example of how our experiences shape the way we understand the world, let’s go back to the Dress. As it turns out, at least part of the reason some people see the Dress as white and gold, while others see it as blue and black, can be traced back to differences in our experiences. In fact, the whole process of seeing color likely involves much more interpretation than you think. This might surprise you if you learned that the colors we see correspond to specific wavelengths of light. You may even have learned that typical color vision includes three different types of receptors (or cones) located in the back of the eye that respond preferentially to long, medium, or short wavelengths of light. This seems like a straightforward way for figuring out what color something is without connecting any dots. How can the color of something be open for interpretation? Fortunately, the way we understand what color something is, is not that simple. If it were, we all might be able to agree on the color of the Dress, but we would also agree that a green apple turns red at sunset and bluish in a shadow. Because the fact is, as the nature of the light that bounces off an object changes, so do the wavelengths that reach our brains through our eyes. Thankfully, one of the things our brains learn from experience is that the properties of the light bouncing off an object are more likely to change than the color of an object itself. And so, to adjust for different lighting situations, it uses a shortcut: It takes a survey of all of the wavelengths in a particular context and uses the differences between them—rather than their absolute value—to figure out what color something might be.
What makes the picture of the Dress tricky for your brain to interpret is that there isn’t a lot of context in the picture to gauge what kind of lighting is bouncing off of it. Under this circumstance, people’s brains make different assumptions, automatically, about what the light is like in the picture. Those of you who see a white-and-gold dress do so because your brain assumes, based on your lifetime of experiences with light sources, that light is coming from behind, and that the dress is in a shadow. To “fix” this, it automatically subtracts out the dark blue and black hues and leaves you seeing white and gold. Others, like me, who see the Dress as blue and black, assume that it is well lit from the front or top, possibly through some source of artificial lighting, and so we make no such subtraction.
So what kind of life experiences might shape our assumptions about lighting? Writer and vision researcher Pascal Wallisch tested one interesting hypothesis by exploring whether people who tend to wake up early in the morning (the “larks”) would see the Dress differently from those who wake up late and stay up late (the “owls”). His assumption was that larks would have more experience with natural lighting, and thus would be more likely to assume the dress was in a shadow and see it as white and gold. On the other hand, owls, who spend more time awake after dark, would have more experience with artificial lighting and would be more likely to see the Dress as black and blue. To test his hypothesis, he asked 13,000 people what color they thought the Dress was, and what their normal sleeping habits were. When he did, he found a small but reliable effect that was consistent with his intuition. The larks were more likely to see the Dress as white and gold, while owls were more likely to see it as blue and black!
MV: In her explanation, Prat uses the words 'horse' and 'rider' to represent the two types of control in the brain.
The way you navigate through your life's decisions is undoubtedly made up of some percentage of the horse's decision-making and some percentage of the rider's more controlled driving.
From your horse’s perspective, these brain functions are a means to an end. To put it simply, your horse learns to pay attention to features of its environment that are associated with good or bad outcomes while at the same time learning to ignore things that have no effect on their decision space. Learning to distinguish the sounds of a language you don’t speak, for instance, is unlikely to be useful. But learning the difference between “ba” and “pa” in native English-speakers might empower you to request a “banana”—a real and delicious food—instead of a “panana,” which isn’t a thing. But to learn which features of the environment are important to consider when deciding what to do next, your brain needs a way to link the environment it’s in, and the choice it makes, to the consequences of that choice.
This process, called reinforcement learning, is one of the strongest influences on your horselike navigation systems. To move you through life in a way that maximizes your rewards, your brain engages in the following four-step procedure:
First, it uses the database of your previous experiences to build the most accurate representation it can of the important features of the world around you. When bombarded with information on a busy street, for instance, doing a quick assessment of whether a person walking toward you is holding a tool or a weapon will motivate different actions on your part, while noticing what type of shoes they are wearing may be less consequential.Second, based on your previous experiences in similar environments, your brain builds a representation of the repertoire of possible actions you might take. For example, you could smile and say hello to the person approaching you or engage in some other positive interaction. You might choose to remain neutral or pretend you don’t see them. You could also avoid the person by walking (or running) in the other direction. Of course, there are any number of other actions available, from belting out “Halo” by Beyoncé to deciding to sit on the corner and sketch the scene. Whether your brain considers these actions has a lot to do with your previous experiences in similar contexts. Third, based on what you’ve learned from your previous actions, your horse brain navigates the path it believes will bring you the most success by deciding which of the potential actions you can take is most likely to have a good outcome. Then fourth, your brain compares the actual outcome of this choice with the outcome it expected, and updates its database on the relative “goodness” of that choice accordingly.
Of course, many of the lessons we learned about how different brain designs influence the way we understand the world apply to this decision space. For example, whichever aspect(s) of the environment capture your attention will be weighed most heavily in your brain’s decision about what to do next. And perhaps most critically for the discussion at hand, people with different life experiences will have different estimates of how good the outcomes of any of these actions may be. For instance, if you are a bad singer, or even a good one who embarrasses easily, singing “Halo” in public may move to the bottom of the list. But when you don’t have much experience with a particular situation, your brain starts to explore the possible actions through trial and error, to learn how good (or bad or ugly) the results may be.
On a busy street, you might try out a smile. If the response is good, and not creepy, your brain will take note, increasing the likelihood that you will choose that option again in a similar circumstance in the future. But the kinds of notes it takes depends on the fourth and final stage of reinforcement learning. Because very few things in life are certain, and we rarely find ourselves in exactly the same situation twice, your brain learns by comparing how good what actually happened was to what you expected to happen based on your previous experiences. If the outcome is better than you expected it to be, your brain releases dopamine, the feel-good chemical. And as you may remember from “Mixology,” that creates the learning signal that causes it to rewire, increasing the likelihood that you will choose that action again in a similar situation in the future. But if the result was worse than expected, your dopamine neurons would dip below their baseline firing rates, which would leave you feeling disappointed and weaken the connections to that action.
As your brain fine-tunes its expectations about the outcomes of your actions, it builds something like a playbook with information about the best and worst actions you can take in any given context. And it uses this playbook, largely automatically, to guide your basic decisions about what to do when. From your first decision in the morning, like whether to press Snooze on your alarm to the words you choose to use when expressing yourself, your brain’s four-step reinforcement-learning process makes it feel effortless to choose the most rewarding actions based on your previous experiences. And the process works wonderfully. In fact, reinforcement learning alone drives the decisions of most living, behaving creatures as well as most of the successful artificially intelligent systems we’ve built.
Much like physical threats, such as the risk of receiving a shock, might shut down our willingness to explore, your brain must also be motivated to protect itself from psychological threats. If this is true, maintaining your most central, identity-based beliefs must be one of the goals your prefrontal cortex would use to guide your behaviors. The power of this kind of belief structure is that rather than driving you to explore, or collect statistics and form an objective opinion about what might be true of the world “out there,” such top-down navigation strategies would cause your basal ganglia to turn up the volume only on “relevant” information—that is, information that is consistent with your identity-based beliefs—while turning down the volume on any information deemed “irrelevant” because it doesn’t support your worldview. In a recent opinion paper, Jay Van Bavel and Andrea Pereira outlined how such a brain-based model might be used to describe the relation between personal values, political beliefs, and partisan behaviors. Whether you’re willing to believe it or not, we all do this. It keeps us feeling safe, and protected, and correct. Psychologists who study how we form and hold beliefs have long known that when people are surprised by information that is inconsistent with what they believe to be true, they don’t often behave rationally. Instead, they ignore or even discredit evidence that is inconsistent with their beliefs—a phenomenon known as a confirmation bias. The important take-away from this is that the possibility of encountering a piece of information that is inconsistent with your centrally held beliefs may be perceived as a threat during the appraisal phase. The result would be to shut down the cycle of wondering—and wandering—that brings us to explore the unknown. With this in mind, in the next chapter, I will walk you through one of the most vulnerability-inducing explorations of the unknown that any of us can ever undertake—our attempt to see through the bubbles created by our own brains to connect with another person, whose views of the world may not align with our own.