Freeman, W. J. (1991) The Physiology of Perception.
Scientific American, Vol. 264 (2), p. 78-85.
The Physiology of Perception
By Walter J. Freeman
The brain transforms sensory messages into conscious perceptions almost
instantly Chaotic, collective activity involving millions of neurons seems
essential for such rapid recognition.
From: February 1991 Scientific American, Vol 264, (2) Pgs. 78-85.
WALTER J. FREEMAN is professor of Neurobiology at the University
of California, Berkeley. He received an M.D. from Yale University in 1954
and completed postdoctoral training in neurophysiology at the University
of California, Los Angeles, in l959, the year he joined the Berkeley faculty.
When a person glimpses the face of a famous actor,
sniffs a favorite food or hears the voice of a friend, recognition is instant.
Within a fraction of a second after the eyes, nose, ears, tongue or skin
is stimulated, one knows the object is familiar and whether it is desirable
or dangerous. How does such recognition, which psychologists call preattentive
perception, happen so accurately and quickly, even when the stimuli are
complex and the context in which they arise varies?
Much is known about the way the cerebral cortex, the outer rind of the
brain, initially analyzes sensory messages. Yet investigations are only
now beginning to suggest how the brain moves beyond the mere extraction
of features-how it combines sensory messages with past experience and with
expectation to identify both the stimulus and its particular meaning to
My own group's studies, carried out over more than 30 years at the University
of California at Berkeley, suggest that perception cannot be understood
solely by examining properties of individual neurons, a microscopic approach
that currently dominates neuroscience research. We have found that perception
depends on the simultaneous, cooperative activity of millions of neurons
spread throughout expanses of the cortex. Such global activity can be identified,
measured and explained only if one adopts a macroscopic view alongside
the microscopic one.
There is an analogy to this approach in music. To grasp the beauty in a
choral piece, it is not enough to listen to the individual singers sequentially.
One must hear the performers together, as they modulate their voices and
timing in response to one another.
Our studies have led us as well to the discovery in the brain of chaos-
complex behavior that seems random but actually has some hidden order.
The chaos is evident in the tendency of vast collections of neurons to
shift abruptly and simultaneously from one complex activity pattern to
another in response to the smallest of inputs.
This changeability is a prime characteristic of many chaotic systems. It
is not harmful in the brain. In fact, we propose it is the very property
that makes perception possible. We also speculate that chaos underlies
the ability of the brain to respond flexibly to the outside world and to
generate novel activity patterns, including those that are experienced
as fresh ideas.
An understanding of perception must be based on knowledge
of the properties of the neurons that enact it. My colleagues and I have
concentrated in many of our studies on neurons of the olfactory system.
For years it has been known that when an animal or a person sniffs an odorant,
molecules carrying the scent are captured by a few of the immense number
of receptor neurons in the nasal passages; the receptors are somewhat specialized
in the kinds of odorants to which they respond. Cells that become excited
fire action potentials, or pulses, which propagate through projections
called axons to a part of the cortex known as the olfactory bulb. The number
of activated receptors indicates the intensity of the stimulus, and their
location in the nose conveys the nature of the scent. That is, each scent
is expressed by a spatial pattern of receptor activity, which in turn is
transmitted to the bulb.
The bulb analyzes each input pattern and then synthesizes its own message,
which it transmits via axons to another part of the olfactory system, the
olfactory cortex. From there, new signals are sent to many parts of the
brain-not the least of which is an area called the entorhinal cortex, where
the signals are combined with those from other sensory systems. The result
is a meaning-laden perception, a gestalt, that is unique to each individual.
For a dog, the recognition of the scent of a fox may carry the memory of
food and expectation of a meal. For a rabbit, the same scent may arouse
memories of chase and fear of attack.
Such knowledge has provided a valuable starting point for more detailed
study of olfaction. But it leaves two important issues unresolved. The
first is the classic problem of separating foreground from background:
How does the brain distinguish one scent from all others that accompany
PORTRAITS" made from electroencephalograms (EEGs)
generated by a computer model of the brain reflect the
overall activity of
the olfactory system at rest (above) and during perception
of a familiar
scent (right). Resemblance of the portraits to irregularly
shaped, but still
structured, coils of wire reveals that brain activity
in both conditions is
chaotic: complex but having some underlying order. The
shape of the right-hand image, together with its greater
color, indicates that olfactory EEGs are more ordered-more
periodic-during perception than during rest.
Also, how does the brain achieve what is called generalization-over- equivalent
receptors? Because of turbulence in nasal air flow, only a few of the many
receptors that are sensitive to an odorant are excited during a sniff,
and the selection varies unpredictably from one sniff to the next. How
does the brain recognize that signals from different collections of receptors
all refer to the same stimulus? Our investigations begin to suggest answers
to both problems.
Many of our insights were derived from intensive studies of the olfactory
bulb. Those experiments show clearly that every neuron in the bulb participates
in generating each olfactory perception. In other words, the salient information
about the stimulus is carried in some distinctive pattern of bulbwide activity,
not in a small subset of feature-detecting neurons that are excited only
by, say, foxlike scents.
Moreover, although this collective neural activity reflects the odorant,
the activity itself is not determined solely by the stimulus. Bulbar functioning
is self-organized, very much controlled by internal factors, including
the sensitivity of the neurons to input.
The experiments uncovering the collective activity were conceptually simple.
By applying standard reinforcement techniques, we trained animals, often
rabbits, to recognize several different odorants and to behave in particular
ways when they did-for instance, to lick or chew in expectation of food
or water. Before training was started, we attached 60 to 64 electrodes
0.5 millimeter apart in a gridlike array to a large part of the bulbar
During training and thereafter, the array enabled us to collect sets of
60 to 64 simultaneously recorded electroencephalogram (EEG) tracings as
the animals breathed in and out, sometimes sniffing familiar scents and
sometimes not. Each tracing reflects the mean excitatory state of local
pools of neurons lying in a well-defined layer immediately beneath the
electrodes. Rises in the wavelike tracings indicate increasing excitement;
dips represent diminished excitement caused by inhibition.
The EEGs should not be confused with recordings of impulses fired by individual
axons or by pools of neurons, although each EEG is related to the firing
pattern of neurons in a neighborhood of the cerebral cortex. The tracings
detect essentially the same information that neurons assess when they "decide"
whether or not to fire impulses, but an EEG records that information for
thousands of cells at once.
To better understand exactly what the EEG shows, it helps to know some
of the details of how cortical neurons operate. Such cells continuously
receive pulses-usually at projections known as dendrites-from thousands
of other neurons. The pulses are conveyed at specialized junctions called
synapses. Certain incoming pulses generate excitatory waves of electric
current in the recipients; others generate inhibitory waves [see top illustration
on page 82]. These currents-"dendritic currents"-are fed through the cell
body (which contains the nucleus) to a region called the trigger zone,
at the start of the axon.
There the currents cross the cell membrane into the extracellular space.
As they do, the cell calculates the overall strength of the currents (reflected
in changes in voltage across the membrane), essentially by adding excitatory
currents and subtracting inhibitory ones. If the sum is above a threshold
level of excitation, the neuron fires.
The mechanism producing each EEG tracing similarly sums the currents initiated
at the dendrites, but it taps the currents after they leave the cell. The
tracings reflect the excitatory state of groups of neurons rather than
of individual ones, because the extracellular space is traversed by currents
from thousands of cells.
BASIC FLOW OF OLFACTORY INFORMATION IN THE BRAIN
In our experiments the EEG tracings from the electrodes
in an array are as unpredictable and irregular as freehand scrawls. Yet
they manifest perceptual information.
In living individuals, EEGs always oscillate, or rise and fall, to some
extent, but the oscillations are usually quite irregular. When an animal
inhales a familiar scent, what we call a burst can be seen in each EEG
tracing. All the waves from the array of electrodes suddenly become more
regular, or ordered, for a few cycles-until the animal exhales. The waves
often have a higher amplitude (height) and frequency than they do at other
The burst waves are often called 40 hertz waves, meaning that they oscillate
at about 40 cycles per second. Because the frequency can actually range
from 20 to 90 hertz, I prefer to call them gamma waves, in analogy with
a range of high-frequency X rays.
The fact that the bursts represent cooperative, interactive activity is
not immediately clear in the EEG plots, because the burst segments differ
in shape from tracing to tracing in a simultaneously recorded set. Nevertheless,
by taxing our computers, we find we are able to tease out evidence of collective
behavior from the complex background. In each set of burst recordings,
we can identify a common waveform, or carrier wave: a shared pattern of
rises and falls that is embedded in each tracing. The average amplitude
is not identical across the set-some versions of the carrier wave are shallow,
and others are deep. But all of them curve up and down nearly in synchrony.
The common behavior makes up between one quarter and three quarters of
the total activity of the neurons giving rise to each trace.
Curiously, it is not the shape of the carrier wave that reveals the identity
of an odor. Indeed, the wave changes every time an animal inhales, even
when the same odorant is repeatedly sniffed. The identity of an odorant
is reliably discernible only in the bulbwide spatial pattern of the carrier-
wave amplitude [see top illustration on page 84].
Amplitude patterns become especially clear when we plot the average amplitude
of the individual versions of the carrier wave on a grid representing the
surface of the bulb. The resulting "maps" resemble contour diagrams that
indicate the elevations of mountains and valleys. As long as we do not
alter the animals' training, the same map emerges every time an animal
sniffs a particular odorant, even though the carrier wave differs with
These maps have helped demonstrate not only that perception requires global
bulbwide activity but also that the bulb participates in assigning meaning
to stimuli. The amplitude map representing a given odorant changes strikingly
when we alter the reinforcement associated with that scent. If the bulb
did not bring experience to bear on perception, the map would remain constant
even after the conditioned association had been changed.
THE OLFACTORY SYSTEM share information through a rich web of synapses,
junctions where signals flow from neuron to neuron. Usually signals pass
from projections called axons to projections called dendrites, but sometimes
they pass from dendrite to dendrite or axon to axon. The widespread sharing
leads to collective activity. In this highly schematic diagram, red shading
signifies that a neuron is exciting another cell, black shading that a
neuron is inhibiting another.
We believe that something we call the nerve cell
assembly is both a crucial repository of past associations and an essential
participant in the formation of the collective bulbar burst. The hypothetical
assembly consists of neurons that have simultaneously been excited by other
neurons during learning.
More than 20 years ago my colleagues and I discovered that when animals
are trained by reinforcement techniques to discriminate olfactory stimuli,
certain synapses that connect neurons within the bulb and within the olfactory
cortex become selectively strengthened during the training. That is, the
sensitivity of the postsynaptic cells to excitatory input-a property known
as gain-is increased at the synapse, so that an input generates a greater
dendritic current than it would have generated in the absence of special
training. Technically, gain is the ratio of output to input-here, the net
strength of the dendritic currents to the number of incoming pulses. The
strengthening occurs not in the synapse between an input axon (such as
a receptor from the nose) and the neuron it excites (such as a bulbar neuron)
but in the synapse between connected neurons that are simultaneously excited
by input neurons during learning. Neurons in the bulb and in the olfactory
cortex are connected to many others in those regions.
EEG WAVES reflect
the mean excitation of pools of neurons. Excitatory inputs at synapses
generate electric currents that flow in closed loops within the recipient
neuron toward its axon, across the cell membrane into the extracellular
space and, in that space, back to the synapse (red arrows). Inhibitory
inputs generate loops moving in the opposite direction ( black arrows).
In cells the trigger zone adds current strengths (reflected in changes
in voltage across the membrane), and it fires impulses if the sum is sufficiently
positive. Electrodes on the brain tap those same currents after they leave
the cell. The resulting EEGs indicate the excitation of whole groups of
cells, not individuals, because the extracellular avenues from which the
EEGs arise carry currents contributed by thousands of cells.
Such strengthening is predicted by the widely accepted Hebb rule, which
holds that synapses between neurons that fire together become stronger,
as long as the synchronous firing is accompanied by a reward. (The strengthening
is now known to involve "modulator" chemicals that the brain stem releases
into the bulb and cortex during reinforcement.) We infer from our data
that a nerve cell assembly, consisting of neurons joined by Hebbian synapses,
forms for a particular scent as an individual is reinforced for learning
to identify that odorant. Thereafter, when any subset of neurons in the
assembly receives the familiar input, the entire assembly can rapidly become
stimulated, as excitatory signals speed across the favored Hebbian synapses.
The assembly, in turn, directs the rest of the bulb into a distinct pattern
If we are correct, the existence of a nerve cell assembly would help explain
both the foreground-background problem and generalization-over- equivalent
receptors. In the first instance, the assembly would confer "frontrunner"
status on stimuli that experience, stored in the Hebbian synapses has made
important to the individual. In the second instance, the assembly would
ensure that information from any subset of receptors, regardless of where
in the nose they were located, would spread immediately over the entire
assembly and from there to the rest of the bulb.
RECORDINGS from the olfactory bulb (a) and front (b) and rear (c) parts
of a cat's olfactory cortex show low-frequency waves interrupted by "bursts"-high-amplitude,
high-frequency oscillations that are generated when odors are perceived.
The average amplitude of a burst is some 100 microvolts. Each lasts a fraction
of a second, for the interval between inhalation and exhalation.
As important as the nerve cell assembly is to
perception, it does not by itself generate bulbwide bursts of collective
activity. For a burst to occur in response to some odorant, the neurons
of the assembly and the bulb as a whole must first be "primed" to respond
strongly to input.
Two important processes complement the priming accomplished by the development
of Hebbian synapses. Both processes affect the gain, doing so by altering
the sensitivity of the trigger zones, not the synapses. Here the gain is
the ratio of the number of pulses fired (output) to the net dendritic current
(input). The total gain is the product of the gain at the synapses and
One primer is general arousal. Our experiments show that the gain in neuronal
collectives increases in the bulb and olfactory cortex when an animal is
hungry, thirsty, sexually aroused or threatened [see illustration on page
85]. Such priming seems to be accomplished by axons from elsewhere in the
brain that release modulatory chemicals (other than those involved in forming
The other primer is input itself. When cortical neurons are excited, their
output increases. Each new input they receive while they are still excited
raises their output markedly, indicating that their gain has been increased
by the input. This increase occurs over a particular range of input. If
the net input is strongly inhibitory, no pulses are fired. Above some very
high level of excitatory input, neurons fire at their maximal rate and
cannot do more, even if the input is increased. In the wide range between,
however, pulse output increases along a sigmoid (S-shaped) curve. The steepness,
or slope, of the curve reflects the gain.
The discovery of an increase in gain with excitation is particularly noteworthy
because most neural network models assume neurons are at maximum gain when
they are at rest. Both excitation and inhibition are generally assumed
to decrease gain, so that the networks constantly maintain stability. Such
assumptions are inappropriate for the brain because they do not allow networks
to generate explosive changes. Hence, it seems that information from odorants
is fed by a small number of receptors to a still smaller number of cells
in the bulb. If the odorant is familiar and the bulb has been primed by
arousal, the information spreads like a flash fire through the nerve cell
assembly. First, excitatory input to one part of the assembly during a
sniff excites the other parts, via the Hebbian synapses. Then those parts
reexcite the first, increasing the gain, and so forth, so that the input
rapidly ignites an explosion of collective activity throughout the assembly.
The activity of the assembly, in turn, spreads to the entire bulb, igniting
a full-blown burst.
The bulb then sends a "consensus statement" simultaneously along parallel
axons to the olfactory cortex. What must next be made clear is how that
cortical area distinguishes the consensus statement from the background
of other stimuli impinging on it from the bulb and elsewhere.
WHY EEG WAVES OSCILLATE
Alternating rises and falls in amplitude stem from negative-feedback
circuits that are established by the interaction of pools of excitatory
and inhibitory neurons. When the pools have been sensitized to input, even
a small input can trigger. A burst of high-amplitude oscillation. The diagrams
represent neuronal activity at the end of each quarter cycle. Dark shading
signifies great excitement; lighter shading signifies less excitement.
The answer undoubtedly has to do with the wiring
joining the bulb to the cortex. The bulb generates trains of impulses that
run simultaneously along the parallel axons leading from the bulb to the
cortex. Each axon branches extensively and transmits pulses to many thousands
of neurons across the olfactory cortex, and each cortical target cell receives
input from thousands of bulbar cells.
The carrier activity of the incoming lines, which is synchronized by cooperation,
probably stands out for the simple reason that such signals add together-
nonsynchronous inputs, which are not at the carrier frequency and phase,
effectively cancel one another. Thus, every recipient neuron in the olfactory
cortex picks up a share of the cooperative bulbar signal and transmits
the summed signals to thousands of its neighbors simultaneously.
In response, the massively connected neurons of the cortex, which have
formed their own nerve cell assemblies, promptly generate their own collective
burst, albeit one having a carrier wave and a spatial amplitude pattern
that differ from those in the bulb. In essence, the transmission pathway
for the global pattern in the bulb launders the bulbar message; it removes
"noise," so that only the collective signal affects the olfactory cortex
significantly. Just as a burst in the bulb guarantees the delivery of a
coherent message to the cortex, so presumably does the global burst in
the cortex enable outgoing messages from that region to stand above the
din when they reach other regions of the brain.
There are many reasons why we believe the activity of the brain both during
and between bursts is chaotic, not merely random. But before I delve into
those reasons, let me clarify further what is meant by chaos. At the risk
of oversimplification, I sometimes like to suggest the difference between
chaos and randomness by comparing the behavior of commuters dashing through
a train station at rush hour with the behavior of a large, terrified crowd.
The activity of the commuters resembles chaos in that although an observer
unfamiliar with train stations might think people were running every which
way without reason, order does underlie the surface complexity: everyone
is hurrying to catch a specific train. The traffic flow could rapidly be
changed simply by announcing a track change. In contrast, mass hysteria
is random. No simple announcement would make a large mob become cooperative.
One of the most convincing early clues to the presence of chaos was an
aperiodic (nonrepeating) common carrier wave everywhere in the bulb not
only during bursts but also between bursts-even when there was no extrabulbar
stimulus driving that collective activity. The lack of external driving
meant the activity was self-generated by the bulb. Such self- organization
is a characteristic of chaotic systems [see "Chaos," by James B. Crutchfield,
J. Doyne Farmer, Norman H. Packard and Robert S. Shawl SCENTIFIC AMERICAN,
Another clue was the apparent ability of neural collectives in the bulb
and cortex to jump globally and almost instantly from a nonburst to a burst
state and then back again. Rapid state changes are called phase transitions
by physicists and bifurcations by mathematicians. Whatever they are called,
dramatic changes in response to weak input are, it will be recalled, another
feature of chaotic systems. Bifurcation is significantly harder to control
in random systems.
We gained more evidence for chaos by developing computer models of the
olfactory system as a whole: the bulb, the cortex, the connections between
them and the input to both areas from outside the system. We simulated
the activity of the system by solving sets of ordinary differential equations
that describe the dynamics of local pools of neurons.
First we demonstrated that the model did in fact represent the olfactory
system accurately. With no more than a single pulse (equivalent to excitation
of a few receptors) to start the system, the model sustained activity that
closely resembled aperiodic olfactory EEGs.
After we " trained" the model to recognize specific odorants, the bulbar
segment generated bursts in response to the selected inputs, and the embedded
common carrier waves yielded distinct and consistent amplitude maps. Moreover,
whenever we added a new "odorant" to the perceptual repertoire of our hypothetical
subject, an identifying global amplitude map was created. At the same time,
the other maps changed-as they should, of course, in a true associative
memory system. We had earlier found such changes in test animals after
they were trained to recognize stimuli beyond the ones they had learned
COMMON CARRIER WAVE emerged from 60 EEGs recorded information
is contained in the spatial pattern of amplitude simultaneously from the
olfactory cortex of a rabbit as it recognized a scent (left). The
wave is nearly the same in each recording, except that the amplitude varies.
The shape of the carrier wave does not indicate the identity of the scent.
That information is contained in the spatial pattern of amplitude across
the cortex, which can be displayed as a contour plot(right), much like
the plots of elevations in topographic maps. The colored contours represent
the highest amplitude; successive contours represent the lower amplitudes.
Our model yielded additional evidence for chaos
when we coaxed it to produce mock EEGs of extended bursts and of "interburst"
activity in the intervals between bursts. Because the artificial EEGs persisted
longer than EEGs normally do, we were able to plot what are called phase
portraits of the predicted behavior of the olfactory system, both during
and between bursts. The portraits can show at a glance whether the dynamics
may be chaotic.
The details of how such portraits are made and why they are a valid reflection
of global activity in the olfactory system are too complex to discuss at
length. Nevertheless, for those readers familiar with phase portraits,
I should note that we plotted the portraits in a three- dimensional grid
and added color to display a fourth dimension. Each axis represented EEG
amplitude from some part of the olfactory system, such as the bulb or a
subsection of the olfactory cortex. A range of colors from red to blue
represented high to low amplitude from a fourth part of the system.
We plotted as a point one set of three amplitudes, measured at a given
moment. Next we plotted another point from the set, representing a thousandth
of a second later, and connected the two points with a colored line. Then
we plotted a third point, and so on. We rotated the final image in space
to find the most informative point of view.
at the left emerged consistently from bulbar EEG's of a rabbit that had
been conditioned to associated the scent of sawdust with a particular reinforcement.
After the animal learned to recognize the smell of banana (middle), however,
reexposure to sawdust led to the emergence of a new sawdust plot (right).
The change shows that bulbar activity is dominated more by experience than
by stimuli; otherwise, sawdust would always give rise to the same plot.
The pictures supported the possibility of chaos, because the images
resembled loose coils of wire having different shapes and color distributions.
If the model olfactory system had behaved randomly, there would be no coherent
shapes, just dots spread everywhere, like "snow" on a television set. If,
on the other hand, the system was predictable in detail, the shapes would
be simpler; they might resemble a spiral, a folded circle or a torus (a
The shapes we found represent chaotic attractors. Each attractor is the
behavior the system settles into when it is held under the influence of
a particular input, such as a familiar odorant. The images suggest that
an act of perception consists of an explosive leap of the dynamic system
from the "basin" of one chaotic attractor to another; the basin of an attractor
is the set of initial conditions from which the system goes into a particular
behavior. The bottom of a bowl would be a basin of attraction for a ball
placed anywhere along the sides of the bowl. In our experiments, the basin
for each attractor would be defined by the receptor neurons that were activated
during training to form the nerve cell assembly.
We think the olfactory bulb and cortex maintain many chaotic attractors,
one for each odorant an animal or human being can discriminate. Whenever
an odorant becomes meaningful in some way, another attractor is added,
and all the others undergo slight modification.
show the relation between input (wave density) and output (pulse density)
at trigger zones in populations of neurons. (The plots are not valid for
individual neurons.) The rising steepness associated with increased arousal
indicates that sensitivity to input-or gain (the ratio of output to input,
or the slope)-rises with arousal. In each case, gain also increases as
neurons that are already excited (those at and to the right of the circles)
receive more stimulation. This input-dependent increase in gain is essential
to the formation of bursts
Identification of chaos does not automatically reveal its source. We suspect
chaos in the brain arises when two or more areas of the brain, such as
the bulb and the olfactory cortex, meet at least two conditions: they excite
one another strongly enough to prevent any single part from settling down,
and, at the same time, they are unable to agree on a common frequency of
oscillation. Competition between the parts would increase the sensitivity
and instability of the system contributing to chaos. Part of the evidence
for the importance of interaction between the bulb and the cortex is that
disconnection of the two regions makes chaos disappear; both parts become
abnormally stable and quiet.
Modulatory chemicals released into the system from elsewhere in the brain
also increase sensitivity to input, both by participating in the formation
of the Hebbian synapses in nerve cell assemblies and by enhancing arousal.
Because various factors maintain great sensitivity, a very small signal-a
whiff, a whisper, a glimpse-can trigger a massive, collective state change.
Conceivably, the chaos we have observed is simply an inevitable by- product
of the brain's complexity, including its myriad connections. Yet our evidence
suggests that the controlled chaos of the brain is more than an accidental
by-product. Indeed, it may be the chief property that makes the brain different
from an artificial-intelligence machine.
One profound advantage chaos may confer on the brain is that chaotic systems
continually produce novel activity patterns. We propose that such patterns
are crucial to the development of nerve cell assemblies that differ from
established assemblies. More generally, the ability to create activity
patterns I may underlie the brain's ability to generate insight and the
"trials" of trial and-error problem solving.
We have found widespread, apparently chaotic behavior in other parts of
the brain. That finding does not necessarily imply that other sensory systems
operate as the olfactory system does. But we think they do. Indeed, we
and other investigators have documented gamma bursts across large cortical
regions involved in recognizing visual images. As in the olfactory system,
familiar visual stimuli are associated with specific amplitude maps of
common carrier waves. I predict that when people examine drawings in which
foreground and background are ambiguous, so that perception alternates
between two images, the amplitude maps will be found to alternate as well.
I begin to envision the general dynamics of perception. The brain seeks
information, mainly by directing an individual to look, listen and sniff.
The search results from self-organizing activity in the limbic system (a
part of the brain that includes the entorhinal cortex and is thought to
be involved in emotion and memory), which funnels a search command to the
motor systems. As the motor command is transmitted, the limbic system issues
what is called a reafference message, alerting all the sensory systems
to prepare to respond to new information.
And respond they do, with every neuron in a given region participating
in a collective activity-a burst. Synchronous activity in each system is
then transmitted back to the limbic system, where it combines with similarly
generated output from other sensory systems to form a gestalt. Then, within
a fraction of a second, another search for information is demanded, and
the sensory systems are prepared again by reafference.
Consciousness may well be the subjective experience of this recursive process
of motor command, reafference and perception. If so, it enables the brain
to plan and prepare for each subsequent action on the basis of past action,
sensory input and perceptual synthesis. In short, an act of perception
is not the copying of an incoming stimulus. It is a step in a trajectory
by which brains grow, reorganize themselves and reach into their environment
to change it to their own advantage.
The poet William Blake wrote: "If the doors of perception were cleansed
every thing would appear to man as it is, infinite." Such cleansing would
not be desirable. Without the protection of the doors of perception-that
is, without the self-controlled chaotic activity of the cortex, from which
perceptions spring-people and animals would be overwhelmed by eternity.
MASS ACTION IN THE NERVOUS SYSTEM: EXAMINATION OF THE NEUROPHYSIOLOGICAL
BASIS OF ADAPTIVE BEHAVIOR THROUGH THE EEG. Walter J. Freeman. Academic
How BRAINS MAKE CHAOS IN ORDER TO MAKE SENSE OF THE WORLD. Christine
A. Skarda and Walter J. Freeman in behavioral and Brain Sciences, Vol.
10 No. 2, pages 161-195; June 1987.
THE SYNAPTIC ORGANIZATION OF THE BRAIN. Third edition. Gordon M. Shepherd.
Oxford University Press, 1990.
SYNERGETICS OF COGNITION: PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM
AT SCHLOSS ELMAU, BAVARIA, JUNE 4-8, 1989. Edited by H. Haken and M. Stadler.
Copyright 1991: Walter J. Freeman