# Comments on Bolles **URL:** \ **Category:** CSG1995\ **Created:** [September 16, 1995, 2:23am UTC](http://discourse.iapct.org/t/comments-on-bolles/2688 "1995-09-16T02:23:26Z")\ **Posts on this page:** 2\ **Page:** 1

**Author:** ![Bruce\_Abbott](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/ba8739/32.png) [@Bruce\_Abbott](http://discourse.iapct.org/u/Bruce_Abbott)\ **Post date:** [September 16, 1995, 2:23am UTC](http://discourse.iapct.org/t/comments-on-bolles/2688/1 "1995-09-16T02:23:26Z")

[From Bruce Abbott (950915.2125 EST)] My thanks to (in order of receipt) Avery Andrews, Rick Marken, and Bill Powers for their comments on the Bolles quote on regulation I posted yesterday (950914.1840 EST). One thing I've been trying to do lately is find out what happened to the intense interest in regulatory (control) models involved in feeding, drinking, and other activities which seemed aimed at controlling some physiological quantity or quantities such as cellular hydration, blood glucose level, or body weight, which was in evidence in the late 70's. After a brief "heyday," this approach seems to have withered under intense criticism levied against it, such as Bolles expresses. I thought posting Bolles's critique would provide an opportunity to deal publicly with the issues Bolles (and others) have raised. In so doing I am neither espousing nor defending the position Bolles takes. However, given that this kind of reasoning seems to have led to the dismissal of control theory as an adequate model of physiologically-based motivation (hunger, thirst, etc.), it would seem essential that one be able to answer these criticisms when they are raised. One of the difficulties Bolles (and others) apparently had with applying control theory seems to be that they expected the elements of the model to be represented somewhere in the body literally as diagrammed. If the block diagram shows a comparator, then one must be able to find the comparator, the mechanism in the body where the reference signal is physically subtracted from the perceptual signal to produce the error signal. If the diagram of the standard control system shows a proportional compensator able to oppose errors from both above and below, then the organism had better contain such a mechanism. If there is a set point in the system, there must be a physical signal, being generated by something, which represents the desired state of the controlled variable. When these physical entities were not discovered, this evidence was taken to repudiate the control-system model. Bolles is not the only writer to complain about the problem. After describing temperature regulation by the gound squirrel (which forages in the desert sun until it gets hot and then dives into its burrow and lays flat on the cold floor until it looses the extra heat) and the bee (which regulates the hive temperature through a set of fairly complex interactions among individual bees), J. D. Davis in the same volume says ". . . although one might want to posit the existence of a set-point somewhere in the brain of the ground squirrel it is very difficult to imagine what a set-point for bee hive temperature would be like, where it would be located, or how it would work." D. A. Booth, after outlining his marvelously detailed Mark 3 computer model of feeding, has the following to say under the subtitle "Regulation - a Pernicious Concept": There is the seductive convenience of comparison between thermostats which everyone knows about and homeostats which we hope to learn about. In control theory, the value of the set-point is not identical to the value of the controlled variable when the system has steadied, but it can be made similar; thus it is easy to skip the distinction and read the value acheived by homeostasis into the setting of the homeostat. Most serious of all, the set-point formalism can be interpreted as a physical mechanism and then what may be equilibration between body, environment and brain is attributed to a mechanistic marvel within the brain. Some have claimed to resist this temptation and to intend their invocation of regulatory set-points merely as description of the system's performance characteristics. However, as equilibrium or unreferenced feedback control on the one hand and regulation on the other hand are intertranslatable formalisms for describing performance, the only point in invoking set-point regulation would appear to be the implication that a physical monitor-comparitor mechanism exists which explians the observed stabilising achievements. However, such inference is fallacious. The postulate is arbitrary unless and until independent evidence for a physical comparator mechanism is obtained by anatomical observation and physiological or biochemical measurement at the cellular level in the relevant location(s). Thus, the result of this definition of regulation (even though not its logical requirement) is that stabilities and their defense that can be generated by equilibrium processes which are abundantly evidenced are being "explained" by physical mechanisms of much greater complexity than need to be invoked and are of a type for which there remains no direct physiological evidence in the whole of biology (not even for thermoregulation, or for metabolic biochemistry or genetic expression). The genes, with or without environmental aid, would have to specify a cellular arrangement to produce an extremely precise and unvarying signal of a particular strength throughout an animal's life; this would be the set-point. A monitor has to produce a graded signal of comparable accuracy and a comparator has to subtract signals and emit another graded signal which is converted into physiological or behavioral activity. Mechanical and electronic engineers find such material systems easy to construct but living matter does not have the properties that they exploit. Whether this argument is well framed or not, it appears to have been excepted among the majority of researchers in this area. I am reminded of our own little e. coli nutrient-control model in comparison to Koshland's description of the physical arrangement actually found. In real e. coli, apparently, the rate of change of nutrient concentration as the organism swims about simply alters the rate at which tumbles are initiated via some chemical mediator. All that is required is that a direct relationship be established between rate of nutrient concentration increase and time to next tumble. No reference signal, no comparator, no error signal. Just greater rates of increase lead to longer intervals between tumbles. Our control-system model of e. coli, however, contains an explicit reference signal, comparator, and error signal. Anyone looking into e. coli's system for the physical representations of these entities is not going to find them there; logically, the system merely acts AS IF they are. Perhaps that is the important thing. Regards, Bruce ---

**Author:** ![William\_T\_Powers4](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/w/977dab/32.png) [@William\_T\_Powers4](http://discourse.iapct.org/u/William_T_Powers4)\ **Post date:** [September 16, 1995, 4:53am UTC](http://discourse.iapct.org/t/comments-on-bolles/2688/2 "1995-09-16T04:53:23Z")

[From Bill Powers (950915.2140 MDT)] Bruce Abbott (950915.2125 EST) -- Bruce, this is great work you're doing. All these things you're citing are exactly the reasons for which PCT has not been accepted. J. D. Davis in the same volume says ". . . although one might want to posit the existence of a set-point somewhere in the brain of the ground squirrel it is very difficult to imagine what a set-point for bee hive temperature would be like, where it would be located, or how it would work." This manner of speaking uses words that say "I have difficulty understanding how ..." but which really mean "It is ridiculous to propose ...". Clearly, the idea of controlling a \_perception\_ of beehive temperature would solve Davis's problem, because that would tell us where the set point is located (inside the bee), and a little education in control theory would explain how it would work. But many people have taken Davis' attitude of "If I don't understand it, there can't be anything to it." Booth has a similar problem: There is the seductive convenience of comparison between thermostats which everyone knows about and homeostats which we hope to learn about. In control theory, the value of the set-point is not identical to the value of the controlled variable when the system has steadied, but it can be made similar; thus it is easy to skip the distinction and read the value acheived by homeostasis into the setting of the homeostat. This word "similar" implies "mere" similarity, hiding the fact that the actual temperature can be maintained within a fraction of a degree of the set point. If he had said "almost identical" the whole meaning of the sentence would have been changed. But that isn't Booth's only problem. He says The genes, with or without environmental aid, would have to specify a cellular arrangement to produce an extremely precise and unvarying signal of a particular strength throughout an animal's life; this would be the set-point. The term "extremely precise and unvarying signal of a given strength" reveals a misconception, because there is no "set point" that is invariant for the life of the organism or even for one whole day. A good antidote for this misconception is Myrsovski's \_Homeorhesis\_, in which he shows that (a) the set points of all known biological regulatory systems are variable, and (b) these set points can be proven to change by showing that the system defends different levels of the variable against disturbances at different times. Perhaps someone influential in biology once misinterpreted a "set" point to mean a point that was fixed forever in some optimum state. It's that sort of pompous ignorance that I have been fighting for 40 years. I do get hot under the collar at statements like this: A monitor has to produce a graded signal of comparable accuracy and a comparator has to subtract signals and emit another graded signal which is converted into physiological or behavioral activity. Mechanical and electronic engineers find such material systems easy to construct but living matter does not have the properties that they exploit. This is merely a pretense at expertise on a subject of which the author knows nothing. One of the main reasons for which control systems are used in engineering is that they do NOT require precise or stable components to achieve precise and stable results. One of the main reasons for which control theory is an ideal theory of real human systems is that it describes an organization that can work with the sorts of sloppy components found in living systems, yet achieve quite accurate results. It is the theories that do NOT use control principles that run into problems of precision and stability. What elevates the temperature of my neck protector is these authors' totally unwarranted claim to understanding. The anti-control-theory literature in the behavioral sciences is full of this sort of thing: announcements of how control systems work and what they can or can't do that are based on a few minutes of reasoning and an abysmal lack of actual knowledge. This is how all the myths about control theory have got started; some amateur thinks that he's got it all figured out, but never having studied the subject he makes all the elementary mistakes that any sophomore undergraduate engineering student gets cured of in the first six weeks of an introductory course. Unfortunately, the people who make these mistakes have big names in their fields, so those who read their words naturally assume they know what they're talking about. So the myths just spread and spread. I am reminded of our own little e. coli nutrient-control model in comparison to Koshland's description of the physical arrangement actually found. In real e. coli, apparently, the rate of change of nutrient concentration as the organism swims about simply alters the rate at which tumbles are initiated via some chemical mediator. All that is required is that a direct relationship be established between rate of nutrient concentration increase and time to next tumble. No reference signal, no comparator, no error signal. Just greater rates of increase lead to longer intervals between tumbles. Actually, if you read Koshland carefully, you'll see that there is evidence for variable reference signals. There are "mutants" which always tumble, and others that never tumble. A sufficiently rapid change in the concentration, however, can make the always-tumblers stop tumbling or (in the other direction) the never-tumblers start tumbling. Among normal bacteria, there are different biases on the rate of change of concentration that will begin to suppress tumbling, and of course any such bias is evidence of a reference signal, and by implication some comparison mechanism. The operational definition of a reference level, which is quite independent of the block diagram by which you choose to model the system, is "that level of input at which the output just becomes zero." There is certainly such a level of rate of change of concentration that can be determined for any individual bacterium. And any way you choose to explain this effect is exactly equivalent, mathematically, to the standard PCT diagram. Our control-system model of e. coli, however, contains an explicit reference signal, comparator, and error signal. Anyone looking into e. coli's system for the physical representations of these entities is not going to find them there; logically, the system merely acts AS IF they are. Perhaps that is the important thing. The important thing is not the particular block diagram, but the relationships observed among the variables. What we see is that Output = k \* (RefLevel - Input), Where RefLevel is simply that magnitude of input at which Output = 0. If the Output becomes zero as Input approaches 10 units, then Reflevel is 10 and the equation is Output = k \* (10 - Input). Then by observing how the Output changes as Input departs from the value of 10 units, you can determine the value of k. This is all purely empirical, no theory involved. There is absolutely nothing about this analysis that depends on the particular way you propose that the nervous system creates this relationship. We use the simple PCT diagram because it shows all the basic operations needed to create such a relationship, and its parts correspond to known components of some actual physiological systems. The Input Function converts the physical variable outside the system into an internal signal; the comparator implements the subtraction; the output function implements the amplification and conversion of the difference into a corresponding amount of output. Any two adjacent operations or all three of them could be combined in a single physical element of the system. A single neuron can function as a complete control system. Koshland was actually quite interested in the 'signaling system', which is the Input Function part of the standard model. Once you have split out the input processes, you are left only with the comparison and output processes to explain, and you can model them separately or as a combined function -- until and unless further research enables you to show that these two functions are carried out by different means in different places. This equation and the definition of RefLevel do not depend on the block diagram. The PCT diagram is simply one straightforward way of implementing the equation to produce the same input-output relationship. All of the principles of control can be expressed entirely in terms of observable variables, without ever trying to guess how the nervous system is internally organized. But we -- or at least I -- want to try to understand how the nervous system is organized, which is why I keep looking for physical evidence about the actual wiring, and keep proposing possible block diagrams. Also, a block diagram communicates relationships which are hard for people who are not comfortable with simultaneous equations to understand. The other equation in the simultaneous pair is, of course, the equation that describes how the Input depends on the Output via the environment. The diagram of a control loop makes the solution of the simultaneous equations obvious, or at least more obvious. > **···** > > ----------------------------------------------------------------------- > Best to all, > > Bill P.