Control theory and nervous systems

In the attempt to pursue analysis of the mechanisms of behaviour to the neural level, most of the concepts used are drawn either from general neurobiology or from ethology itself. An additional strand of thought that has made a useful contribution is cybernetics or control systems theory, developed to provide a formal analysis of human control systems. It is often useful to treat the nervous system of a behaving animal, or some part of its nervous system, as a control system through which there is an orderly flow of information, with definite input and output elements.

This approach has provided a helpful terminology and way of thinking about the mechanisms of behaviour. With the advent of powerful computers, it has also become possible to use this approach for constructing models that mimic the interactions among groups of neurons. When used carefully, this provides a means of testing whether circuits work in the way that is predicted from physiological recordings. This is particularly useful when large numbers of neurons are involved because it is rarely possible to monitor activity in many neurons simultaneously.

An example of a useful concept from control theory is that of feedback; this takes place when an event or process has consequences which affect the occurrence of that event or process. In control systems, feedback is usually negative, which means that action is taken in response to a

Figure 1.7 Orientation to prey in a mantis (Tenodera), illustrating movements with and without feedback. (a) A flow diagram of visual tracking of prey with feedback. (b) A flow diagram of rapid visual location of prey without feedback. In (a) and (b) the boxes represent major systems or operations and the circles indicate sites where summation of inputs occurs. (c) Rapid location of prey, as in (b), analysed from videotape, showing orientation towards a stationary target (left) and towards a target that moves off at a constant angular velocity after the mantis has started to turn (right). (c redrawn after Rossel, 1980.)

Figure 1.7 Orientation to prey in a mantis (Tenodera), illustrating movements with and without feedback. (a) A flow diagram of visual tracking of prey with feedback. (b) A flow diagram of rapid visual location of prey without feedback. In (a) and (b) the boxes represent major systems or operations and the circles indicate sites where summation of inputs occurs. (c) Rapid location of prey, as in (b), analysed from videotape, showing orientation towards a stationary target (left) and towards a target that moves off at a constant angular velocity after the mantis has started to turn (right). (c redrawn after Rossel, 1980.)

disturbance so as to correct that disturbance. This usually involves a special mechanism like a thermostat, by means of which the output of a system is fed back to regulate the input. Many behaviour patterns also have this self-regulatory character. In egg retrieval, the movement of the beak towards the chest seems not to involve feedback because it is so stereotyped and because it continues to completion even if the egg is removed during the movement. However, the side-to-side movements that keep the egg centred on the beak certainly appear to involve feedback of some kind; they tend to disappear if the bird is retrieving a cylindrical model, which rolls smoothly and so does not need centring.

The distinction between movements that do and do not involve feedback is made clear by the visual orientation to prey in a praying mantis. The insect follows potential prey with movements of its head or body so as to keep the prey in the centre of its line of vision. In this behaviour pattern, visual information triggers a movement of the praying mantis, and this results in an altered visual input, which in turn influences the subsequent movement. Hence, the flow of information forms a closed loop, with output feeding back to the input (Fig. 1.7a). However, a different situation obtains when the mantis first locates the prey. As soon as a suitable object appears in the visual field, the mantis turns towards it with a rapid movement that is not influenced by feedback from the visual system. Even if the object is experimentally removed during the turn, the mantis still continues turning until it faces the place where the object originally was. Hence, in this case, the information flow forms an open loop, without feedback (Fig. 1.7b, c).

In common with ethological concepts considered above, such concepts from control theory do not in themselves provide an explanation in terms of underlying mechanisms. Rather, they are, in computer terminology, 'software' explanations that specify the job done and the relations between the different components of a behaviour pattern. For a full understanding of the mechanisms of behaviour, these concepts obviously need to be coupled with a detailed analysis of the underlying neural 'hardware'. Once a neural analysis is accomplished, or at least is underway, then the 'software' concepts come into their own as a vehicle for showing how the neural 'hardware' is organised so as to generate a given behaviour pattern. To take a simple example, flow diagrams such as that in Fig. 1.3 have been borrowed from control theory as a vehicle for summarising behavioural mechanisms. If such a diagram is based on known neural components, whose physiological properties have actually been studied, rather than on hypothetical 'black boxes', then the diagram becomes a truly effective way of summarising the link between the nervous system and behaviour (see, for example, Fig. 3.7, p. 60).

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