The function of behaviour patterns

The second kind of answer is couched in terms of function. Diverse as they are, our examples of behaviour above (and any others we might have come up with) fall into

1.1 ⁿ What is behaviour? x ₃ AB_C01.qxd 9/17/07 8:00 PM Page 3

one of two camps. Moving a limb or batting an eyelid each involves a relatively simple set of motor responses resulting in a clear-cut and seemingly isolated action. The display of the bird of paradise and the helpful chimpanzee, on the other hand, employ a complex set of actions that has all the appearance of contriving a desired outcome (attracting a female, comforting an infant). The sequence has a functional outcome, but more than that it seems to have purpose. Animals appear to do things in order to achieve something. This is reflected in our very descriptions of behaviour. We talk of

‘searching for food’, ‘hiding from predators’, ‘migrating home’ or ‘exploring a cage’.

Each involves a diversity of actions, perhaps no more complicated than moving a limb or blinking an eye, but actions that are clustered together into functionally organised sequences resulting in the animal achieving an important outcome. What can we infer from this?

1.1.2.1 Purpose and goal-directedness: means to ends

The apparent purposefulness of much behaviour begs two important questions. How has such purposefulness come about in natural systems, and what does it imply about the organisms that show it?

As McFarland (1989) has pointed out, there is a widespread temptation to interpret apparent purposefulness as indicating some kind of internal representation of what has to be achieved. The representation may be a set point (an ideal state of the system), as envisaged in certain homeostatic physiological processes such as temperature regulation, or it may be some kind of mental image, as postulated in many cognitive explanations of behaviour (a hungry rat sets out with an image of food in its head, a blackbird weaves twigs and grass into its notion of a nest) (see 4.2). McFarland uses the term ‘goal-directedness’

to describe purposefulness based on these kinds of internal representation and contrasts it with two other ways of appearing to pursue a goal.

In ‘goal-achieving’ systems the requirement for some commodity, say food, makes the animal restless; it moves around until it happens to encounter some food, then it becomes quiescent. This implies that the goal is recognised when it is encountered rather than the behaviour resulting in its discovery (restlessness) being driven by a prior internal representation. Template recognition in certain molecular systems, such as ‘lock and key’ enzyme–substrate complexes, would be an analogous process. In ‘goal-seeking’

systems, on the other hand, there is no representation or recognition of the goal at all.

The apparent attainment of a goal is due entirely to the physical forces acting on and /or within the system. McFarland uses the example of a marble rolling around a bowl.

Depending on where it starts rolling, the marble could take a variety of routes round the bowl but it will inevitably end up sitting in the bottom. There is no internal representa-tion of the bottom of the bowl and the effectiveness of its downward movement in bringing the marble to rest is independent of its environment (unlike a goal-achieving system in which triggered activity such as restlessness will lead to an appropriate outcome, say finding food, only in specific kinds of environment). The marble would head downward and come to rest whether it was rolled around a bowl or dropped from a skyscraper. It arrives at its ‘goal’ simply by gravity.

McFarland’s distinctions, while schematic, show there are several ways of appearing purposeful, each with different implications for underlying mechanism. These kinds of distinction become extremely important, as we shall see later, when we consider the nature of internal mechanisms responsible for behaviour. Some examples make them clearer.

Locomotion in woodlice

A nice example of goal-achieving behaviour comes from Fraenkel & Gunn’s (1961) classic study of locomotion in woodlice (Porcellio scaber) (see also Benhamou & Bovet 1989).

Woodlice tend to end up in dark, damp places, but they do not get there by knowing where these are and setting out to find them. Instead, individuals that find themselves in places that are too dry or too light simply start moving about randomly. The drier or lighter the area they encounter, the faster they move, the damper or darker the area, the slower they move. When they reach a place that is sufficiently damp and dark, they stop moving altogether. Thus, like the marble in the bottom of the bowl, woodlice end up in damp, dark places simply because that is where they stop moving about.

Burrowing behaviour in digger wasps

Females of the great golden digger wasp (Sphex ichneumoneus) dig a burrow in the ground which they provision with paralysed katydids (relatives of grasshoppers) as food for their larvae. Burrows consist of a main shaft with one or more side tunnels branching off. At the end of each side tunnel the female excavates a nesting chamber in which she lays a single egg (Fig. 1.1a). When she has completed one burrow, the female moves off to start digging another. But how does she know when a burrow is complete? Does she have some model she is working to, or does she follow a simple rule such as, say, ‘dig downwards for t minutes then along for t′ minutes’ which produces the required design without any working blueprint? To find out, Jane Brockmann manipulated the depth of digger wasp burrows during their excavation to see how females responded (Brockmann 1980).

Brockmann found that if she artificially lengthened the main shaft so that it was deeper than the wasps would normally dig, females backed up the shaft to the appropriate level for the side tunnel and filled in the excess depth as they went. If a wooden or plastic extension shaft was added to a burrow in progress, wasps reduced their excavation to compensate. Moreover the degree of reduction could be manipulated by varying the length of extension shaft (Fig. 1.1b). This suggests that females registered and were satisfied with the modified shafts despite not having completed the excavation themselves. When the extension was removed, however, they resumed digging. This combination of digging 1.1 ⁿ What is behaviour? x ₅

Figure 1.1 (a) Diagram of the nesting burrow of a great golden digger wasp (Sphex ichneumoneus); (b) when bur-rows are artificially lengthened by placing blocks on top of the entrance, wasps reduce their excavation accordingly.

After Brockmann (1980).

AB_C01.qxd 9/17/07 8:00 PM Page 5

and filling in response to different experimental manipulations is consistent with the wasps having some criterion for deciding when a burrow is finished and moving on to the next. Such responses are suggestive of goal-directed burrowing behaviour, perhaps based on some set point mechanism for gauging depth (Brockmann 1980).

Nest-building in domestic hens

A completely different picture emerges when we look at nesting behaviour in domestic hens (Gallus gallus domesticus). Hens go through a well-defined series of activities dur-ing nest-builddur-ing, from scrapdur-ing a shallow depression in the ground to placdur-ing nestdur-ing materials around the edges. Do hens have the finished product of a nest as a goal to head for as the digger wasps seem to with their burrows? A study by Hughes et al. (1989) suggests not. Hughes et al. presented hens with three different types of nest: (a) a flat litter surface, (b) a pre-formed hollow nest and (c) a pre-formed nest with an egg. If a fully formed nest was the goal of building activity we should expect hens to show less building with nest types (b) and (c) than with nest type (a) because the job is essentially done in the first two cases. Somewhat surprisingly, however, Hughes et al. found that the amount of nest-building by hens was in fact greater with nest types (b) and (c), with hens taking longer to reach the egg-laying stage after entering the nest area (Fig. 1.2).

This suggests that nest-building is driven by factors other than the functional con-sequences (a complete nest) of the behaviour and that it is the performance of the behaviour itself that matters to the animal. In this and its dependence on an appropriate environment (no pre-formed nest available) for the right outcome, the hens’ response is more in keeping with a goal-seeking system than a goal-directed one (the hen behaves

Figure 1.2 Domestic hens (Gallus gallus domesticus) spend more time nest-building and thus take longer to lay eggs after enter-ing a nestenter-ing area if they are presented with pre-formed nests, especially if these already have an egg. Nest types: A – litter surface only; B – pre-formed nest; C – pre-formed nest with egg. See text. After Hughes et al.

(1989).

along the lines of ‘keep adding bits of nesting material until it’s time to lay an egg’ rather than ‘add bits of nesting material until the structure looks like a nest’).

1.1.2.2 Purpose and mind

While there may be several different ways of generating the same purposeful outcome, there is also a hierarchy of potential decision-making processes by which animals might arrive at their choice of behaviour. The hierarchy is one of increasing sophistication in the scope and flexibility of choice, and thus justification for thinking in terms of ‘mind’

and ‘intelligence’ as opposed to pre-programmed stimulus–response relationships.

Dennett (1995) captures this, again schematically, in his so-called ‘Tower of Generate-and-Test’ (Fig. 1.3). In Dennett’s scheme, organisms face various problems of survival and reproduction set by the environment and have to come up with appropriate solutions from a battery of options available to them. The ‘Tower of Generate-and-Test’ envisages four levels of complexity by which choices might be made.

1.1 ⁿ What is behaviour? x ₇

Figure 1.3 The levels of Dennett’s ‘Tower of Generate-and-Test’. In each case there is a range of possible solutions to problems of survival and reproduction set by the environment, but organisms at each level of the hierarchy arrive at one of them by different means. In Darwinian creatures (a), natural selection chooses between different genetically encoded options. In Skinnerian creatures (b), individuals arrive at a choice by trial and error learning. Popperian creatures (c) also choose by a trial and error process, but this is in the form of internalised hypothesis testing.

Gregorian creatures (d) are like their Popperian predecessors, but hypothesis testing is now aided by cultural tools. See text. After Dennett (1985) Darwin’s Dangerous Idea by Daniel C. Dennett (NY: Simon and Schuster, 1995, pp. 374–8).

AB_C01.qxd 9/17/07 8:00 PM Page 7

Hard-wired solutions: ‘Darwinian creatures’

At the simplest level, decisions are genetically hard-wired (what we shall later [Chapter 5]

call ‘developmentally fixed’), so that each decision is an inflexible property of a particular genotype. A variety of candidates is generated by mutation and (in sexually reproducing organisms) recombination and outcrossing. Candidate decision-makers compete for resources and the most effective genotypes reproduce to make it down the generations.

These are Dennett’s ‘Darwinian creatures’, products of natural selection between altern-ative, inflexible, genetically encoded responses. To pursue (now hypothetically) our example of nest-building hens, this would mean that hens inheriting different versions (alleles) of a putative nest-building gene would build nests in the one particular way encoded in their genotype which would be inflexibly different from the way hens with other genotypes built their nests.

Reinforcement and learning: ‘Skinnerian creatures’

In time, after many generations and varieties of innovative, hard-wired solution, the Darwinian process throws up a chance novelty that takes things to the next level of Dennett’s scheme: phenotypic plasticity. Here, choices are still genetically encoded but the coding allows for a variety of responses. There is thus more opportunity to hit on a good solution, but the advantage over pure ‘Darwinian creatures’ is not very great unless there is a means of biasing choice in favour of the more effective options. The advent of a reinforcer of some kind (see Box 6.1), a mechanism that increases the likelihood of a good solution being tried again next time, does the trick. Now organisms have conditionable flexibility and become Dennett’s ‘Skinnerian creatures’, named after the famous learning theorist B.F. Skinner (see 6.2.1.2). A ‘Skinnerian’ hen might winnow down her range of nest-building moves according to their contribution to a sense of support. Moves increasing the feeling of support would be repeated next time, and those that did not would be abandoned.

Hypothesis-testing: ‘Popperian creatures’

Conditionable flexibility is a useful advance over the rigid single option of the ‘Darwinian creature’, but it is still a very inefficient way to proceed. It is far better to avoid mistakes altogether, or at least reduce their performance costs, by thinking through available options first and dispensing with those that are obviously useless. To paraphrase the philosopher of science Sir Karl Popper, it is better to let your hypotheses die in your stead (Dennett 1995). ‘Popperian creatures’ have the edge over their ‘Skinnerian’ precursors because they have a better chance of choosing the best option at the outset. However, the ‘Popperian’ process presupposes some elaborate internal machinery for storing, sifting and integrating information as well as a means of modelling the world and testing possibilities against the model’s predictions; in other words it assumes a certain level of cognitive processing. In terms of our nest-building example, a ‘Popperian’ hen would view the problem in hand, consult its memory of past approaches and outcomes and select the approach most likely to complete the task effectively.

Cultural enhancement: ‘Gregorian creatures’

Dennett envisages a stage beyond his ‘Popperian creatures’, a stage informed and assisted by a cultural environment (see 12.1). The inhabitants of this level he calls ‘Gregorian creatures’ after the psychologist Richard Gregory. Gregory’s thesis is that cultural artefacts are not just a result of intelligence but in many cases endow intelligence by providing

new means of choosing appropriate responses. Gadgets such as lathes and computers potentiate clever options that could never be realised in their absence. But cultural

‘tools’ are not limited to physical artefacts. As Gregory (1981) and others have argued, language, one of the consummate skills of our own species, can be considered a cultural facilitator of new intellectual possibilities (11.3.2). Indeed, some view language as the principal driving force in the evolution of intelligence (Dennett 1995). ‘Gregorian creatures’

thus have an additional armoury that can be focused on problems and their potential solutions and gain a cultural boost over their ‘Popperian’ rivals. In our nesting hen, a

‘Gregorian’ builder might glean some tips by watching the hens around her and incorporate the acquired information into her own repertory of options.

The ascent of Dennett’s tower is one of gradual emancipation from rigid pre-programmed responses to a flexible, higher-level choice of options which depends on a host of contingencies and a carefully integrated bank of information. The complex on-board computer of the brain, rather than simple neural circuits, assumes responsibility for translating incoming information into suitable action, aided in its task in ‘Gregorian creatures’ by the collective intelligence of culture. We, of course, appear to be the most sophisticated ‘Gregorian creatures’. Our culture has an evolutionary life of its own, one that is many times faster than the neoDarwinian process from which it arose (12.1).

The ability of culture to invent and propagate mind tools that themselves accelerate the pace of change partly explains this. But the positive feedback effect is enhanced by the fact that our on-board computer is an elaborate problem-solving machine honed by natural selection to aid survival in a diverse and changeable environment. One of its key propensities is to set goals and achieve them, but, as we have seen in our discussion of goal directedness, this propensity may be brought to bear inappropriately when reflecting on the problem-solving mechanisms of other species.

Of course, McFarland’s and Dennett’s distinctions are crude categorisations for the purpose of illustration. Nevertheless they highlight the important point that much may be hidden within an observed behaviour. A variety of mechanisms and processes can produce the same apparent outcome and some deft investigation may be necessary to discover which of the possibilities it is. Which behaviours are goal-directed and which merely goal-achieving? Which are the result of ‘Popperian’ choice and which of the ‘Skinnerian’ or first-order ‘Darwinian’ variety? How sophisticated are models of the world in ‘Popperian’

and ‘Gregorian’ heads? We shall see what progress has been made in this respect in later chapters. First we must look at questions about behaviour from a different perspective.