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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 745 746 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 | off A p 11 mli eff | off | | 111III | 1 1 | 1 1 1III! 1 | | | 1 I eff 1 1 11 1M I N I 1 1 1MM C off I | | 1 1 1 1 11 | 11 1 1 1I I | 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— 754 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.