Why do we dream?
  The expectation fulfilment theory of dreaming
sleep and dreams

How the expectation fulfilment theory of dreaming explains dream and sleep research findings

Let us take a look at the expectation fulfilment theory to see if it can explain the evidence that previous dream theories cannot explain.

The expectation fulfilment theory of dreaming is different from all others in that it is firmly based in biology and yet explains the richness of the subjective experience of dreams (something previous dream theories cannot explain). It states that: all arousals of the autonomic nervous system — the generation of an emotion, however slight — form half of a process. The second half is that the brain has to fulfil that expectation (an emotion is the same as an expectation) through an action of some kind. If that doesn't happen in reality during the daytime, it happens metaphorically in a dream at night, thus completing the arousal — de-arousal process.

Since the expectation fulfilment theory was first published in 1994, professors at various universities have looked it at and no evidence against has been put forward. Professor Hans Eysenck of the Institute of Psychiatry saw it at the very beginning and advised that it be published in book form, to do it justice. Many other people working in dream research have looked at it as well, and no flaws have been identified in the theory, to date.

Evidence for: Dream experiment

There is, however, a considerable amount of evidence in support of it. First is the experiment Joe Griffin carried out, the findings of which were published in The Therapist,[1] predecessor of the Human Givens Journal, and then in book form, in The Origin of Dreams,[2] and further updated in Dreaming Reality.[3] It was possibly the first time in scientific dream research that someone had set out to predict their own dreams with the hypothesis that dreams relate to emotional experiences of the day before, and this as a hypothesis has since been well validated. Dreams do involve waking emotional material.

Griffin set up an experiment using his own dreams, waking himself up every two hours, and, for a period of a week, predicted the emotional concerns that would feature in the dreams. He found that the dreams always reflected my waking emotional concerns of the previous day, but not necessarily the most important of these. By analysing the data, he was able to show that dreams dealt not with emotional concerns per se but with those emotional concerns that had not been dealt with satisfactorily.

No matter how important the emotional concern, if it got dealt with while awake, it was over and did not re-appear in a dream. The only emotional concerns that became dreams were those that he was still aroused about, for which he still had expectations that he couldn't complete.

Dreams are the fulfilment of those emotional expectations that have not been met prior to waking. They always act out the fulfilment in metaphor — ie a matching sensory pattern to the original expectation. For example, if a man feels like hitting his boss but restrains the impulse, that night he might dream of attacking another authority figure. The hypothesis was derived from a scientific experiment, which anyone can replicate, should they wish.

Evidence for: Dream analysis

A second piece of evidence arises from an analysis of Freud and Jung's specimen dreams, which they had offered as the best convincing evidence for their theories.[20] The analysis revealed that the dreams were perfect metaphorical manifestations of what was worrying them the day before, according to detailed written data they had themselves provided.

This was structurally extremely tight-fitting data. Freud's dream of Irma's injection and the expectations he had the previous day, the sequencing of the dream, the characters involved and what they actually did in the dream provided an exact mirror image of the biggest event he had on his mind before he went to bed that night. There is no ambiguity there. It was likewise for Jung's dream.

Furthermore, hundreds of other dreams for which we had the emotional data from waking have been analysed, and have validated the theory. Thousands of people have read the theory and many of them have contacted us with confirmation of their own.

Evidence for: Meets Domhoff’s three requirements

In addition, the expectation fulfilment theory explains the developmental evidence that Domhoff wanted explained — that dreams are coherent (because they are metaphorical representations of uncompleted emotional expectations) and become more complex over time from childhood (as our introspective processes become more complex and develop). Indeed, it even goes further and explains how REM function in the fetus relates to REM function in adulthood in dreams — the pattern-matching templates are programmed in during REM sleep, as a fetus and in early life, and the same pattern-matching process is used in dreams to deactivate emotional arousal.

It is also consistent with Domhoff's requirement for "a forebrain network for dream generation"[4] (ie the uncompleted emotional expectations). And that is "most frequently triggered by brainstem activation" — the PGO startle response serves to alert the cortex to something happening and, as the brain is getting no information from the outside world at this point, it has to release from memory its current unfulfilled expectations, as its best guess as to what the 'something happening' might be.

The theory explains the consistency of dreams and the relationship to waking emotional concerns, so it meets Domhoff's criteria in that respect too. It explains the depression evidence, which none of the other theories does. (Depressed people have proportionally too much REM sleep because they continually worry and introspect, causing so much arousal needing to be discharged in dreams that they end up exhausted in the morning, instead of refreshed after sleep.[5]) It provides the first scientific explanation for hypnosis (showing that the REM state and the state known as hypnosis are one and the same). It is the only REM theory in the field to go beyond itself in this way and, indeed, a good theory ought to be able to do that, to enlarge our understanding by explaining other things not currently explained.

The functions of REM sleep

So what, then, are the functions of REM sleep? There are three.

First, it switches off emotional expectation and thereby reducing the stress of managing increasing numbers of expectations that are no longer applicable to the current environment.

Second, it creates spare storage capacity in the cortex. If we look back to a primitive mammal such as the echidna (the spiny anteater), we see that, from one perspective, it has the most amazing brain on earth. It has the biggest cortex of any creature alive, for the amount of its body-weight. It doesn't have REM sleep. That is evidence to suggest that, if a creature doesn't have REM sleep, maybe it needs to have a massive cortex instead because, if unfulfilled expectations are not cleared out each night, a brain is going to need the ability to grow an ever bigger catalogue of expectations that it is still seeking to fulfil. So, by clearing in dreams each night expectations that haven't been acted out, there can be more spare capacity in the cortex.

Third, REM sleep has the function of preserving the integrity of our emotional templates. Up till now, we have never really said much about how this happens. We have said that somehow REM sleep removes impediments by acting out the unfulfilled expectations, but we haven't been specific about what is actually going on in the brain. And that is what I would like to do now to carry the expectation fulfilment theory forward to show that it is consistent with the very latest neurological findings and ideas about how the brain works.

Evidence for: Neurological findings about how intelligence systems work.

Evolutionary psychology had postulated that brains, and in particular the human brain, must contain particular modules in the cortex that give us various types of intelligence. Hundreds, perhaps even thousands of these modules are in there, written from the genes in the cortex, telling us how to do all the things we might have to do — for instance, how to choose a mate, how to calculate whether there is reciprocity in a partnership, when to have sex, what tastes good, how to recognise the faces of the people we know, when to get sexually jealous and how to read other people's minds. Hundreds of little intelligence systems within the brain were postulated to explain how human beings can be so intelligent.[6]

What we've learned from bees

That view has been strongly challenged from two separate sources. The new theory is that the brain has what is termed an adaptive intelligence.[7] It starts off with some basic instincts but these instincts are modifiable, as a result of experience, and the brain can continually refine its learnings.

Of course, this is similar to the terms in which we have been talking for the last ten years in the human givens approach — patterns being programmed into the brain in the REM state, during gestation and very early childhood, which humans seek to complete in the environment after birth, allowing our brains to be more flexible. All learnings, we have said, are about pattern refinement — and that, in effect, is what is contained in the latest scientific theory, which has been shown to be capable of explaining complex human behaviour.

The first evidence for this came from research findings that the honeybee has a neural transmitter called octopamine, which is similar to dopamine, our own motivation neurochemical. One single cell, using this neurochemical, motivates the bee to go out every morning to search for nectar (instinctive behaviour) and then that cell keeps a record of where the nectar is found.

The next time the bee goes out, it predicts, on the basis of that record, where it will get nectar today. So if the bee got nectar from a blue flower yesterday, it will pattern match and go to a blue flower today, predicting and expecting that it will get nectar there again. If it doesn't get nectar from the blue flower today, it immediately revises its memory store. So the memory store will now show that blue is not such a good predictor of nectar after all. Clearly, then, the bee has an instinct plus a capability for learning; it takes an instinctive pattern, builds on current information and modifies it, literally, on the wing.[8]

That is also what was postulated by computer scientists trying to model how the brain works. Their computer program succeeded in modelling complex bee foraging behaviour, and many other kinds of more complex behaviours, using this simple idea that you start with an instinctive core that can be modified through feedback from previous efforts.[9] It is a far more efficient system for acquiring knowledge than the one suggested in the module theory. If we had masses of modules in the brain, all occupying their own areas, the brain should be pretty well fixed, and that is exactly what the evolutionary psychologists thought was so.

Their idea was that those modules had evolved over the two million years that we were Stone Age hunter-gatherers and that, as all of our knowledge would go back to those times, we are ill-fitted for the world we live in today — a very fatalistic view of human nature. But the new information allows us to be more optimistic about human capacity. Even bees can learn. Behaviour has been shown to be so very much more malleable than anyone had ever suspected.

The sight cells that read Braille

The second source of evidence is neurological, and became available to us once brain scans were developed that could show exactly what was happening inside the skull cap when people learn new things. For example, it is now clear that, when people are born blind, the brain cells that would have been used to generate sight learn to read Braille instead.[10] So neurons are incredibly adaptive. They can take on new tasks.

It is now well known, for example, that the hippocampal area in taxi drivers' brains grows new cells and expands, when they do 'the knowledge' — the huge number of street maps they must plot out, learn and keep in their heads. It has also been shown that we can teach even autistic children some of the basics for empathy, despite their initial marked lack of emotional understanding.[11]

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dreaming reality

For the full story of Griffin's
ground-breaking research, the resulting insights and applications, as well as all references, see: Dreaming Reality:
How dreaming keeps us sane,
or can drive us mad

The text on this page comes from an article called "Dreaming to forget: the real reason why" first published in 2005 in the Human Givens Journal

Read the full article here >













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1]. Griffin, J (1993). The meaning of dreams: a scientific solution to an ancient mystery. The Therapist, 1, 3, 33—38.

2]. Griffin, J (1997). The Origin of Dreams. The Therapist Ltd.

3]. Griffin, J and Tyrrell, I (2004). Dreaming Reality: how dreaming keeps us sane or can drive us mad. HG Publishing, East Sussex.

4]. Domhoff, G W (2000). Needed: a new theory. Behavioural and Brain
Sciences, 23, 6, 928—930.

5]. Berger, M, Lund, R et al (1983). REM latency in neurotic and
endogenous depression and the cholinergic REM induction test.
Psychiatry Research, 10, 113—123.

6]. Tooby, J and Cosmides, L. Evolutionary psychology: a primer.

7]. Quartz, S and Sejnowski, T (2002). Liars, Lovers and Heroes: what the new brain science reveals about how we become who we are. HarperCollins, New York.

8]. Hammer, M and Menzel, R (1995). Learning and memory in the
honeybee. Journal of Neuroscience, 15, 1617—1630.

9]. Montague, P, Dayan, P et al (1995). Bee foraging in uncertain
environments using predictive Hebbian learning. Nature, 377, 725—728.

10]. Robertson, I (1999). Mind Sculpture: unleashing your brain's potential.
Bantam Books.

11]. Austin, A (2003). Good choices: autism and the human givens.
Human Givens, 10, 2, 19—23.







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© Copyright Joe Griffin and Human Givens Publishing Ltd. 2007