Chapter 2 — Why We Dream, and Why No One Yet Knows

Here is a question that ought to have an answer by now, and does not.

You spend roughly a third of your life asleep. A sizable fraction of that — a fifth to a quarter of it in adulthood, and something close to half of it in infancy, as we saw — is given over to the vivid, metabolically expensive, physiologically elaborate business of REM sleep and the dreaming that rides inside it. Your brain does not conserve energy during a dream; parts of it run as hot as waking. Evolution installed a dedicated brainstem mechanism to paralyze your body so the dreaming could proceed safely. None of this is cheap, and none of it is optional. It is one of the largest, most reliable, most conserved behaviors in the animal kingdom.

And we do not know what it is for.

I want to sit with how strange that is before I do anything else, because it is easy to assume that a phenomenon this universal and this well-studied must, by now, have yielded up its purpose. It has not. There is no consensus answer to the question why do we dream — not a shy, technical lack of consensus about details, but a genuine, open, live disagreement among serious scientists about the fundamental function of one of the most basic things brains do. There are several strong theories. They are not obviously compatible. The evidence does not clearly pick a winner. And a respectable minority position holds that the dream experience itself may have no function at all.

This chapter is a fair map of that disagreement, and I need to change registers to draw it. The previous chapter lived on the empirical floor — measured, standardized, agreed upon. This one moves up into the second of my three levels, the theoretical: the domain of what we reasonably infer but have not nailed down. Almost everything in this chapter is inference. I will mark the places where a theory rests on something genuinely measured, because those anchors matter, but the theories themselves are exactly that — theories, held with varying confidence, defended by intelligent people, unresolved. I will not crown one of them for you and pretend the matter is closed. The honest state of the science is plural, and I would rather hand you the real argument than a tidy falsehood.

I should also tell you, before we start, that part of why this question stays open is methodological — dreams are private, remembered badly, and close to impossible to study cleanly, which is a large enough problem that it gets its own chapter next. For now, just hold the consequence: because the dream is so hard to observe directly, the theories about it are underdetermined by the evidence. That is the soil in which so many rival explanations grow.

Let me walk you through the serious contenders.

The old quarrel: meaning versus noise

Every modern theory of dreaming is, in part, a reaction to a quarrel that has run for more than a century — the quarrel between those who think dreams mean something and those who think they are, at bottom, noise the brain tidies up.

The meaning camp begins, unavoidably, with Freud. The Interpretation of Dreams proposed that dreams are disguised wish-fulfillments — that beneath the odd surface story, the manifest content, lies a hidden latent content, a censored expression of repressed desire, which the work of interpretation could decode. Whatever you make of the specifics, and most contemporary scientists make very little of them, Freud's core wager was that dreams are psychologically meaningful, continuous with your emotional life, and worth reading. I mention him not to relitigate psychoanalysis but because the wager itself — dreams are meaningful — never fully went away, and several respectable modern theories are, in effect, careful attempts to rescue that intuition from the parts of Freud that could not survive contact with evidence. The trouble with the strong Freudian version is not that it is obviously false but that it is close to unfalsifiable: a theory that can interpret any dream as a disguised wish, and any counterexample as a deeper disguise, has slipped free of the discipline that would let evidence bear on it at all.

The reaction came, most influentially, in 1977, when J. Allan Hobson and Robert McCarley proposed the activation-synthesis hypothesis and turned the whole picture upside down. Their claim, grounded in the brainstem neurophysiology of REM, was roughly this: during REM, the brainstem fires off bursts of more-or-less random signals; the higher brain, receiving this internally generated storm, does what it always does with input — it tries to make a story out of it. The bizarreness of dreams, on this view, is not disguised meaning. It is the cortex improvising a narrative over essentially chaotic activation — synthesis imposed on noise. The dream feels meaningful because your meaning-making machinery cannot help but run; but the meaning is manufactured after the fact, not encoded in advance. It was a deliberate, deflationary answer to Freud: not a secret message, but the mind's narrative reflex firing over random sparks.

I want to be fair to both, because the quarrel was never as clean as its slogans. Hobson himself spent the following decades softening the "random" part and building something larger and stranger out of it. In his later protoconsciousness theory, REM dreaming is not mere noise-processing but a kind of virtual-reality generator — a state in which the brain, especially the developing brain, runs a built-in world-simulation, rehearsing the very capacity for conscious experience it will need when awake. That is a long way from "random sparks," and it points, as you will see, straight at the theory this book leans on most. The historical dialectic — meaning versus noise — did not end with a winner. It matured into a subtler question: not is the dream meaningful or random, but what is the brain accomplishing by generating an internal world at all? Nearly every theory that follows is a different answer to that better question.

The consolidation account: the night sorts what the day gathered

The theory with the strongest empirical anchor is the one that connects sleep to memory — and I want to be careful and exact here, because this is a case where solid measured findings shade into a more contested claim about dreams specifically, and the two are easy to blur.

Start with what is genuinely well-established, and therefore empirical: sleep helps memory. This is not seriously in doubt. Across a large and replicated literature, learning something and then sleeping consolidates it better than learning it and staying awake. Different stages appear to serve different kinds of memory — the deep slow-wave sleep of early night is heavily implicated in the consolidation of declarative, fact-like memory, while REM has been linked to procedural skills and emotional memory. And there is a beautiful, direct neural finding underneath it: in 1994, Matthew Wilson and Bruce McNaughton recorded the "place cells" of a rat's hippocampus — neurons that fire when the animal is in a particular spot — as the rat ran a maze, and then watched those same cells replay their firing sequences during subsequent sleep, as though the animal were mentally re-running the route in miniature. This hippocampal replay has been confirmed many times over. The sleeping brain demonstrably reactivates and reorganizes the traces of waking experience. That much is measured fact.

Now the leap, which is theoretical: does the dream — the felt, first-person experience — do the consolidating? Or is dreaming merely a byproduct, the subjective flicker thrown off by consolidation machinery that would run just as well with the lights of experience switched off? Here the ground gets softer. There is a suggestive bridge finding: Robert Stickgold and colleagues had people play the video game Tetris and found that many reported hypnagogic images of falling, rotating blocks as they fell asleep — including, strikingly, people with dense amnesia who could not consciously remember having played the game at all. The imagery of a recent, heavily practiced experience surfaced into the sleeping mind even when the episodic memory of it did not. That looks like the memory system's overnight work becoming briefly visible as dream content. But "visible" is not the same as "responsible." The consolidation theory of dreaming, in its strong form, claims the dreaming is the sorting; in its weak form, it claims only that the dreaming reflects the sorting. The evidence supports the weak form comfortably. The strong form remains a reasonable inference, not a settled result.

There is a companion idea worth naming, because it reframes what "sorting" even means. Giulio Tononi and Chiara Cirelli's synaptic homeostasis hypothesis proposes that the core job of sleep, especially slow-wave sleep, is not to strengthen memories but to renormalize them — to scale down the synaptic connections that grew all day during learning, pruning the whole network back toward a sustainable baseline so it does not saturate. On this view the night is less an archivist than a groundskeeper, cutting back the overgrowth so tomorrow has room to learn. It is a theory about sleep more than about dreams, but it changes the flavor of the consolidation story: perhaps the night's work is as much forgetting as remembering — deciding what to let go.

Overnight therapy: the night defuses what the day charged

A close relative of the memory account narrows the focus from information to feeling, and it has produced some of the most humanly resonant claims in the field.

The idea, developed by Rosalind Cartwright over decades of studying the dreams of people going through hard passages — divorces, depressions — and sharpened more recently by Matthew Walker and colleagues, is that REM dreaming performs a kind of overnight emotional processing. The proposal, which Walker has called "overnight therapy," is roughly this: during REM, the brain re-runs the emotional experiences of the day, but does so in a particular neurochemical environment — one notably low in the stress-related chemistry of waking. Replaying a painful memory in that calmer chemistry may allow the brain to keep the memory while stripping off some of its emotional charge — to remember what happened without being made to feel it as sharply the next time it comes to mind. Sleep to remember the event; dream to forget the sting. There is supporting evidence that a night's sleep with REM reduces the next day's emotional reactivity to disturbing material, measured both in how people rate it and in how strongly the amygdala responds.

I find this the most emotionally believable of the theories, which is precisely why I want to flag the caution. It fits our intuition that things look better in the morning, that grief loosens in the dark, that sleep is where we process. But intuitive fit is a warning as much as a recommendation — a theory we badly want to be true deserves extra scrutiny, not less. The evidence for a genuine emotional-regulation role for REM is real and growing; the specific "overnight therapy" mechanism is a well-motivated interpretation of it, not a closed case. Its best negative evidence, tellingly, comes from where it seems to fail: in post-traumatic stress disorder, the recurring nightmare re-runs the trauma without ever defusing it, the emotional charge reasserting itself night after night — which some read as the overnight-therapy process broken, and others read as evidence that the whole framing is too clean. Both readings are alive. That is the state of it.

Threat simulation: the dream as a flight rehearsal

Now a theory with a different logic altogether — not about processing the past but about rehearsing the future, and grounded frankly in evolution.

Antti Revonsuo proposed, around the turn of the millennium, the threat simulation theory of dreaming. Its starting observation is one you can check against your own dream life: dream content is disproportionately negative and threatening. We dream of being chased, of falling, of danger, of losing people, of being unprepared and exposed, far more than a neutral sampling of daily life would predict. Revonsuo's proposal is that this bias is not a bug but the whole point. Dreaming, on this account, is an evolved simulation of threatening situations — a safe, offline arena in which the ancestral brain could rehearse detecting and escaping danger, over and over, without physical risk. The organism that spent its nights running virtual drills against predators and rivals woke better prepared to survive real ones, and so the trait was selected. The dream is a flight simulator, and evolution installed it for the same reason we build flight simulators: because practicing the emergency in advance, where crashing costs nothing, makes you better at the real thing.

Revonsuo and colleagues later extended the idea to a social simulation theory — that dreams also rehearse the complex social interactions that so dominate human life, our nightly practice at reading, bonding with, and navigating other minds. Together these frame dreaming as rehearsal: the offline practicing of the situations that matter most, threat and belonging.

I flag this theory with particular interest because it is the one that most directly foreshadows the argument this whole book is building toward — the idea of the brain as a simulator running scenarios, of imagination as the offline rehearsal of possible lives. Threat simulation is that idea in its oldest, most survival-bound form. Its weakness is the usual one for evolutionary-function claims: it explains the negative bias of dreams elegantly but has a harder time with everything else we dream — the tedious, the neutral, the joyful, the surreal — and evolutionary rehearsal stories are notoriously easy to tell and hard to test. It is a strong, motivating, partial account. Hold onto its central image, though. The simulator rehearsing what has not yet happened is coming back, transformed, in the last part of this book.

The predictive brain: dreaming as the model running on its own

Now the theory this book will lean on most — and I owe you complete honesty about that leaning, so let me be blunt: I am about to give this one more space and more sympathy than the others, and that is an authorial choice, not a scientific verdict. I lean on it not because it has won but because it is the most generative frame for the questions I most want to ask, the one that connects the dreaming brain to the waking imagination and to the artificial minds we will meet in Part II. That it fits my purposes is a reason to be more suspicious of my own enthusiasm, not less, and I will try to keep the theory's uncertainty visible even as I build on it. Treat this whole section as clearly marked theoretical, with a thumb, honestly disclosed, on the scale.

The frame is called predictive processing, and its most radical version comes from Karl Friston's free-energy principle, elaborated into a broad picture of the mind by thinkers like Andy Clark, Jakob Hohwy, and Anil Seth. Here is the core reversal it asks of you. We tend to imagine perception as a bottom-up affair: the senses deliver the world, and the brain reads it off. Predictive processing inverts the arrow. On this account the brain is fundamentally a prediction machine — it is always, at every level, generating a model of what it expects the world to be, and comparing that top-down prediction against the incoming sensory signal. What actually flows up through the system is not the raw world but the error — the mismatch between prediction and input, the part the model got wrong. Perception, in this picture, is the brain's best-guess model, continuously corrected by error. Anil Seth's memorable phrase for it is controlled hallucination: waking perception is a hallucination — a generated model — that happens to be controlled, reined in and corrected by a steady stream of sensory data.

Now watch what happens to that model when you fall asleep and the sensory stream is cut off. The generative machinery does not shut down. But the leash — the incoming error signal that keeps the model tethered to the actual world — goes slack. The brain keeps generating. It keeps producing a model of a world. Only now there is no sensory correction reeling it back toward reality, so the model drifts, recombines, invents, follows its own internal logic wherever the associations lead. On this view, a dream is the generative model running with the controller unplugged — the same world-building the brain does every waking moment, now uncoupled from the senses and free to hallucinate without constraint. Waking perception is controlled hallucination; dreaming is the hallucination with the controls released. This is why the deflationary "random noise" of activation-synthesis and the meaning-laden intuitions of the Freudians can, oddly, be partly reconciled here: the content is internally generated, yes, but it is generated by the very machinery you use to model reality, so it is saturated with your real associations, memories, fears, and expectations. Not random. Not disguised messages. The reality-model, running free.

Why would a brain want to do this? Here the predictive frame offers a purpose, and a recent version of it makes a connection I have to flag as leaning toward my third register, the speculative, because it borrows a metaphor straight from artificial intelligence — a metaphor Part II will take up in earnest. In 2021 the neuroscientist Erik Hoel proposed the overfitted brain hypothesis. It runs like this. In machine learning, a model trained too tightly on its data overfits — it memorizes the training set so exactly that it fails to generalize, cracking the moment it meets anything new. The standard fix is to corrupt the training on purpose: inject noise, distort inputs, feed the system deliberately weird and warped versions of what it has seen, so it is forced to learn the general shape rather than the specific instances. Hoel's suggestion is that dreams are the brain's version of this. A brain that spent all day learning from its actual, statistically narrow experience risks overfitting to that experience — becoming too tuned to yesterday to handle tomorrow. So each night it generates strange, warped, hallucinated variations on its life — the bizarreness of dreams not as noise and not as message but as deliberate corruption, a nightly regime of weird inputs that keeps the mind's model general, flexible, ready for the genuinely new. The dream is dropout for the brain. The very oddness we have puzzled over for millennia might be the functional point.

I love this idea, which is once again the reason to distrust my love of it. It is recent, it is contested, and its central move — read the brain through the lens of the learning machine — is exactly the move this book will spend its middle chapters interrogating rather than assuming. I offer the overfitted-brain hypothesis here not as a result but as a marker of where the predictive frame is heading and why it excites me: it makes the strangeness of dreams useful, and it does so by treating the brain as the kind of thing that can overfit — a prediction engine, a generative model, a system that has to work to keep from getting stuck. Whether that lens illuminates or merely seduces is a question I am holding open, and will keep holding open, all the way to the frontier.

The continuity view: the dream is daytime imagination, off its leash

One more serious theory, and it is the one that reaches out of Part I and takes the rest of this book by the hand.

G. William Domhoff, drawing on decades of empirical dream-content research and on David Foulkes's remarkable studies of how dreaming develops in children, has argued for a neurocognitive and continuity theory of dreams. Its claim is deflating in the best way: dreaming is not a special, sealed-off mode of mind with its own exotic purpose. It is what your ordinary imaginative machinery does when it runs unconstrained. Domhoff points to the fact that dreaming, in children, does not arrive fully formed but matures alongside their waking cognitive and imaginative abilities — young children's dreams are sparse and static, and grow richer and more narrative only as the child's waking capacity for visual imagination and storytelling grows. Dreaming, on this view, rides on the same neural systems as waking mind-wandering — the so-called default mode network, the circuitry that lights up when your attention drifts inward and you fall into reverie, replaying the past and rehearsing the future. A dream is a daydream that has slipped its last constraints — the same faculty, more fully released.

I have saved this one for the hinge position deliberately, because it is the theory on which the second half of this book quietly depends. If Domhoff and the continuity theorists are even partly right — if the machinery of the dream and the machinery of waking imagination are one continuous system — then the study of dreaming is not a detour into a curious nocturnal specialty. It is a way in to the study of imagination itself: the planning, the longing, the rehearsal, the possible selves, the imagined life. The dream would be imagination with the training wheels of reality removed, and everything we could learn about the one would bear on the other. That is a large if, and I am marking it clearly as an if. But it is the if that makes this a book about the imagined life rather than merely a book about sleep.

The honest skeptic: perhaps it is for nothing

I promised you a fair map, and a fair map has to include the position that unsettles all the others: that the dream experience may have no function at all.

The philosopher Owen Flanagan put it most memorably by calling dreams the spandrels of sleep. A spandrel, in the original architectural sense Stephen Jay Gould borrowed for biology, is the space left over between two arches — a byproduct of the structural design, not something built for its own purpose, however much later decoration it acquires. Flanagan's suggestion is that dreaming might be exactly that: sleep does real and vital work — restoration, consolidation, renormalization, all the measured functions — and the dream, the vivid first-person experience that accompanies some of that work, might simply be a side effect of a brain that cannot do its nightly business without, incidentally, generating experience. The experience would be real, sometimes even useful once we have it, meaningful to us in the way we make anything meaningful — but not itself selected for, not there because it does a job. Sleep is the arch. The dream is the pretty space between.

I include this not as a concession but because it is genuinely a live and honest position, and because it enforces a distinction the other theories can blur: the difference between sleep having a function (which is beyond serious doubt) and the dream experience having a function (which is not settled at all). It is entirely possible that everything measured and marvelous about the sleeping brain is doing essential work, and that the felt dream is, functionally speaking, foam on the wave. A book that skipped this possibility to make its own project sound more important would be exactly the kind of book I promised, on the first page, not to write.

No privileged theory

So where does this leave us? With an argument, and I am not going to resolve it for you, because it is not resolved.

Look back at what we have. Consolidation says the dream reflects the sorting of memory. Overnight therapy says it defuses emotion. Threat simulation says it rehearses danger. Predictive processing says it is the reality-model running free. Continuity says it is waking imagination unleashed. Activation-synthesis says it is narrative imposed on internal activation. And the spandrel view says it may be for nothing at all. Notice something important about that list: these theories are not all competing for the same prize. Some are theories about sleep; some about REM; some about the dream experience specifically. Some could all be true at once — the night could consolidate memory and renormalize synapses and regulate emotion and generate a model that happens to rehearse threats, with the dream experience arising somewhere in the middle of all of it. The theories overlap, cut across each other, and answer subtly different questions. The disagreement is real, but it is not always a disagreement about the same thing.

What there is not, is a privileged theory — one the evidence has singled out, one a working scientist could point to and say this is the answer and the rest are refuted. There are strong theories, better-supported and worse-supported ones, more and less fashionable ones. There is no winner. I have told you that I will lean, going forward, on the predictive-processing and continuity frames — not because they have won but because they are the most useful roads into the country this book actually wants to explore, and I have tried to make that leaning visible rather than smuggle it past you as consensus. When I build on them in later chapters, I am building on an interpretation I find generative, not on a settled fact. You are entitled to hold the alternatives in your other hand the whole way.

And here, finally, is the thought that lets us move forward honestly — the bridge I promised, and the door into the next chapter. Notice what every one of these theories is quietly doing. Each one takes an enormous, private, only-partly-observable phenomenon and offers a simplified account of it — a story compact enough to state, to test in fragments, to reason with. Consolidation compresses the dream into an act of sorting. Threat simulation compresses it into rehearsal. The predictive frame compresses it into a model minimizing its own error. Each theory is a kind of lossy summary of a system too large and too hidden to capture whole. That is not a failing peculiar to dream science; it is what theories are. But it lands with special force here, because the object of study is so nearly closed to us.

All of our current theories of dreaming, in the end, are partial compressions of a system we cannot fully observe.

I want you to hear that sentence in two ways, because it does double duty. Heard one way, it is a confession of the field's limits — an honest admission that we are squinting at something mostly hidden and offering our best compressed guesses. But heard another way, it is a clue, and a strange one. Because compression — the reduction of a vast, high-dimensional reality to a compact model that captures its essential structure — is not a poetic word I reached for by accident. It is a technical idea. It is precisely what certain machines now do, and precisely what a growing school of neuroscience thinks the brain itself is doing all the time. To say our theories of the dream are compressions of an unobservable system is to notice that the brain may be doing the very same thing to the world — compressing an unobservable reality into a workable internal model. And the moment you frame it that way, the study of dreaming stops being a branch of sleep medicine and becomes something else: a question about computation, about inference, about how any system — wet or dry, born or built — manufactures a usable world out of incomplete information.

That is the turn the next chapter takes. We have stood on the empirical floor and surveyed the theoretical argument, and found the argument unresolved but pointing, all of it, toward a single reframing. The science of dreaming, pressed hard enough on the question of why, starts to become a science of modeling — and that is where the brain begins to look, to modern eyes, like an inference machine running in the dark. We are about to walk to the edge of the known.

Part II

The Edge of the Known

Where science becomes inference — the first bridge to AI