This is how your brain makes your mind

A second ingredient of your experience is sense data from events inside your body, like the blood rushing through your veins and arteries, your lungs expanding and contracting, and your stomach gurgling. Much of this symphony is silent and outside your awareness, thank goodness. If you could feel every inner tug and rumble directly, you’d never pay attention to anything outside your skin. 

Finally, a third ingredient is past experience. Without this, the sense data around and inside you would be meaningless noise. It would be like being bombarded by the sounds of a language that you don’t speak, so you can’t even tell where one word ends and the next begins. Your brain uses what you’ve seen, done, and learned in the past to explain sense data in the present, plan your next action, and predict what’s coming next. This all happens automatically and invisibly, faster than you can snap your fingers. 

These three ingredients might not be the whole story, and there may be other routes to create other kinds of minds—say, in a futuristic machine. But a human mind is constructed by a brain in constant conversation, moment by unique moment, with a body and the outside world.


When your brain remembers, it re-creates bits and pieces of the past and seamlessly combines them. We call this process “remembering,” but it’s really assembling. In fact, your brain may construct the same memory (or, more accurately, what you experience as the same memory) in different ways each time. I’m not speaking here of the conscious experience of remembering something, like recalling your best friend’s face or yesterday’s dinner. I’m speaking of the automatic, unconscious process of looking at an object or a word and instantly knowing what it is.

Every act of recognition is a construction. You don’t see with your eyes; you see with your brain. Likewise for all your other senses. Your brain compares the sense data coming in now with things you’ve sensed before in a similar situation where you had a similar goal. These comparisons incorporate all your senses at once, because your brain constructs all sensations at once and represents them as grand patterns of neural activity that enable you to experience and understand the world around you. 

Brains also have an amazing capacity to combine pieces of the past in novel ways. They don’t merely reinstate old content; they generate new content. For example, you can recognize things you’ve never encountered before, like a picture of a horse with feathery wings. You’ve probably never seen Pegasus in real life, but like the ancient Greeks, you can view a painting of Pegasus for the first time and instantly comprehend what it is, because—miraculously—your brain can assemble familiar ideas like “horse” and “bird” and “flight” into a coherent mental image.

Your brain can even impose on a familiar object new functions that are not part of the object’s physical nature. Look at the photograph in Figure 1. Computers today can use machine learning to easily classify this object as a feather. But that’s not what human brains do. If you find this object on the ground in the woods, then sure, it’s a feather. But to an author in the 18th century, it’s a pen. To a warrior of the Cheyenne tribe, it’s a symbol of honor. To a child pretending to be a secret agent, it’s a handy fake mustache. Your brain classifies objects not solely on the basis of their physical attributes, but also according to their function—how the object is used. It goes through this process every time you look at a slip of paper with a dead leader’s face on it and see currency that can be exchanged for material goods.

Figure 1. Human brains can categorize this object by how it will be used. Computers using machine learning will only see a feather.

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This incredible ability is called ad hoc category construction. In a flash, your brain employs past experience to construct a category such as “symbols of honor,” with that feather as a member. Category membership is based not on physical similarities but on functional ones—how you’d use the object in a specific situation. Such categories are called abstract. A computer cannot “recognize” a feather as a reward for bravery because that information isn’t in the feather. It’s an abstract category constructed in the perceiver’s brain.

Computers can’t do this. Not yet, anyway. They can assign objects to preexisting categories based on previous examples (a process called supervised machine learning), and they can cluster objects into new categories based on predefined features, usually physical ones (unsupervised machine learning). But machines don’t construct abstract categories like “facial hair for pretend spies” on the fly. And they certainly don’t do it many times per second to comprehend and act in a massively complex social world.


Just as your memory is a construction, so are your senses. Everything you see, hear, smell, taste, and feel is the result of some combination of stuff outside and inside your head. When you see a dandelion, for example, it has features like a long stem, yellow petals, and a soft, squishy texture. These features are reflected in the sense data streaming in. Other features are more abstract, like whether the dandelion is a flower to be placed in a bouquet or a weed to be ripped from the ground. 

Brains also have to decide which sense data is relevant and which is not, separating signal from noise. Economists and other scientists call this decision the problem of “value.”

Value itself is another abstract, constructed feature. It’s not intrinsic to the sense data emanating from the world, so it’s not detectable in the world. Value is a property of that information in relation to the state of the organism that’s doing the sensing—you. The importance of value is best seen in an ecological context. Suppose you are an animal roaming the forest and you see a blurry shape in the distance. Does it have value for you as food, or can you ignore it? Is it worth spending energy to pursue it? The answer depends partly on the state of your body: if you’re not hungry, the blurry shape has less value. It also depends on whether your brain predicts that the shape wants to eat you. 

Many humans don’t hunt for food on a regular basis, apart from browsing in markets. But the same process of estimating value applies to everything you do in life. Is the person approaching you friend or foe? Is that new movie worth seeing? Should you work an extra hour or go bar-hopping with your friends, or maybe just get some sleep? Each alternative is a plan for action, and each plan is itself an estimation of value. 

The same brain circuitry involved in estimating value also gives us our most basic sense of feeling, which you know as your mood and which scientists call affect. Affective feelings are simple: feeling pleasant, feeling unpleasant, feeling worked up, feeling calm. Affective feelings are not emotions. (Emotions are more complex category constructions.) Affect is just a quick summary of your brain’s beliefs about the metabolic state of your body, like a barometer reading of sorts. People trust their affect to indicate whether something is relevant to them or not—that is, whether the thing has value or not. For example, if you feel that this article is absolutely brilliant, or that the author is off her rocker, or even if you’ve spent the energy to read this far, then it has value for you.


Brains evolved to control bodies. Over evolutionary time, many animals evolved larger bodies with complex internal systems that needed coordination and control. A brain is sort of like a command center to integrate and coordinate those systems. It shuttles necessary resources like water, salt, glucose, and oxygen where and when they are needed. This regulation is called allostasis; it involves anticipating the body’s needs and attempting to meet them before they arise. If your brain does its job well, then through allostasis, the systems of your body get what they need most of the time.