Download IN SEARCH OF PRINCIPLES IN INTEGRATIVE BIOLOGY

AMER. ZOOLOGIST, 5:745-755 (1965;.
IN SEARCH OF PRINCIPLES IN
INTEGRATIVE BIOLOGY
THEODORE HOLMES BULLOCK
Department of Zoology and Brain Research Institute
University of California, Los Angeles
of respect or interest. This is a rich ground
in which to mine for new operating principles, since it includes a whole array of
astounding performances, as well as higher
internal regulations, by which animals
prove their claim to being the most intricately organized objects we know. Although
the level I will speak of overlaps obviously
with cellular and subcellular integration,
a distinction on level of complexity is
heuristic.
By analogy we may inquire into the
mechanism of a watch. To be sure, a thorough understanding calls for the ultimate
in metallurgy and crystallography of springs
and bearings. But we may define a level of
study which asks: Does it work by escapement or by an oscillating crystal? how do
the interacting processes compensate for
deviations by temperature? are there control systems? what do the gears do?—without requiring to know the materials of
which these are made. Indeed we classify
examples made of diverse materials in the
same category if their performances have
similarities.
The few examples I have time for come
from the study of the nervous system and
are chosen to illustrate diversity in the
sorts of problems which nature presents to
us with respect to operating principles of
that system. The field from which to choose
is immense for there are very many workers
and a prodigious literature. The nervous
system has evolved more than any other
organ system. The achievements of its
function, expressed through effectors as
behavior are the quintessence of the animal kingdom and particularly distinguish
higher animals as higher. It is one of the
most characteristic marks of the new age
of biology that the science of the machinery
Presidential address read before the American of behavior has begun to come into its
Society of Zoologists, August 19, 1965, at Urbana,
own. The great ground swell of concern
Illinois. Original observations mentioned were aided
over the urgent problems of man getting
by grants from NIH, XSF, ONR, and AFOSR.
What I would like to do on this occasion
is to share with you some of the excitement
of recent progress in integrative biology. By
this inadequate name is meant the whole
domain of relatively more complex levels
of living entities, emphasizing the system
aspect, the dynamics and the processes more
than the analysis of ultimate componentry
or the description of taxa.
Consider the marvelous mechanisms in
a musician playing the piano, the coordination of parts into a whole (an abbreviation
of the dictionary meaning of integration).
Consider a bat in the woods navigating by
echoes, a spider weaving its characteristic
web, or any of an infinity of examples of
amazing animal performance. Keep these
mental pictures in mind throughout my
remarks since the theme is really "How do
animals do these feats that they all do?"
Recognizing their prey, their own kind,
which side is up, drinking a certain amount,
locomoting a certain amount, orienting,
mating, escaping, displaying—I conjure up
the images and memories that fascinated
you in your tender years before you became
sophisticated and learned it was not dignified to admit an interest in animals and
natural history.
We have for our subjects the most complex systems known, by far, and it is not
to be expected that we will get to the heart
of understanding soon. Nor is it to be expected that man will wait for a step by
step approach, up from the molecule. Simultaneous attack at all levels is called for.
The level of integration which I want to
point to tonight is that intermediate between the cellular and the intact organism,
neglecting the molecular, subcellular, social, ecological, and others out of no lack
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746
THEODORE HOLMES BULLOCK
along with man is now reflected in enorCODING AND FORMS OF COMMUNICATION
mous interest in behavior and its bases, in
AMONG NERVE CELLS
neurobiology, in brain research, psychoLet me develop briefly, however, a group
pharmacology, communication science, neuof
problems and discoveries in which I
rocybernetics, and the rest. As zoologists
we have much to contribute, much to learn, have a special interest, revolving about the
and much to do, using our reservoir of forms of communication among nerve cells,
animal types. Besides it's the best fun I including questions of coding. Call it the
know: figuring out what makes a frog jump, language of the nerve cells. The classical,
a sea urchin on the coral reef shake its all or none nerve impulse (or "spike") is
spines, or a sloth slothful (as I was trying one form of communication and the one
we know most about. Even this quantal
to do last week in Panama).
and discrete event is perhaps usually conAn excellent example of the new uni- verted into a more or less continuously
verse of phenomena now being uncovered graded and smeared out chain of processes
in the search for principles at intermediate at the end of the axon, presynaptically, and
levels is the crucial nervous mystery of in- in the receptive membrane of the next
hibition. We now "know" (!) that there neuron, post-synaptically.
is not one single mechanism of inhibition,
One of the recent findings on modes of
nor a large number of mechanisms, but communication among neurons that has
about five types—where a few years ago we stirred up the neurophysiological world,
knew but one and shortly before that none. because of its extensive implications, is the
But I'm not going to develop this example. assignment of the inhibition or the faciliIf there were time I should like to talk tation caused by certain nerve fibers to a
about the several consequences and impli- presynaptic locus, thus modulating the arcations of lateral inhibition, which is a riving event just as it reaches the axon
widely distributed nervous device involving endings and is about to transmit to the
the systematic suppression of near neigh- postsynaptic cell (Fig. 1). This is the sobors in a layer of nerve cells in parallel. called presynaptic inhibition or presynaptic
New significance is being discovered each facilitation. It enormously increases the
year as both experimental and theoretical range of effects possible, that is to say the
work progresses. Another topic that tempts complexities available with a given number
me and would be fitting is spontaneity and of neurons. We still need a body of comrhythms and their several roles. And an- parative information to assess the relative
other is the major approach to problems importance of this mechanism in different
of functional organization of simple be- kinds of animals and parts of the nervous
havioral acts through the technics of the system.
control systems engineer. He chooses and
Another form of communication between
delimits an input-output function and by
neurons
which was recently discovered is
interrupting or falsifying the flow of inforelectrotonic
connection, via low resistance
mation at chosen points, measuring the
specific
conducting
channels. This was a
phase and the amplitude of response, can
curiosity
of
lobster
heart
ganglia and then
arrive at "as though" assertions concerning
of
strange
supramedullary
cells of puffer
the constituent processes that must exist
and the relations between them. The power
of this method has been applied fruitfully
to several but still only a few cases thus
far. These and a host of other topics I
cannot develop. But you see by these ex- FIG. 1. Diagram of arrangement presumed to exist
amples what I aim at: major foci of new to account for presjnaptic inhibition and pres\naptic facilitation. The terminal of an axon a, just beinsight into the kinds of operations and fore
it makes a junction with posts) naptic neuron
modes of functioning of the brain as a com- b, receives the ending of an axon c, which can
munication-control system.
throttle or enhance the transmission from a to b.
747
PRINCIPLES IN INTEGRATIVE BIOLOGY
of tissue. Sometimes it attenuates brief
electrical events severely and therefore filters in favor of slow changes. We are still
assessing
the significance of this form of
FIG. 2. Diagram ot low resistance electrotonic coninteraction. It will probably turn out to
nection between neurons. The connection shown
by dashed lines is inferred from measurements of
be in some cases an electrically transmitspread of potential from one cell to the other. It
ting synapse, in others a fine anastomosis
is probably situated differently in different cases,
between
nerve cells.
perhaps often between dendrites. It may be a true
anastomosis in some but in others there may be
Communication among masses of cells by
a cell membrane of low resistance forming an elec- diffuse, so-called field effects, is less known
trical synapse between the two neurons.
but is becoming likely, at least in some
fish a short time ago but has now been situations. Brain waves may be an instance
found in a wide variety of situations in (Fig. 3). These are widespread oscillating
invertebrates and in lower vertebrates and currents usually thought to be in synchrony
I expect will turn up any day in a respect- throughout volumes of tissues encompassable animal like the cat! (Only then will ing thousands of millions of cells. In cerit be taken seriously by some neurophysi- tain instances, at least, they appear not to
ologists.) It means there is an electrical be driven by a massive input but to repreconnection between certain nerve cells low sent intrinsic, spontaneous, cellular changes
enough in resistance that useful membrane not really requiring nerve impulses to cocurrent flow occurs from one to the other, ordinate the cells. On this view we are
even though falling off with distance (Fig.' faced with a massive synchronization and
2). This is an effect between specific cells, hence an interaction among cells on a nonnot a diffuse influence throughout a volume specific basis. This is probably electrical
RESPONSE
GATE
w,
LIGHTS
c
i
R. SM CX
L. SM CX
!.i.Jfl.LM./iiu|j,M "
R. OCC CX
%
L. OCC CX
L. LG.
L. HIPPO
W
L. AMYG
RT= 1.9 sec
I sec
FIG. 3. Example of an electroencephalogram.
FIG. 3. A normal electroencephalogram of a cat.
This animal has been trained to recognize that several seconds of lights flashing will mean that opening of a gate offers a food reward. This animal
responds in 1.9 sec after opening of the gate. The
10 sec or so of flashing lights pro\ide a period of
anticipatory change in the brain waves. Prior to
the lights, the waves are small, desynchronized, due
to the alert condition of the animal. Onset of the
lights induces large slow waves in certain parts of
the brain but not others. R. SM CX = right sensory
motor cortex; L. SM CX = left sensory motor cortex; R. OCC CX = right occipital cortex; L. OCC
CX = left occipital cortex; L. LG. = left lateral
geniculate body; L. HIPPO = left hippocampus;
L. AMYG = left amygdala. Courtesy Dr. Nathaniel
Buchwald.
748
THEODORE HOLMES BULLOCK
mi
R i l l
r. I I II I I I I Mill I II I I I I I I
FIG. 4. Hypothetical trains of nerve impulses. A—
A nerve fiber can be silent until a burst of impulses
of a certain duration, number and spacing is generated in the neuron and propagated along the
axon. B—Many neurons are continually firing at
some low, more or less regular rate and increase
(or decrease) in frequency when some event is to
be signaled, that is when they receive some alteration of input. C—Many neurons have more irregular background activity and the signal to noise ratio
of frequency change due to input events is low.
too, but may work quite differently from
the last category and involve feeble modulations, tending on the average to bring
ongoing activity into phase. I must add
that some recent results seem to reopen the
question whether the cells in a mass are
on the average in phase.
However, it is still trains of nerve impulses—quantal, millisecond spikes, propagating without decrement for long distances, that must carry most of the information in the world. (It is a comic sign of
the machine's winning that some people,
more mindful of computers, news media
and the like will object to this statement,
forgetting the teeming billions of animals
and men, each one a crackling maze of
thousands to billions of neurons carrying
scores to hundreds of impulses every second. I hope geneticists among you will
not bristle or take offense. The genetic
information even though duplicated in
every cell bears roughly the same relation
to the nervous as the specifications for a
movie camera, tape recorder, or computer
bear to the information those machines can
process.) This is driven home by the vivid
impression of one who listens spellbound
to the high speed din of impulses in laboriously isolated single nerve fibers, knowing
that their connections typically cascade and
avalanche in the jungle of dendrites, cells,
and axons. A calculation is difficult but
might begin with say 5 or 10 million impulses a day produced by an ordinary neuron, plus even more received and integrated. Expressing this as bits of information is more difficult and beyond our scope
here.
Now we need to know, given nerve imjDulses, what the parameters of the nerve
impulse code can be. It is easy to say a
priori that only the number and the spacing of impulses are available for coding
(Fig. 4). But somewhat more sophisticated
questions are being investigated today. For
example, what level of statistical confidence
does the postsynaptic cell require to distinguish a single significant change in frequency from an insignificant fluctuation?
What is the trade-off between detecting
weak, unreliable signals by averaging over
time and the resulting loss of high temporal
resolution and quick response? How much
fluctuation in successive intervals is tolerable or trivial? (Note in passing that we
are not dealing with a digital system as
some have said, but a pulse-coded analog
system, since the intervals can be continuously varied.)
Can the degree or kind of fluctuation
actually be useful and carry information?
Among kinds of interval fluctuation (Fig.
5) we recognize Gaussian-like and several
non-Gaussian distributions usually with the
mean interval longer than the modal interval; there are also those without and those
with serial correlation in various degrees,
and also differences in the dependency of
standard deviation on mean interval. I mention these to point out the barely tapped
wealth of statistical properties in impulse
trains, for which we badly need good natural history and testable hypotheses.
What degree of fine structure in a train
of spikes is useful or analyzable by the next
cell? The same average frequency can be
achieved by doublets, triplets (Fig. 6), in
fact an infinite number of slightly different
patterns of longer and shorter intervals. If
these can be distinguished to any degree,
the information carrying capacity of each
nerve fiber is enormously greater than if
they cannot. Experimental results from the
few studied cases so far show that fine patterns at a constant average frequency can
be differentially effective on a postsynaptic
cell. Thus a train of impulses separated
by intervals alternately short, long, short,
long has in certain nerve muscle junctions,
cardiac and other ganglia a different
PRINXIPLES IN IXTEGRATIVE BIOLOGY
749
A
Interval class
Interval class
B
FIG. 5. Some statistical properties of trains of impulses. A—Two examples of interspike interval
histograms o£ symmetrical type, one with more
scatter of interval length and higher mean interval
(low frequency), the other faster and more rhythmic. Approximately the same number o£ impulses
in each sample of these and the next two. B—The
same from a neuron which tends to fire close to
strength of excitatory or inhibitory effect
than evenly spaced impulses. The difference in some cases is large, but some junctions show none and the discriminability
of short to long ratios is sometimes low.
Coding by fine temporal structure then, can
be said to be demonstrated and potentially
powerful, but at present I think of it as
rather uncommon since we have but few
cases of naturally occurring doublets or
like groupings, so far.
I have spoken up to this point only of
intervals between successive spikes in a
train, and it is usual to assume that the
language of the nerves can be so described,
i.e., as an interval or frequency code. Recently my colleagues and I have found
candidate coding principles—I say candidate because we don't know yet whether
the analyzing neuron sees the same properties we see—in sensory axons of electroreceptors of the weakly electric fishes (Gymnotidae, Mormyridae, Gymnarchidae), that
differ from the conventional frequency
code. One type of receptor codes stimulaI I I I I I I I I I I I
I I
I I I
I I
I I
I I
I I
I I
I I
I I
FIG. 6. Three of the infinite number of regular
micropal terns of trains of impulses at the same
aveiage frequency.
Interval class
Mean interval
C
D
some limiting interval so that its mode is smaller
than the mean; the right hand side approaches a
Poisson distribution declining logarithmically. C—
Some neurons have a complex histogram, with
more than one mode or/and a long tail. D—Standard deviation of interval is often a linear function
of the mean and the slope is likely to be characteristic for the type of neuron.
tion (provided by movinsr a piece of silver
or plastic in the water near the fish) by
altering the number of spikes in the short
buzz of high frequency spikes that follows
each electric organ discharge (5 to 50±
per second). Of course, the analyzer neuron
in the brain, responding to events per unit
time presumably may be said to measure
the average frequency, but that is a way of
looking at it and it may as well be said
to count. The case is basically distinguished
from the usual in the absence of any systematic change in the individual intervals
(the histogram mode does not shift). The
average over a second or more is not relevant because it is mainly a function of
electric organ discharge rate. We may call
this case a number code (Fig. 7).
Another type of receptor which does not
code by altering spike interval is found in
species that discharge the electric organ
steadily at moderate to high frequency, 100
per sec or more. The receptor generates
one impulse in its axon for each such discharge and therefore fires at a constant rate
(Fig. 7B). Some sensory axons respond to
adequate stimuli by shifting the phase relation (or latency, we can't yet tell which)
precisely and systematically. Many other
fibers do not shift phase (actually this is
harder to explain) but code by changing
the probability that they will fire every
cyle (Fig. 7C). There is therefore ample
basis for the brain to compare a small time
750
THEODORE HOLMES BULLOCK
Stimulus
1
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off
A
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11
mli
eff
|
off
|
|
111III
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1
1
|
1
1
1III!
1
|
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|
1
I
eff
1 1 11 1M I N I 1 1 1MM
C
off
I
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1 1
1 1 11
| 11 1
1 1I I
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FIG. 7. Diagram of some types of nerve impulse
coding. Upper bar indicates onset of a stimulus.
A—Number code as seen in the weakly electric fish
Hypopomus sp. (Gymnotidae). "Eff" shows the
moment of discharge of the electric organ (unaffected by the stimulus). "AfT" shows the burst of
sensory axon impulses consequent to each electric
organ discharge, without changing instantaneous
frequency of firing. The duration of the burst is
altered according to the strength of stimulation.
B— Phase code as seen in Sternopygus sp (Gymnotidae). The latency of the sensory spike is a
function of the stimulus. C—Probability code as
seen in Eigenmannia sp. (Gymnotidae). The ratio
of misses to firings codes intensity of the stimulus.
Time scale: the diagrammatic records each represent about 80 msec.
of spikes the next neuron can actually make
use of, that is, respond to differently. As
for explanations of such discriminations in
more basic terms—generator potentials, excitability time course, and the like—this is
not the place or time to evaluate them,
partly because our knowledge is too meager,
partly because my concern here is to bring
out the possibilities for diverse operating
principles built out of common materials.
The kind of evidence we have been considering emphasizes a prime lesson in unravelling this most complex of systems,
namely that even on the unit level a wide
array of mechanisms and modes is found,
some only in certain places. There have
been workers who preferred to think of the
system as made of simple units, all alike,
the achievements all ascribablc to organization. But nature works quite otherwise,
piling differentiations, specializations, and
emergent degrees of freedom upon each
other at each level where we have sufficient
knowledge. Electrotonic bridges, synchronized brain waves, presynaptic inhibition,
chemical and electrical junctions, patchy
differentiation of neuronal membrane,
graded spikes in axon terminals, spontaneity, various types of frequency distribution
of intervals, various forms of coding—these
do not exhaust the known bases of functional diversity to speak only of the neuronal level. In addition an important diversity of geometric arrangements of junctions is everywhere: buttons, bushes, vines,
nests, brushes, clubs and others, axon to
dendrite or axon to soma, or axon to axon,
possibly dendrite to dendrite and soma to
soma. Still further differentiations at the
electron microscopic level I haven't room
to enumerate.
difference, 100 times a second, and detect
accurate signals of large percentage range
if it is sensitive to time differences in the
fractional millisecond region. Last month
at Barro Colorado Island I found a behavioral reaction in a species of gymnotid
fish sensitive to small differences in phase
between electric organ discharge and extrinsic applied pulse (imitating the pulses
of other individuals), that suggest the system is able to deal with such phase differences. In this case I arranged that each of
the electric organ pulses triggered a stimuTHE MEANING OF MESSAGES; MODALITIES
lator which delivered a small pulse into
AND TRANSFORMATIONS
the water near the fish, after a variable
delay. There is a distinct difference in
Let me turn now to a much more difficult
strength of reaction as between delays topic. I am trying, you see, to parade a
which differ by less than 0.05 millisecond! limited selection of problem-discovery areas
These and other types of evidence point bearing on the question: What's going on
to a diversity of forms of coding. It be- in neurons that recognize, decide, comcomes more urgent than before to try to mand? Given a coded stream of impulses
learn what properties of input sequences what message is it effectively carrying?
PRINCIPLES IN INTEGRATIVE BIOLOGY
"While answers that are not necessarily incorrect can easily be given for final motor
and first order sensory pathways because
we have access to the output in the first
and the input in the second case, these
answers may not fairly represent the meaning of the message for the system. And
still more difficult is an answer for any stage
between first order sensory and final motor.
Suppose we find that a photoreceptor
axon responds to light with a sequence of
impulses having a certain function of frequency to intensity. When this axon carries a train of spikes does it mean to the
brain "A light has abruptly appeared in
such and such part of the visual field, of
such and such intensity and time course?"
Perhaps so; at least it contains that information. But in some cases it may mean
only "Hey., alarm from in front," or it may
mean anything between these extremes. In
others it may mean nothing whatever above
threshold reliability, unless there occur
similar messages in many neighboring fibers. Furthermore somewhere between this
stage and the formulation of motor command there must be one or more transformations. Unless the stimulus was quite
unnatural there must be a decision among
alternatives that the system recognizes:
friend or foe, cloud or leaf, movement
within range, etc. Here is where recent
work gives promise of new insight or at
least cracks for leverage. The problem is
very general, not confined to sensory pathways. Every stage in information processing that is not a pure 1:1 relay, therefore
virtually every junction, is performing a
transformation.
The accumulated experiments taken together with an important amount of anatomical data bring us to a certain concept
of this processing. Nearly always there
must be a convergence or spatial summation
of several to many incoming lines; the crux
of the thing is a dependence of the meaning of messages in one line upon what is
coming in over the others. Generally, it
seems, not a great number of lines converge
on one cell. Successive stages of convergence
occur and useful transformations—let us
call them recognitions—take place in steps.
751
Hence there is a hierarchy of integrative
summations, all perhaps equivalent in
mechanism but each receiving impulse
trains more derived and abstracted in meaning and hence more important than the
preceding.
I believe that there are many varieties of
transformation of meaning in different subsystems. Probably they are often going on
in parallel in separate pathways beginning
with the same input. The photoreceptor
axon spike train I referred to a moment
ago perhaps means only "alarm" to one
central pathway, but to another tickled by
the same sequence of spikes, "moving object going leftward," providing certain
other sequences arrive from other receptors.
Still another central pathway may be concerned only with integrating the average
intensity over many receptors. In another
system, the somatic afferent input from the
skin in mammals, that is the messages in
nerve fibers from sense organs for touch,
temperature, pain, and pressure, bifurcates
into parallel pathways. One of these goes
to the higher centers for specific analysis
of modality, intensity, skin locus, and time
course and one to the lower reticular formation where it virtually loses all specificity, mixes with other inputs and becomes
essentially a message of alerting or arousal.
The story of what the frog's eye tells the
frog's brain, is familiar to some of you. I
regard this as an excellent glimpse into the
future of a key branch of neurobiology.
Several laboratories have now confirmed
that, besides the classical types of nerve
fibers in the optic nerve of the frog which
respond to ON or to OFF or to ON and
OFF of a diffuse light, there are a small
number of additional types which prefer,
i.e., only respond well to, or "recognize"
more complex stimuli. Remember, the optic nerve fibers come from the third layer
of cells in the retina, so that plenty of mixing and comparing of receptor messages
has already taken place. To mention one
example, there is a group of optic nerve
fibers that does not respond to ON or OFF
of the room light. Moreover when it is
adequately stimulated the overall level of
illumination is quite unimportant. These
752
THEODORE HOLMES BULLOCK
fibers require not only light but a light-dark
contrast, such as an object or edge. Moreover it must be sufficiently sharp and focused, and it must not be too large an
object or too straight or gently curved an
edge. A small, dark, sharply focused object is best. Furthermore it must be moving or have recently moved within the 3-5°
excitatory receptive field of that particular
retinal ganglion cell, not too rapidly and
not too slowly. And there must not be at
the same time movement of objects in the
near surroundings, congruent or even contrary in direction. This seems to be quite
a feat of specification for a unit so early
in the system, but others like it are known
in arthropod visual ganglia, cat visual cortex, bat auditory cortex, electric fish cerebellar lateral lobe, and elsewhere. In the
cat visual cortex the literature speaks of
"complex" neurons, "lower order hypercomplex" and "higher order hypercomplex"
.neurons! I think we should regard the
typical central neuron as firing to a constellation of permissive and triggering inputs, thus carrying a highly sophisticated
message. I'm sure we're on the verge of
finding nerve cells that respond to no pure
tones but only to clucking in chickens, or
chirping of the come hither type in crickets,
or to hawk-like silhouettes in certain species, and sea gull bill-like silhouettes in
others. How far this will go is a prime
question in the machinery of behavior. Not
only innate but learned constellations of
stimuli must eventually focus on a recognition unit that has a decisive threshold.
With the background of this improved
insight, as we suppose, into subdivisions of
one modality such as vision, we can reach
perhaps a better understanding of the
thorny old question of modalities. What
is the structural or functional basis of the
several senses? We have to explain not only
the human sense modalities of touch, cold,
heat, pain, taste, smell, vision, and hearing
but also vibration, pressure, tickle, quality
of pain, sense organs that do not reach
consciousness for muscle stretch, joint position, blood pressure, blood CO2, and so
on and on. Are these distinct modalities
equivalent to the first named, or subdivi-
sions or combinations or tangential entities
that don't belong in the same list? Given
whatever list of sensory qualities, are there
separate sets of nerve fibers for each, permanently labeled lines unambiguously signalling their respective forms of stimulation?
On the evidence from visual, auditory, and
some other pathways we can answer yes,
even to the fourth or fifth order neuron
counting in from the sensory cell. Of course
at some level modality is lost when integration between them for higher associations
takes place.
The interesting newer view is that some
sensory influx is not so arranged and may
be ambiguous from the outset, to a certain
degree. Just as the smallest discriminable
locus of touch on the skin is less than the
area of sensibility of a single afferent fiber
but is served by several overlapping receptors, and pitch discrimination is accomplished via input from auditory fibers of
wide and overlapping frequency range, it
seems clear that some sensory fibers overlap
in the quality of stimulus to which they
are usefully sensitive. Nevertheless this
does not mean central confusion necessarily,
since by comparison of many fibers overlapping differently the brain can, we believe, sort out the meaning of the combined
signals. This requires that the overlapping
receptivities of the units be fairly stable
and that they be "known" to the analyzer.
There can thus be more qualities than
there are separate sets of fibers, which answers to an approximation the old riddle.
Our interest here is in the organizational
principle illustrated, central "recovery" of
apparently lost information in overlapping
input lines. This type of transformation of
meaning provides a natural bridge to my
last, brief and still more speculative topic.
DETERMINATE OR APPROXIMATE FUNCTIONS:
PRECISION; REDUNDANCY
We have looked at the single neuron
level and the several neuron level. There
is a very general question, looking at the
large numbers of neurons often available
in a given mass, which is seldom discussed
—perhaps because there are not so many
PRINCIPLES IN INTEGRATIVE BIOLOGY
fools rushing about as angels fearing to
tread. Does the nervous system by and
large employ great numbers of essentially
redundant units with only approximately
the right transfer functions and dynamic
constants (including level of spontaneity)?
This would require less specification to put
together. It might work consistently on a
probabilistic basis. This possibility has
appealed to some workers and is sometimes
elevated to a chief principle of operation
of the brain. This is partly because of the
variability of response of a given neuron
during an experiment, partly because permanent precise calibration is hard to believe, partly because of considerations like
those a moment ago about variation from
unit to unit in a sample and overlapping
to different degrees. The sheer numbers
•of nerve cells is impressive and suggestive
of redundancy as is the tolerance of lesions
that are not too large or in vital spots.
Also it is thought to be unreasonable that
there should be unique neurons, single
"decision cells" and consequently a supposed high vulnerability to unit malfunction.
Is there any case for the contrary, that
neurons are determinate, as precise as the
most reproducible actions and reactions?
Visualize for this the more consistent examples of behavior. In spite of the Harvard
Law,1 behavior is full of highly reproducible actions and it is these rather than
variability that pose our problem. Think
of our piano player again, or the flying
bat, the spider's web or the recognition of
learned symbols.
Is there evidence for precision at the unit
level? There certainly are instances. The
ganglion of the heart of lobsters with only
nine cells reproduces the pattern of its
burst of impulses for hundreds of heart
beats with very small play. This is an interesting type of case because the details
are not due to feedback regulation and the
nine cells fire several dozens of impulses
with considerable fine structure in the pattern. It is highly plastic and alters details
of form extensively but can maintain them
l "Under the most carefully controlled conditions
animals do as they damn please."
753
for many hundreds of repetitions. The pacemaker that controls the electric organ discharge of a species of Hypopomus I studied
last month in Panama is extremely plastic
and commands highly rhythmic firing at
any frequency from 16 to 100 per second,
but a given frequency can be maintained
for thousands of cycles with less than 0.5%
deviation. Neurons can hold calibration
closely. The pacemaker of Eigenmannia,
another such fish may vary still less (ca 300
cps ± one cycle) over days and weeks although it can change quickly if other fish
do certain things. In this species the pacemaker in the brain has been studied and
is a cluster of electrically interconnected
neurons. This may give comfort to the
probabilist, but remember that even though
the cells might vary in their maximum interval (which is never manifested because
the shortest interval paces), there is neither
drift nor fluctuation in any of the cells in
the crucial property, minimum interval,
which we continually see. This is not because they are against some fixed limit,
since certain normal stimuli do elicit a
change in the steady frequency.
The same argument for stable properties
applies more widely. Even if the fastest or
lowest threshold of a population of units
determines response, the fact that the response is consistent bespeaks a statistical
limit on the variability of the cells. A great
deal of behavior is sharply determined and
cannot depend on the mean or mode of a
widely divergent population. When a fly
standing on the table takes flight or a man
says "Aha, I see my friend," there must be
a nervous unit of some kind that makes the
decision, i.e., has a sharp threshold. If
populations of neurons do this democratically, some one has to count the votes and
he becomes the decision unit. Such a unit
need not be a single neuron, but a threshold detecting circuit or a randomly connected mass has little or no advantage.
There can be true redundancy of individually competent decision cells, providing
therefore some tolerance of loss.
We have many examples of unique cells,
especially in arthropods. But in fish the
Mauthner cells, in squid the giant cells—
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THEODORE HOLMES BULLOCK
in fact all good giant systems are examples.
These occur in six or eight phyla. In many
insects the cell-for-cell symmetry in the
two halves of a ganglion is impressive and
certain cells can be recognized in every
specimen. Workers on the mollusc Aplysia
recognize many individual cells by name.
There are of course the phyla with eutely
in which every nerve cell is recognizable
individually, as in Ascaris. Our inability
to do so in higher forms carries no weight;
it may be like the occidental's proverbial
inability to tell Chinese apart!
Even when the behavior is feedback controlled as is believed for walking in insects
and land vertebrates, and the muscle contraction is brought about by different motor
units at different frequencies from moment
to moment, the reproducibility of gait
must mean that input is matched to a desired template and this detailed pattern
can be retained for a life time.
All our recognitions, learned or innate,
including voices, faces, and the like, mean
that the long sequence of transformations
leading to a yes or no are matched against
a stored pattern that is maintained in detail, however many cells are involved. All
our learned symbols and motor patterns,
as in speech, point to the same.
Redundancy does not mean a highly
variant or labile population and is not
equivalent to an antideterminate situation.
It is in fact a loosely used word in the brain
literature. (There is a brief definition and
discussion in the glossary of my book with
Horridge.) The conclusion of the last section, in favor of ambiguous and variously
overlapping sensory units in some modalities (sometimes called a form of redundancy) did not support a probabilistic view
since the overlap function must be stable
and known.
In sum, there are clear cases of precisely
maintained dynamic functions and of
unique cells. Reproducible behavior and
learned and innate patterns severely limit
the range of inconstancy of units. Determinate and precise calibration of neurons
does occur commonly.
Of the reasons listed above for believing
in a probabilistic operation of the brain
the only important one is observed inconsistency of response of units. This certainly
is a finding. Of course we cannot know
how much of the variation is quite determinate arising in the fundamental feature
of central nervous systems that input falls
on an already active system with ongoing
fluctuations of state. Studies, however, on
very simple or isolated parts of the system,
like an axon or single cell, still show variation, e.g., in threshold or in interspike interval which in the context of our understanding of the system is tentatively called
noise. The arrival of impulses from separate receptors converging on a central unit
is also a stochastic process. Between these
two the fixed transfer functions of the cell
operate. It seems reasonable to expect that
there will occur various cases with differing
degree of uncertainty or inconsistency of
response. Note that in the light of these
considerations it is not immediately evident
that apparent inconsistency is indeterminate or probabilistic. Unsuspected differences between stimuli or states of the system
or between units may account for some
variation of responses. The crowd in a
stadium may react to certain stimuli (e.g.,
"strike three!") in an apparently probabilistic way. But the population has a
very small variance in reading the score
board, in categorizing the players into two
teams, in paying for hot dogs.
The argument has been written frankly
as a reaction. Let me make it clear that
there is no doubt in my mind many units
operate with a significant degree of noise
and that an important principle, especially
but not exclusively or universally in higher
animals and higher levels, is averaging
over many parallel lines and over periods
of time long in comparison to the noise
of spike intervals. We know less about
signal-to-noise ratios in slow wave processes
but they may well be similar. In sum,
there are probably all degrees of determinate and of probabilistic operation in different parts of the nervous system; what
degree must be shown critically for each
situation.
This formulation of the issues will hardly
PRINCIPLES IN INTEGRATIVE BIOLOGY
satisfy the interested protagonist of alternate views. But it will serve a useful purpose if it stirs up fresh thinking and new
workers. And for the rest it may illustrate
the yeast and ferment in the broad domain
of integrative biology as well as the diversity of levels of inquiry and type of principle awaiting attention. To me it is an
article of faith that at each higher level
of integration principles will be discovered
755.
that could hardly have been predicted from
lower levels and it is an article of experience that, taking a broad sample of the
animal world, the principles of operation
of any given function are usually not unitary or of very large number but several.
I predict therefore still more exciting insights in the future as biologists on a broad
front patiently unravel the most complex,
levels of life.