1.05 - Computing Machines and the Nervous System

classes ::: Cybernetics, Cybernetics, or Control and Communication in the Animal and the Machine, Norbert Wiener, chapterComputing machines are essentially machines for recording,
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object:1.05 - Computing Machines and the Nervous System
subject class:Cybernetics
book class:Cybernetics, or Control and Communication in the Animal and the Machine
author class:Norbert Wiener
class:chapterComputing machines are essentially machines for recording
numbers, operating with numbers, and giving the result in
numerical form. A very considerable part of their cost, both
in money and in the effort of construction, goes to the simple
problem of recording numbers clearly and accurately. The sim-
plest mode of doing this seems to be on a uniform scale, with
a pointer of some sort moving over this. If we wish to record a
number with an accuracy of one part in n, we have to assure that
in each region of the scale the pointer assumes the desired posi-
tion within this accuracy. That is, for an amount of information
log 2 n, we must finish each part of the movement of the pointer
with this degree of accuracy, and the cost will be of the form An,
where A is not too far from a constant. More precisely, since if
n − 1 regions are accurately established, the remaining region
will also be determined accurately, the cost of recording an
amount of information I will be about
( 2 I − 1 ) A
(5.01)
Now let us divide this information over two scales, each marked
less accurately. The cost of recording this information will be
about160
Chapter V
2 ( 2 I 2 − 1 ) A
(5.02)
If the information be divided among N scales, the approximate
cost will be
N ( 2 I N − 1 ) A
(5.03)
This will be a minimum when
2 I N − 1 =
I IN
2 log 2
N
(5.04)
or if we put
I
log 2 = x
N
(5.05)
when
x =
e x − 1
= 1 − e − x
e x
(5.06)
This will occur when and only when x = 0, or N = ∞. That is, N
should be as large as possible to give the lowest cost for the stor-
age of information. Let us remember that 2 I/N must be an integer,
and that 1 is not a significant value, as we then have an infinite
number of scales each containing no information. The best sig-
nificant value for 2 I/N is 2, in which case we record our number
on a number of independent scales, each divided into two equal
parts. In other words, we represent our numbers in the binary
system on a number of scales in which all that we know is that
a certain quantity lies in one or the other of two equal portions
of the scale, and in which the probability of an imperfect knowl-
edge as to which half of the scale contains the observation is
made vanishingly small. In other words, we represent a number
ν in the formComputing Machines and the Nervous System
ν = ν 0 +
1
1
1
ν 1 + 2 ν 2 + + ν n +
2
2
2 n
161
(5.07)
where every ν n is either 1 or 0.
There exist at present two great types of computing machines:
those like the Bush differential analyzer, 1 which are known as
analogy machines, where the data are represented by measure-
ments on some continuous scale, so that the accuracy of the
machine is determined by the accuracy of construction of the
scale; and those, like the ordinary desk adding and multiply-
ing machine, which we call numerical machines, where the data
are represented by a set of choices among a number of contin-
gencies, and the accuracy is determined by the sharpness with
which the contingencies are distinguished, the number of alter-
native contingencies presented at every choice, and the number
of choices given. We see that for highly accurate work, at any
rate, the numerical machines are preferable, and above all, those
numerical machines constructed on the binary scale, in which
the number of alternatives presented at each choice is two. Our
use of machines on the decimal scale is conditioned merely by
the historical accident that the scale of ten, based on our fingers
and thumbs, was already in use when the Hindus made the great
discovery of the importance of the zero and the advantage of
a positional system of notation. It is worth retaining when a
large part of the work done with the aid of the machine consists
in transcribing onto the machine numbers in the conventional
decimal form, and in taking off the machine numbers which
must be written in the same conventional form.
This is, in fact, the use of the ordinary desk computing
machine, as employed in banks, in business offices, and in
many statistical laboratories. It is not the way that the larger and162
Chapter V
more automatic machines are best to be employed; in general,
any computing machine is used because machine methods are
faster than hand methods. In any combined use of means of
computation, as in any combination of chemical reactions, it is
the slowest which gives the order of magnitude of the time con-
stants of the entire system. It is thus advantageous, as far as pos-
sible, to remove the human element from any elaborate chain
of computation and to introduce it only where it is absolutely
unavoidable, at the very beginning and the very end. Under
these conditions, it pays to have an instrument for the change of
the scale of notation, to be used initially and finally in the chain
of computations, and to perform all intermediate processes on
the binary scale.
The ideal computing machine must then have all its data
inserted at the beginning, and must be as free as possible from
human interference to the very end. This means that not only
must the numerical data be inserted at the beginning, but also
all the rules for combining them, in the form of instructions
covering every situation which may arise in the course of the
computation. Thus the computing machine must be a logical
machine as well as an arithmetic machine and must combine
contingencies in accordance with a systematic algorithm. While
there are many algorithms which might be used for combining
contingencies, the simplest of these is known as the algebra of
logic par excellence, or the Boolean algebra. This algorithm, like
the binary arithmetic, is based on the dichotomy, the choice
between yes and no, the choice between being in a class and out-
side. The reasons for its superiority to other systems are of the
same nature as the reasons for the superiority of the binary arith-
metic over other arithmetics.Computing Machines and the Nervous System
163
Thus all the data, numerical or logical, put into the machine
are in the form of a set of choices between two alternatives, and
all the operations on the data take the form of making a set of
new choices depend on a set of old choices. When I add two
one-digit numbers, A and B, I obtain a two-digit number com-
mencing with 1, if A and B are both 1, and otherwise with 0.
The second digit is 1 if A ≠ B, and is otherwise 0. The addition
of numbers of more than one digit follows similar but more
complicated rules. Multiplication in the binary system, as in
the decimal, may be reduced to the multiplication table and the
addition of numbers, and the rules for multiplication for binary
numbers take on the peculiarly simple form given by the table
× 0 1
0 0 0
1 0 1
(5.08)
Thus multiplication is simply a method to determine a set of
new digits when old digits are given.
On the logical side, if O is a negative and I a positive decision,
every operator can be derived from three: negation, which trans-
forms I into O and O into I; logical addition, with the table
⊕ O I
O O I
I I I
(5.09)
and logical multiplication, with the same table as the numerical
multiplication of the (1, 0) system, namely,
O I
O O O
I O I
(5.10)164
Chapter V
That is, every contingency which may arise in the operation of
the machine simply demands a new set of choices of contin-
gencies I and O, depending according to a fixed set of rules on
the decisions already made. In other words, the structure of the
machine is that of a bank of relays, capable each of two condi-
tions, say “on" and “off"; while at each stage the relays assume
each a position dictated by the positions of some or all the relays
of the bank at a previous stage of operation. These stages of oper-
ation may be definitely “clocked" from some central clock or
clocks, or the action of each relay may be held up until all the
relays which should have acted earlier in the process have gone
through all the steps called for.
The relays used in a computing machine may be of very var-
ied character. They may be purely mechanical, or they may be
electro-mechanical, as in the case of a solenoidal relay, in which
the armature will remain in one of two possible positions of
equilibrium until an appropriate impulse pulls it to the other
side. They may be purely electrical systems with two alternative
positions of equilibrium, either in the form of gas-filled tubes,
or, what is much more rapid, in the form of high-vacuum tubes.
The two possible states of a relay system may both be stable in
the absence of outside interference, or only one may be stable,
while the other is transitory. Always in the second case and gen-
erally in the first case, it will be desirable to have special appara-
tus to retain an impulse which is to act at some future time, and
to avoid the clogging up of the system which will ensue if one
of the relays does nothing but repeat itself indefinitely. However,
we shall have more to say concerning this question of memory
later.
It is a noteworthy fact that the human and animal ner-
vous systems, which are known to be capable of the work of aComputing Machines and the Nervous System
165
computation system, contain elements which are ideally suited
to act as relays. These elements are the so-called neurons or nerve
cells. While they show rather complicated properties under the
influence of electrical currents, in their ordinary physiological
action they conform very nearly to the “all-or-none" principle;
that is, they are either at rest, or when they “fire" they go through
a series of changes almost independent of the nature and inten-
sity of the stimulus. There is first an active phase, transmitted
from one end to the other of the neuron with a definite velocity,
to which there succeeds a refractory period during which the
neuron is either incapable of being stimulated, or at any rate is
not capable of being stimulated by any normal, physiological
process. At the end of this effective refractory period, the nerve
remains inactive, but may be stimulated again into activity.
Thus the nerve may be taken to be a relay with essentially
two states of activity: firing and repose. Leaving aside those neu-
rons which accept their messages from free endings or sensory
end organs, each neuron has its message fed into it by other
neurons at points of contact known as synapses. For a given out-
going neuron, these vary in number from a very few to many
hundred. It is the state of the incoming impulses at the various
synapses, combined with the antecedent state of the outgoing
neuron itself, which determines whether it will fire or not. If it is
neither firing nor refractory, and the number of incoming syn-
apses which “fire" within a certain very short fusion interval of
time exceeds a certain threshold, then the neuron will fire after
a known, fairly constant synaptic delay.
This is perhaps an oversimplification of the picture: the
“threshold" may not depend simply on the number of synapses
but on their “weight" and their geometrical relations to one
another with respect to the neuron into which they feed; and166
Chapter V
there is very convincing evidence that there exist synapses of
a different nature, the so-called “inhibitory synapses," which
either completely prevent the firing of the outgoing neuron or
at any rate raise its threshold with respect to stimulation at the
ordinary synapses. What is pretty clear, however, is that some
definite combinations of impulses on the incoming neurons
having synaptic connections with a given neuron will cause it to
fire, while others will not cause it to fire. This is not to say that
there may not be other, non-neuronic influences, perhaps of a
humoral nature, which produce slow, secular changes tending
to vary that pattern of incoming impulses which is adequate for
firing.
A very important function of the nervous system, and, as
we have said, a function equally in demand for computing
machines, is that of memory, the ability to preserve the results
of past operations for use in the future. It will be seen that the
uses of the memory are highly various, and it is improbable that
any single mechanism can satisfy the demands of all of them.
There is first the memory which is necessary for the carrying
out of a current process, such as a multiplication, in which the
intermediate results are of no value once the process is com-
pleted, and in which the operating apparatus should then be
released for further use. Such a memory should record quickly,
be read quickly, and be erased quickly. On the other hand, there
is the memory which is intended to be part of the files, the per-
manent record, of the machine or the brain, and to contribute
to the basis of all its future behavior, at least during a single
run of the machine. Let it be remarked parenthetically that an
important difference between the way in which we use the brain
and the machine is that the machine is intended for many suc-
cessive runs, either with no reference to each other, or with aComputing Machines and the Nervous System
167
minimal, limited reference, and that it can be cleared between
such runs; while the brain, in the course of nature, never even
approximately clears out its past records. Thus the brain, under
normal circumstances, is not the complete analogue of the com-
puting machine but rather the analogue of a single run on such
a machine. We shall see later that this remark has a deep signifi-
cance in psychopathology and in psychiatry.
To return to the problem of memory, a very satisfactory
method for constructing a short-
time memory is to keep a
sequence of impulses traveling around a closed circuit until
this circuit is cleared by intervention from outside. There is
much reason to believe that this happens in our brains during
the retention of impulses, which occurs over what is known as
the specious present. This method has been imitated in several
devices which have been used in computing machines, or at
least suggested for such a use. There are two conditions which
are desirable in such a retentive apparatus: the impulse should
be transmitted in a medium in which it is not too difficult to
achieve a considerable time lag; and before the errors inherent
in the instrument have blurred it too much, the impulse should
be reconstructed in a form as sharp as possible. The first condi-
tion tends to rule out delays produced by the transmission of
light, or even, in many cases, by electric circuits, while it favors
the use of one form or another of elastic vibrations; and such
vibrations have actually been employed for this purpose in com-
puting machines. If electric circuits are used for delay purposes,
the delay produced at every stage is relatively short; or, as in
all pieces of linear apparatus, the deformation of the message
is cumulative and very soon becomes intolerable. To avoid this,
a second consideration comes into play; we must insert some-
where in the cycle a relay which does not serve to repeat the form168
Chapter V
of the incoming message but rather to trigger off a new message
of prescribed form. This is done very easily in the nervous sys-
tem, where indeed all transmission is more or less of a trigger
phenomenon. In the electrical industry, pieces of apparatus for
this purpose have long been known and have been used in con-
nection with telegraph circuits. They are known as telegraph-type
repeaters. The great difficulty of using them for memories of long
duration is that they have to function without a flaw over an
enormous number of consecutive cycles of operation. Their suc-
cess is all the more remarkable: in a piece of apparatus designed
by Mr. Williams of the University of Manchester, a device of this
sort with a unit delay of the order of a hundredth of a second has
continued in successful operation for several hours. What makes
this more remarkable is that this apparatus was not used merely
to preserve a single decision, a single “yes" or “no," but a matter
of thousands of decisions.
Like other forms of apparatus intended to retain a large num-
ber of decisions, this works on the scanning principle. One of
the simplest modes of storing information for a relatively short
time is as the charge on a condenser; and when this is supple-
mented by a telegraph-type repeater, it becomes an adequate
method of storage. To use to the best advantage the circuit facili-
ties attached to such a storage system, it is desirable to be able
to switch successively and very rapidly from one condenser to
another. The ordinary means of doing this involve mechanical
inertia, and this is never consistent with very high speeds. A
much better way is the use of a large number of condensers, in
which one plate is either a small piece of metal sputtered into a
dielectric, or the imperfectly insulating surface of the dielectric
itself, while one of the connectors to these condensers is a pen-
cil of cathode rays moved by the condensers and magnets of aComputing Machines and the Nervous System
169
sweep circuit over a course like that of a plough in a ploughed
field. There are various elaborations of this method, which
indeed was employed in a somewhat different way by the Radio
Corporation of America before it was used by Mr. Williams.
These last-named methods for storing information can hold a
message for quite an appreciable time, if not for a period compa-
rable with a human lifetime. For more permanent records, there
is a wide variety of alternatives among which we can choose.
Leaving out such bulky, slow, and unerasable methods as the
use of punched cards and punched tape, we have magnetic
tape, together with its modern refinements, which have largely
eliminated the tendency of messages on this material to spread;
phosphorescent substances; and above all, photography. Pho-
tography is indeed ideal for the permanence and detail of its
records, ideal again from the point of view of the shortness of
exposure needed to record an observation. It suffers from two
grave disadvantages: the time needed for development, which
has been reduced to a few seconds, but is still not small enough
to make photography available for a short-time memory; and (at
present [1947]) the fact that a photographic record is not sub-
ject to rapid erasure and the rapid implanting of a new record.
The Eastman people have been working on just these problems,
which do not seem to be necessarily insoluble, and it is possible
that by this time they have found the answer.
Very many of the methods of storage of information already
considered have an important physical element in common.
They seem to depend on systems with a high degree of quantum
degeneracy, or, in other words, with a large number of modes
of vibration of the same frequency. This is certainly true in the
case of ferromagnetism, and is also true in the case of materials
with an exceptionally high dielectric constant, which are thus170
Chapter V
especially valuable for use in condensers for the storage of infor-
mation. Phosphorescence as well is a phenomenon associated
with a high quantum degeneracy, and the same sort of effect
makes its appearance in the photographic process, where many
of the substances which act as developers seem to have a great
deal of internal resonance. Quantum degeneracy appears to be
associated with the ability to make small causes produce appre-
ciable and stable effects. We have already seen in Chapter II that
substances with high quantum degeneracy appear to be associ-
ated with many of the problems of metabolism and reproduc-
tion. It is probably not an accident that here, in a non-living
environment, we find them associated with a third fundamen-
tal property of living matter: the ability to receive and organize
impulses and to make them effective in the outer world.
We have seen in the case of photography and similar proc-
esses that it is possible to store a message in the form of a per-
manent alteration of certain storage elements. In reinserting
this information into the system, it is necessary to cause these
changes to affect the messages going through the system. One of
the simplest ways to do this is to have, as the storage elements
which are changed, parts which normally assist in the transmis-
sion of messages, and of such a nature that the change in their
character due to storage affects the manner in which they will
transport messages for the entire future. In the nervous system,
the neurons and the synapses are elements of this sort, and it is
quite plausible that information is stored over long periods by
changes in the thresholds of neurons, or, what may be regarded
as another way of saying the same thing, by changes in the per-
meability of each synapse to messages. Many of us think, in the
absence of a better explanation of the phenomenon, that the
storage of information in the brain can actually occur in thisComputing Machines and the Nervous System
171
way. It is conceivable for such a storage to take place either by
the opening of new paths or by the closure of old ones. Appar-
ently it is adequately established that no neurons are formed in
the brain after birth. It is possible, though not certain, that no
new synapses are formed, and it is a plausible conjecture that the
chief changes of thresholds in the memory process are increased.
If this is the case, our whole life is on the pattern of Balzac’s Peau
de Chagrin, and the very process of learning and remembering
exhausts our powers of learning and remembering until life itself
squanders our capital stock of power to live. It may well be that
this phenomenon does occur. This is a possible explanation for
a sort of senescence. The real phenomenon of senescence, how-
ever, is much too complicated to be explained in this way alone.
We have already spoken of the computing machine, and
consequently the brain, as a logical machine. It is by no means
trivial to consider the light cast on logic by such machines, both
natural and artificial. Here the chief work is that of Turing. 2 We
have said before that the machina ratiocinatrix is nothing but the
calculus ratiocinator of Leibniz with an engine in it; and just as
modern mathematical logic begins with this calculus, so it is
inevitable that its present engineering development should cast
a new light on logic. The science of today is operational; that is,
it considers every statement as essentially concerned with pos-
sible experiments or observable processes. According to this, the
study of logic must reduce to the study of the logical machine,
whether nervous or mechanical, with all its non-removable limi-
tations and imperfections.
It may be said by some readers that this reduces logic to psy-
chology, and that the two sciences are observably and demon-
strably different. This is true in the sense that many psychological
states and sequences of thought do not conform to the canons172
Chapter V
of logic. Psychology contains much that is foreign to logic, but—
and this is the important fact—any logic which means anything
to us can contain nothing which the human mind—and hence
the human nervous system—is unable to encompass. All logic is
limited by the limitations of the human mind when it is engaged in
that activity known as logical thinking.
For example, we devote much of mathematics to discussions
involving the infinite, but these discussions and their accompa-
nying proofs are not infinite in fact. No admissible proof involves
more than a finite number of stages. It is true, a proof by math-
ematical induction seems to involve an infinity of stages, but this
is only apparent. In fact, it involves just the following stages:
1. P n is a proposition involving the number n.
2. P n has been proved for n = 1.
3. If P n is true, P n+1 is true.
4. Therefore, P n is true for every positive integer n.
It is true that somewhere in our logical assumptions there must
be one which validates this argument. However, this mathemati-
cal induction is a far different thing from complete induction
over an infinite set. The same thing is true of the more refined
forms of mathematical induction, such as transfinite induction,
which occur in certain mathematical disciplines.
Thus some very interesting situations arise, in which we may
be able—with enough time and enough computational aids—to
prove every single case of a theorem P n ; but if there is no sys-
tematic way of subsuming these proofs under a single argument
independent of n, such as we find in mathematical induction,
it may be impossible to prove P n for all n. This contingency isComputing Machines and the Nervous System
173
recognized in what is known as metamathematics, the discipline
so brilliantly developed by Gödel and his school.
A proof represents a logical process which has come to a
definitive conclusion in a finite number of stages. However, a
logical machine following definite rules need never come to
a conclusion. It may go on grinding through different stages
without ever coming to a stop, either by describing a pattern of
activity of continually increasing complexity, or by going into a
repetitive process like the end of a chess game in which there is
a continuing cycle of perpetual check. This occurs in the case of
some of the paradoxes of Cantor and Russell. Let us consider the
class of all classes which are not members of themselves. Is this
class a member of itself? If it is, it is certainly not a member of
itself; and if it is not, it is equally certainly a member of itself. A
machine to answer this question would give the successive tem-
porary answers: “yes," “no," “yes," “no," and so on, and would
never come to equilibrium.
Bertrand Russell’s solution of his own paradoxes was to affix
to every statement a quantity, the so-called type, which serves
to distinguish between what seems to be formally the same
statement, according to the character of the objects with which
it concerns itself—whether these are “things," in the simplest
sense, classes of “things," classes of classes of “things," etc. The
method by which we resolve the paradoxes is also to attach a
parameter to each statement, this parameter being the time at
which it is asserted. In both cases, we introduce what we may
call a parameter of uniformization, to resolve an ambiguity
which is simply due to its neglect.
We thus see that the logic of the machine resembles human
logic, and, following Turing, we may employ it to throw light
on human logic. Has the machine a more eminently human174
Chapter V
characteristic as well—the ability to learn? To see that it may
well have even this property, let us consider two closely related
notions: that of the association of ideas and that of the condi-
tioned reflex.
In the British empirical school of philosophy, from Locke to
Hume, the content of the mind was considered to be made up of
certain entities known to Locke as ideas, and to the later authors
as ideas and impressions. The simple ideas or impressions were
supposed to exist in a purely passive mind, as free from influ-
ence on the ideas it contained as a clean blackboard is on the
symbols which may be written on it. By some sort of inner activ-
ity, hardly worthy to be called a force, these ideas were supposed
to unite themselves into bundles, according to the principles of
similarity, contiguity, and cause and effect. Of these principles,
perhaps the most significant was contiguity: ideas or impres-
sions which had often occurred together in time or in space were
supposed to have acquired the ability of evoking one another, so
that the presence of any one of them would produce the entire
bundle.
In all this there is a dynamics implied, but the idea of a
dynamics had not yet filtered through from physics to the bio-
logical and psychological sciences. The typical biologist of the
eighteenth century was Linnaeus, the collector and classifier,
with a point of view quite opposed to that of the evolutionists,
the physiologists, the geneticists, the experimental embryolo-
gists of the present day. Indeed, with so much of the world to
explore, the state of mind of the biologists could hardly have
been different. Similarly, in psychology, the notion of mental
content dominated that of mental process. This may well have
been a survival of the scholastic emphasis on substances, in a
world in which the noun was hypostasized and the verb carriedComputing Machines and the Nervous System
175
little or no weight. Nevertheless, the step from these static ideas
to the more dynamic point of view of the present day, as exem-
plified in the work of Pavlov, is perfectly clear.
Pavlov worked much more with animals than with men, and
he reported visible actions rather than introspective states of
mind. He found in dogs that the presence of food causes the
increased secretion of saliva and of gastric juice. If then a certain
visual object is shown to dogs in the presence of food and only
in the presence of food, the sight of this object in the absence of
food will acquire the property of being by itself able to stimulate
the flow of saliva or of gastric juice. The union by continguity
which Locke had observed introspectively in the case of ideas
now becomes a similar union of patterns of behavior.
There is one important difference, however, between the
point of view of Pavlov and that of Locke, and it is precisely due
to this fact that Locke considers ideas and Pavlov patterns of
action. The responses observed by Pavlov tend to carry a process
to a successful conclusion or to avoid a catastrophe. Salivation is
important for deglutition and for digestion, while the avoidance
of what we should consider a painful stimulus tends to protect
the animal from bodily injury. Thus there enters into the condi-
tioned reflex something that we may call affective tone. We need
not associate this with our own sensations of pleasure and pain,
nor need we in the abstract associate it with the advantage of the
animal. The essential thing is this: that affective tone is arranged
on some sort of scale from negative “pain" to positive “plea-
sure"; that for a considerable time, or permanently, an increase
in affective tone favors all processes in the nervous system that
are under way at the time and gives them a secondary power
to increase affective tone; and that a decrease in affective tone176
Chapter V
tends to inhibit all processes under way at the time and gives
them a secondary ability to decrease affective tone.
Biologically speaking, of course, a greater affective tone must
occur predominantly in situations favorable for the perpetua-
tion of the race, if not the individual, and a smaller affective
tone in situations which are unfavorable for this perpetuation, if
not disastrous. Any race not conforming to this requirement will
go the way of Lewis Carroll’s Bread-and-Butter Fly, and always
die. Nevertheless, even a doomed race may show a mechanism
valid so long as the race lasts. In other words, even the most
suicidal apportioning of affective tone will produce a definite
pattern of conduct.
Note that the mechanism of affective tone is itself a feedback
mechanism. It may even be given a diagram such as shown
in Fig. 7.
Here the totalizer for affective tone combines the affective
tones given by the separate affective-tone mechanisms over a
short interval in the past, according to some rule which we need
not specify now. The leads back to the individual affective-tone
Fig. 7Computing Machines and the Nervous System
177
mechanisms serve to modify the intrinsic affective tone of each
process in the direction of the output of the totalizer, and this
modification stands until it is modified by later messages from
the totalizer. The leads back from the totalizer to the process
mechanisms serve to lower thresholds if the total affective tone
is increasing, and to raise them if the total affective tone is
decreasing. They likewise have a longtime effect, which endures
until it is modified by another impulse from the totalizer. This
lasting effect, however, is confined to those processes actually in
being at the time the return message arrives, and a similar limi-
tation also applies to the effects on the individual affective-tone
mechanisms.
I wish to emphasize that I do not say that the process of
the conditioned reflex operates according to the mechanism I
have given; I merely say that it could so operate. If, however, we
assume this or any simular mechanism, there are a good many
things we can say concerning it. One is that this mechanism
is capable of learning. It has already been recognized that the
conditioned reflex is a learning mechanism, and this idea has
been used in the behaviorist studies of the learning of rats in
a maze. All that is needed is that the inducements or punish-
ments used have, respectively, a positive and a negative affective
tone. This is certainly the case, and the experimenter learns the
nature of this affective tone by experience, not simply by a priori
considerations.
Another point of considerable interest is that such a mecha-
nism involves a certain set of messages which go out generally
into the nervous system, to all elements which are in a state to
receive them. These are the return messages from the affective-
tone totalizer, and to a certain extent the messages from the
affective-tone mechanisms to the totalizers. Indeed, the totalizer178
Chapter V
need not be a separate element but may merely represent some
natural combinatory effect of messages arriving from the indi-
vidual affective-
tone mechanisms. Now, such messages ‘‘to
whom it may concern" may well be sent out most efficiently,
with a smallest cost in apparatus, by channels other than ner-
vous. In a similar manner, the ordinary communication system
of a mine may consist of a telephone central with the attached
wiring and pieces of apparatus. When we want to empty a mine
in a hurry, we do not trust to this, but break a tube of a mercap-
tan in the air intake. Chemical messengers like this, or like the
hormones, are the simplest and most effective for a message not
addressed to a specific recipient. For the moment, let me break
into what I know to be pure fancy. The high emotional and con-
sequently affective content of hormonal activity is most sugges-
tive. This does not mean that a purely nervous mechanism is
not capable of affective tone and of learning, but it does mean
that in the study of this aspect of our mental activity, we can-
not afford to be blind to the possibilities of hormonal transmis-
sion. It may be excessively fanciful to attach this notion to the
fact that in the theories of Freud the memory—the storage func-
tion of the nervous system—and the activities of sex are both
involved. Sex, on the one hand, and all affective content, on the
other, contain a very strong hormonal element. This suggestion
of the importance of sex and hormones has been made to me by
Dr. J. Lettvin and Mr. Oliver Selfridge, While at present there is
no adequate evidence to prove its validity, it is not manifestly
absurd in principle.
There is nothing in the nature of the computing machine
which forbids it to show conditioned reflexes. Let us remember
that a computing machine in action is more than the concatena-
tion of relays and storage mechanisms which the designer hasComputing Machines and the Nervous System
179
built into it. It also contains the content of its storage mecha-
nisms, and this content is never completely cleared in the course
of a single run. We have already seen that it is the run rather
than the entire existence of the mechanical structure of the com-
puting machine which corresponds to the life of the individual.
We have also seen that in the nervous computing machine it is
highly probable that information is stored largely as changes in
the permeability of the synapses, and it is perfectly possible to
construct artificial machines where information is stored in that
way. It is perfectly possible, for example, to cause any message
going into storage to change in a permanent or semi-permanent
way the grid bias of one or of a number of vacuum tubes, and
thus to alter the numerical value of the summation of impulses
which will make the tube or tubes fire.
A more detailed account of learning apparatus in comput-
ing and control machines, and the uses to which it may be put,
may well be left to the engineer rather than to a preliminary
book like this one. It is perhaps better to devote the rest of this
chapter to the more developed, normal uses of modern com-
puting machines. One of the chief of these is in the solution
of partial differential equations. Even linear partial differential
equations require the recording of an enormous mass of data
to set them up, as the data involve the accurate description of
functions of two or more variables. With equations of the hyper-
bolic type, like the wave equation, the typical problem is that
of solving the equation when the initial data are given, and this
can be done in a progressive manner from the initial data to the
results at any given later time. This is largely true of equations
of the parabolic type as well. When it comes to equations of the
elliptic type, where the natural data are boundary values rather
than initial values, the natural methods of solution involve an180
Chapter V
iterative process of successive approximation. This process is
repeated a very large number of times, so that very fast methods,
such as those of the modern computing machine, are almost
indispensable.
In non-linear partial differential equations, we miss what we
have in the case of the linear equations—a reasonably adequate,
purely mathematical theory. Here computational methods are
not only important for the handling of particular numerical
cases, but, as von Neumann has pointed out, we need them in
order to form that acquaintance with a large number of partic-
ular cases without which we can scarcely formulate a general
theory. To some extent this has been done with the aid of very
expensive experimental apparatus, such as wind tunnels. It is in
this way that we have become acquainted with the more com-
plicated properties of shock waves, slip surfaces, turbulence,
and the like, for which we are scarcely in a position to give an
adequate mathematical theory. How many undiscovered phe-
nomena of similar nature there may be, we do not know. The
analogue machines are so much less accurate, and in many cases
so much slower, than the digital machines that the latter give us
much more promise for the future.
It is already becoming clear in the use of these new machines
that they demand purely mathematical techniques of their own,
quite different from those in use in manual computation or in
the use of machines of smaller capacity. For example, even the
use of machines for computing determinants of moderately
high order or for the simultaneous solution of twenty or thirty
simultaneous linear equations shows difficulties which do not
arise when we study analogous problems of small order. Unless
care is exercised in setting up a problem, these may completely
deprive the solution of any significant figures whatever. It isComputing Machines and the Nervous System
181
a commonplace to say that fine, effective tools like the ultra-
rapid computing machine are out of place in the hands of those
not possessing a sufficient degree of technical skill to take full
advantage of them. The ultra-
rapid computing machine will
certainly not decrease the need for mathematicians with a high
level of understanding and technical training. In the mechani-
cal or electrical construction of computing machines, there are
a few maxims which deserve consideration. One is that mech-
anisms which are relatively frequently used, such as multiply-
ing or adding mechanisms, should be in the form of relatively
standardized assemblages adapted for one particular use and no
other, while those of more occasional use should be assembled
for the moment of use out of elements also available for other
purposes. Closely related to this consideration is the one that in
these more general mechanisms the component parts should be
available in accordance with their general properties, and should
not be allotted permanently to a specific association with other
pieces of apparatus. There should be some part of the appara-
tus, like an automatic telephone-switching exchange, which will
search for free components and connectors of the various sorts
and allot them as they are needed. This will eliminate much of
the very large expense which is due to having a great number of
unused elements which cannot be used unless their entire large
assembly is used. We shall find this principle is very important
when we come to consider traffic problems and overloading in
the nervous system.
As a final remark, let me point out that a large computing
machine, whether in the form of mechanical or electric appa-
ratus or in the form of the brain itself, uses up a considerable
amount of power, all of which is wasted and dissipated in heat.
The blood leaving the brain is a fraction of a degree warmer182
Chapter V
than that entering it. No other computing machine approaches
the economy of energy of the brain. In a large apparatus like
the Eniac or Edvac, the filaments of the tubes consume a quan-
tity of energy which may well be measured in kilowatts, and
unless adequate ventilating and cooling apparatus is provided,
the system will suffer from what is the mechanical equivalent of
pyrexia, until the constants of the machine are radically changed
by the heat, and its performance breaks down. Nevertheless, the
energy spent per individual operation is almost vanishingly
small, and does not even begin to form an adequate measure of
the performance of the apparatus. The mechanical brain does
not secrete thought “as the liver does bile," as the earlier mate-
rialists claimed, nor does it put it out in the form of energy, as
the muscle puts out its activity. Information is information, not
matter or energy. No materialism which does not admit this can
survive at the present day.

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Wikipedia - Higher consciousness

https://www.goodreads.com/book/show/183246.Higher_Consciousness_And_Kundalini

https://www.goodreads.com/book/show/375409.A_Brief_Tour_of_Higher_Consciousness

https://www.goodreads.com/book/show/43826302-higher-consciousness

https://www.goodreads.com/book/show/588443.Handbook_to_Higher_Consciousness

Integral World - Stages of higher consciousness (Integral Esotericisn - Part Seven), Alan Kazlev

Integral World - FOOTPRINTS IN THE SAND: Can We Identify Brain Correlates of Higher Consciousness?, essay by Andrew Smith

Integral World - The Stage-Skipping Problem: How Did Our Ancestors Realize Higher Consciousness?, essay by Andrew Smith

https://esotericotherworlds.blogspot.com/2013/10/the-six-planes-of-higher-consciousness.html

https://en.wikiquote.org/wiki/Higher_consciousness

https://humanscience.fandom.com/wiki/Higher_consciousness

Higher consciousness

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