Dreaming as a function of the
chaos in the self-organizing brain
David Kahn, Allan Combs, and Stanley
Krippner
This paper agues that REM state dream experiences
owe both their structure and meaning to chaotic self-organizing
properties of the brain during REM sleep. Several lines of evidence
support the notion that the REM dreaming brain can be understood
as a process system that exists near the edge of chaos, one highly
sensitive to internal influences. This sensitivity is due, first,
to the fact that the dreaming brain gates out external input,
thus operating without the stabilizing influences of waking feedback.
Second, the pre-frontal cortex in REM sleep is only minimally
activated, thus the brain operates with weakened volition, reduced
logic, and diminished self-reflection. Third, there is a reduction
of neuromodulatory inhibition during REM sleep, allowing the brain
to respond to minuet internal stimulation. Finally, the REM sleeping
brain is subject to powerful intermittent cholinergic PGO stimulation
that may initiate creative patterns of dream activity. Taken in
overview, this conception of dreaming offers a common meeting
ground for brain-based studies of dreaming and psychological dream
theory.
Key words: brain, consciousness, dream, chaos, self-organization,
REM sleep.
Dreaming is the brain doing its typical thing in the atypical
conditions of sleep.
David Foulkes (1999)
Introduction
Self-organizing dynamics are fundamental to processes at many
levels of the organic as well as the physical world, an idea shaped
by both empirical and theoretical research over the last thirty
years (e.g., Kauffman, 1993; Laszlo, 1987; Maturana, Varela, &
Uribe, 1974; Prigogine & Stengers, 1984). Recent work shows
the same self-organization in the brain (e.g., Freeman, 1991;
Kahn, & Hobson, 1993; Pribram, 1995; Varela, Thompson, &
Rosch, 1991), as well as in the process structure of human experience
itself (e.g., Combs, 1996; Combs & Krippner, 1998). This paper
discuses self-organizing dynamics in the brain with the intention
of understanding the REM dream experience alone and in relation
to waking consciousness.
The Self-Organizing Brain
One way think of the brain is to view it as a self-organizing
system comprised of self-organizing subsystems. First of all,
how could it be otherwise? Though the brain is usually modeled
in terms of neural networks and circuitry, this circuitry certainly
is not static. It changes frequently due to influences from neurological
development, daily learning, and encoded neuromodulations. In
addition, both single unit firing and mass activity is widespread
in the brain, implying that process itself is a feature of neural
functionality that rivals the importance of anatomy. The electrical
circuits in a house or a computer can endure extended periods
of inactivity without suffering loss of function. However, self-organizing
and self-creating (autopoietic) systems such as ecologies, weather,
and living organisms, are constantly in motion, just as is the
living brain.
The physiology of the brain reveals a wealth of process patterns,
which taken as a whole suggest that any final accounting of the
nature of brain activity will be made in terms of activities as
much or more than in terms of structures. Many if not most of
these activities seem fundamentally chaotic in form. For instance,
the EEG rhythm is roughly cyclic in appearance, and different
categories of activity, such as alpha, beta, theta, or delta,
can be recognized on visual inspection. On closer examination,
however, it becomes apparent that the actual waveform changes
from cycle to cycle. Indeed, it is unlikely that any cycle of
activity ever repeats itself exactly, and it is apparently impossible
to predict with precision the shape of a future EEG wave. This
situation of global familiarity combined with non-repetition and
unpredictability defines a chaotic process, one whose action describes
a strange attractor (Kellert, 1993). Such attractors appear to
be a common if not universal feature of complex self-organizing
systems such as living cells, ecologies, and evidently brains
as well (e.g., Abraham & Gilgen, 1994; Basar, 1990; Freeman,
1995; Hardy, 1997; Pribram, 1995; Robertson & Combs, 1995;
but also see Mandell & Selz, 1997).
Studies of the human EEG demonstrate a significant fractal structure,
(e.g., Basar, 1990; Screenivason, Pradhan, and Rapp, 1999), suggestive
of an underlying self-organizing process (Anderson & Mandell,
1996). The dimensionality of this structure appears to be higher
in REM than NREM sleep, indicating greater complexity and a larger
number of underlying influences, as would be expected if EEG activity
even in part reflects the complexity of accompanying dream experiences.
Anderson and Mandell (1996) have made detailed studies of the
temporal structure of REM state electrical activity in fetal rats.
They believe that such activity reflects self-organizing hierarchical
integrative processes in the developing nervous system. Interestingly,
there is a preliminary report which indicates that this integrative
process may follow an abnormal developmental pathway in the case
of autistic individuals (Tanguay et al., 1976).
That EEG activity exhibits fractal properties is consistent with
the self-evident fact that the brain can be understood as residing
in a condition of self-organized criticality (Bak, 1996). A system
can be said to be in as critical state if a small perturbation
sets it into fluctuation on all scales of length or time, that
is, if the response is fractal. A commonly cited example of a
critically poised system is a sand of pile ready to cascade into
an avalanche when a single additional grain is dropped onto it.
Bak points out that the brain is critically poised; otherwise
it would not respond globally to the small amount of energy contained
in a retinal image or a sound heard near the auditory threshold.
However, the brain unlike the sand pile is not a static structure.
It is an extremely complex dynamical process system, the product
of its own self-organizing tendencies. Thus it can rightly be
said to exhibit self-organized criticality. With regard to the
importance of self-organized criticality in biological systems,
Stewart Kauffman (1993) observed that “selection achieves
and maintains complex systems poised on the boundary or edge between
order and chaos. These systems are best able to coordinate complex
tasks and evolve in a complex environment” (p.xv).
Organized criticality in a chaotic system is just another way
of talking about the popularly termed butterfly effect, or “sensitive
dependence on initial conditions” originally discovered by
meteorologist Edward Lorenz (1963) while investigating models
of fluid convection (e.g., Kellert, 1993; Peak, 1994). Its relevance
here is that the smallest of influences active in the sleeping
brain might have sizable effects after just a few cycles of activity.
However, by its very nature the butterfly effect is unpredictable,
and while it might add to the spontaneous creativity-read randomness-of
the dream process, it does not help us understand how the brain
might respond in an ordered way to subtle internal stimuli such
as those discussed below. It is also helpful to understand activity
in the dreaming brain in terms of stochastic resonance. This is
a well known effect that has been studied in a variety of media,
ranging from electronic circuits to nerve cells (Moss and Wiesenfeld,
1995), by which vibration or noise keeps a system in motion and
on track, rather than allowing it to get caught in small groves
or “minima.” A simple example of stochastic resonance
is a cup that “walks” across the surface of an uneven
vibrating tabletop, following the course of least resistance from
higher to lower regions of the surface. The vibrations keep the
cup from getting stuck along the way because of friction and small
groves in the surface. Stochastic resonance can improve the effective
signal-to-noise ratio in a communication situation. In the brain
it may allow ongoing processes to “relax” into inherently
natural patterns of activity, an important point to which we will
return shortly.
Before doing so, let us consider the possibility that the brain’s
activity, like that of other extremely complex systems such as
the weather, can be understood as an exquisitely intricate strange
attractor, one exhibiting an intricate array of “wings”
or “compartments” (Goertzel, 1994). During wakefulness
the shape of this attractor, especially in the sensory cortices,
is powerfully constrained by sensory input, which itself is often
highly patterned (e.g., Gibson, 1966, 1979). Freeman and his colleagues
(Freeman, 1991, 1995; Freeman & Barrie, 1994) have mapped
such attractors in a variety of different sensory cortices. They
found that the sensory regions of the brain are critically poised
to respond robustly and in an ordered fashion to even the smallest
stimulation. In the REM state, however, such attractors are not
constrained by sensory input. In this state the self-organizing
dynamics of the brain are set into motion not by external stimulation
but by its own internal situation. Interestingly, it is possible
to find such self-organizational dynamics at work in the waking
state as well. Freeman, for instance, discovered that new learning
experiences actually modify previously established cortical activity
patterns. For example, a rabbit’s original cortical response
to an odor is altered when the odor is experienced in a new context,
such as a classical conditioning situation. Freeman interprets
such changes to signify that the meaning of the stimulus is as
important in the production of the brain’s response as the
physical structure of the stimulus itself. Speaking informally,
Freeman (1997) once observed that if one sees Hamlet, then sees
Rosencrantz and Guildenstern are Dead, returning to Hamlet one
finds it to be a different play.
The Dreaming Brain
Tononi, Edelman, and Sporns (1998; Tononi & Edelman 1998)
argue that the complexity of a living organism is not represented
by a fully integrated system, as exemplified by the structure
of a crystal, or by a differentiated and unconstrained system
such as seen in an ideal gas. Rather the complexity of a living
organism lies at an intermediate point where structural elements
are sufficiently undifferentiated to engage in “unplanned”
interactions, while at the same time sufficiently integrated to
allow many of the relationships between them to be stable. The
human brain, with its many interconnections and its many individual
elements, is an example of a complex self-organizing system within
a larger complex self-organizing system, the human body. It is
a system that is capable of moving between very many states. Thinking
is an example of a self-organizing action of the waking brain
(Combs, 1996), and dreaming is an example of a self-organizing
action of the sleeping brain, especially in REM sleep (Kahn and
Hobson, 1993; Kahn et al., 2000).
During REM sleep, brain activity is not constrained by external
stimulation as it is during waking. The brain is as active as
it is during waking, 4 but information processing is inwardly
oriented, occupied, for example, by memories and feelings, as
distinct from extroceptive input which dominates waking life.
In this state a number of factors combine to make it acutely reactive
to internally generated influences. Not only are the stabilizing
effects of external sensory input actively inhibited, but there
is a shift away from widespread aminergic neuromodulatory inhibition,
which dominates the waking brain, toward cholinergic modulation,
predisposing it to easy activation (Hobson, 1994, 1988). To be
more specific, during REM sleep norepinephrine and serotonin containing
neurons cease firing while acetycholine containing neurons fire
more actively. The loss of the aminergic neuromodulation (norepinephrine
and serotonin) is associated with a decrease in signal reliability
(Foote, Bloom, & Aston-Jones, 1983) and an increase in the
error rate of neuronal firing (Mamelak and Hobson, 1989). The
increase of cholinergic containing neurons is associated with
the initiation of the rapid eye movement (REM) generator (Hobson
and McCarley, 1977).
In addition to a changed neuromodulation, certain areas within
the dreaming brain are connected functionally in a different way
than in the waking brain, as recent PET studies have disclosed
(Braun, et al., 1997, 1998; Maquet, et al., 1996; Maquet, 2000).
Because the interconnectedness of the dreaming brain is different
from that of the waking brain, it self-organizes differently.
The brain has developed specific yet dynamically changing connections
between groups of neurons for specific tasks. Active connections
with and within the dorsal lateral prefrontal cortex (DLPFC) are
necessary for short-term memory, planning, and volitional actions.
For example, working memory for face recognition, and short-term
visual memory for objects and faces, has been shown to involve
the DLPFC in conjunction with areas in the ventral pathway in
the inferotemporal cortex (Goldman-Rakic, et al., 1998; McIntosh
et al., 1996). These PET studies have shown that the DLPFC is
much less active in the dreaming brain than in the wake brain.
In addition, these PET studies (Braun, et al., 1997, 1998; Maquet,
et al., 1996, 1997) show notable arousal of the extrastriate visual
cortex, especially in the ventral processing stream. The fact
that activation is also seen in limbic and para-limbic structures,
most significantly in the anterior cingulate and the amygdaloid
complexes, while at the same time activity in the dorsolateral
pre-frontal cortex is markedly reduced, point toward emotional
arousal and at the same time suggest a reduction of memory as
well as a diminished capacity for logic and self-reflection. All
this is entirely consistent with many studies of the subjective
qualities of REM dreaming (e.g., Hall & Van de Castle, 1966;
Tonay, 1991). They are also consistent with the hypothesis that
the dreaming brain self-organizes differently than the wake brain,
not only because the dreaming brain is minimally receptive to
outside stimuli, but also because of its changed functional activation
patterns and its changed neuromodulation.
It is interesting that Braun et al. (1998) report decreased activation
of the primary visual cortex during REM. This observation may
seem surprising, since a deactivated primary visual cortex due,
say, to a stroke, results in the absence of visual awareness.
It is, however, consistent with the suggestion that the conscious
experience of vision is more directly associated with the extrastriate
association areas and their connections with the frontal cortex
than with the primary visual cortex itself (Crick & Koch,
1992; Koch, 1998; Revonsuo, 1998). In line with this, lesion studies
show that damage to the extrastriate cortex, as well as damage
to the parietal operculum and to the mediobasal frontal cortex,
result in decreased dreaming (Solms, 1997; Hobson, et al. 1998).
Neurological patients who report a global cessation of dreaming
typically exhibit damage in the parietal convexity, or have suffered
disconnection of the mediobasal frontal cortex from the brainstem
and diencephalic limbic regions (Solms, 1997; Hobson et al. 1998b).
Solms (1997) suggests that since the parietal convexity is important
for sustaining the visual activity implicated by visual phenomenology,
a crucial link exists between dreaming and some of the brain’s
highest regulatory and inhibitory mechanisms. He found that REM
continues even after patients report complete lack of dream phenomenology.
Solms (1999) argues that if dreams completely cease when specific
cortical areas are damaged, yet REM is preserved, there is no
place for a passive, non-initiating, cortex in a robust theory
of dreaming. The question of whether cortical structures are involved
in initiating dreaming is, indeed, controversial and has been
addressed in Hobson, Pace-Schott, and Stickgold (2000) on one
side, and by Antrobus (1990), on the other.
PGO Stimulation, the Dream, and the Self-Organizing
Brain
One of the most striking features of REM sleep is the bombardment
of the optic cortex with large pontine-geniculate-occipital (PGO)
spikes, which release powerful cholinergic stimulation (Callaway
et al., 1987). These spikes originate in the lower brainstem,
travel upward to the lateral geniculate bodies, and then on to
the occipital lobes. Their discovery led Hobson and McCarley (1977)
to offer the now classic activation-synthesis hypothesis, according
to which dream experiences represent the efforts of the cortex
to make sense out of this apparently random activity. In other
words, this PGO activity is interpreted by the visual brain as
sensory stimulation. The implication of this view was that dreams
are meaningless from the perspective of high level cognitive or
emotional process. Taken on face value this notion leaves relatively
little room for dream experiences to be taken seriously as meaningful.
Since then, however, Hobson and one of the present authors took
the initial steps toward exploring the notion that the content
of dream consciousness is the result of self-organizing dynamics
in the brain (Kahn & Hobson, 1993). This idea was further
developed in a recent paper authored by all three of the present
writers, and is continued in the present paper (Kahn, Krippner,
& Combs, 2000). The basic aim of all three of these papers
is toward understanding how coherent dream experiences can arise
in the context of seemingly unpatterned PGO stimulation, as well
as other chaotic-like aspects of brain function.
We suggest that PGO activity has two effects on the dreaming brain.
First, the bombardment of the cortex by PGO spikes might act as
a perturbation to the dreaming visual cortex, creating stochastic
resonance. This raising of the cortical “temperature”
by PGO stimulation would allow the ongoing patterns of cortical
activity to “relax” into natural forms (attractors)
shaped by residual emotional and cognitive influences present
from moment to moment. Thus, the dreaming brain, isolated from
extroceptive sensory constraints, becomes subject to subtle influences
that might exert sizable patterning effects on neural activity
(Combs & Krippner, 1998). Such effects might be felt experientially
as the conscious flow of the dream. This does not mean that dream
narratives carry no forward momentum of their own. Indeed, the
creation of stories seems to be virtually obligatory to the human
mind and brain. Rather, the pelting of the cortex does not allow
the cortical system to stagnate, but keeps it in a forward motion
that is sensitive to the moment to moment changing psychophysiological
state of the brain-in other words, keeps the dream narrative in
motion. Approaching dreaming in the brain from a similar direction,
Globus (1989, 1995) holds that dream narratives are not assembled
from memories that combine according to syntactic rules, but rather
are created de novo as underlying neural networks relax from moment
to moment into natural minima. De novo creativity has no elementals.
The whole product is fashioned at once and is not made of individual
pieces. As an interesting aside, we note that PGO timing becomes
progressively more coherent over the neocortex during periods
of REM sleep, suggestive of an underlying self-organizing stochastic
process (Amzica and Steriade, 1996).
Second, the effect on the cortex of the bombardment of PGO spikes
might be to frequently disrupt ongoing patterns of activity, resulting
experientially in abrupt plot or scenery shifts. At the level
of cortical brain activity these can be understood as catastrophic
bifurcations. Mamelak and Hobson (1989), for instanced, have argued
that PGO stimulation is tied to the high rate of plot shifts experienced
during REM dreaming. Such shifts are more frequent in REM dreaming
than during dreaming reported from NREM sleep (Cavallero, Cicogna,
Natalie, Occhionero & Zito, 1992). Such shifts are evidently
essential to the “bizarreness” of REM dreams (Porte
& Hobson, 1986). Abrupt transitions in dream content are made
all the more effortless during REM sleep by a diminished short
term memory and the loss of a continuous objective sense of self
(e.g., see Purcell, Mullington, Moffitt, Hoffman, & Pigeau,
1986), both perhaps related to the fact that the prefrontal lobes
are essentially taken off-line in the REM state.
As for other influences that mold the content of dreams, the presence
of high activation levels in certain limbic structures during
REM sleep is consistent with the idea that emotional factors play
a significant role in dreams. The brain clearly does not receive
such emotional influences passively, however, but incorporates
them into complex self-organized attractor patterns that play
themselves out as dream narratives (Combs & Krippner, 1998).
Additional influences on dream content also include long-term
episodic and semantic memories, “relaxed” into the dream
narrative, as well as recent experiences whose emotional residues
remain written on the mind and the brain for as long as a few
hours to a few days (Globus, 1989). For instance, Freud (1900/1955)
correctly pointed out that much dream content is directly related
to events of the prior day, a view that has found general support
ever since (Hall & Van de Castle, 1966).
According to Globus’ (1995) view, sleep states evolve naturally
in a self-organizing brain that operates under mutable constraints.
A particular dream experience relies on the pattern of organization
operating at the moment. Influences such as emotions activate
low threshold meanings in a way that is changed by the tuning
of constraints. Learning is one such constraint, as are connection
weights between neurons at the synapse level. The constraint structure
defines a set of possibilities, which in turn dictates what input
the cortical system resonates with. According to these constraints,
the cortical system settles into an actual dream state. No rules
are followed, rather the system flows according to emergent chaotic
attractors.
Interestingly, the sensitivity instilled by the influence of stochastic
resonance may be sufficient to release subtle influences including
narratives and symbols laid down as Hebbian networks early in
the development, perhaps through personal experience or even genetic
patterning (e.g., Edelman, 1992, 2000). If such networks exist
they could do much to give the interpretative views of dynamic
psychology a grounding in the study of the brain.
The details of how the brain transforms each night’s constellation
of emotional and cognitive influences into the rich fabric of
dream life remains a deep mystery. However, these nocturnal productions
in which reality is essentially preserved, but stretched, turned
about, and parceled out into fragments, intuitively seems much
more like the outcome of dynamical processes than of computational
ones. Though dreams will remain a mystery, the authors hope that
they will now become a mystery of the brain-mind system, from
which a unified science and subsequent understanding can emerge.
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Stanley Krippner Ph.D.
Saybrook Graduate School
and Research Center
450 Pacific Avenue
San Fransisco, CA 94133 - 4640
USA
e-mail: skrippner@saybrook.edu
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