In this chapter, I focus on the origins of memory, posing the question of what were the very initial forces that led to the evolution of learning. Although the common answer is that the function of memory is to allow future behavior to benefit from past experiences, I argue that future benefit is too small to overcome the large energetic costs associated with the neural mechanisms that support memory formation. Instead, I advance the hypothesis that memory evolved to solve an immediate problem, the identification of novel biologically significant objects. Although such identification is often attributed to innate recognition, reliance on genetic encoding would require enormous genomic space and would be unreliable when phylogenetically novel but important objects were encountered. Some often-unappreciated features of Pavlovian conditioning make it an ideal mechanism for immediate perceptual identification of biologically important objects. Although episodic memory is most clearly identified with this recognition process, immediate perceptual identification may be a general function of several memory systems.

Animal learning may play several important roles in evolution. Here we discuss how: (1) learning can provide an additional form of inheritance, (2) learning can instigate plasticity-first evolution, (3) learning can influence niche construction, and (4) learning can generate developmental bias. Evidence for these evolutionary effects of learning has accumulated rapidly over the last two decades, yet their significance for biological evolution remains poorly appreciated.

Caenorhabditis elegans is a microscopic, free-living nematode species that has been studied as a model organism for learning and memory. With a nervous system consisting of 302 neurons, its accessible anatomy accommodates an incredible capacity to support a wide range of behaviors to navigate in its surroundings. In this chapter, we review both the classic and cutting-edge studies on learning and memory in C. elegans. These findings illustrate that learning allows C. elegans to adaptively adjust its behaviors to the environment as a result of experiences and plays a key role in promoting the organism’s fitness. Learning and memory in simple organisms like C. elegans is mediated by complex neural and molecular mechanisms. Mechanisms of learning and memory elucidated from C. elegans studies show convergence onto the learning mechanisms discovered in other species, suggesting that a large portion of the neural principles of learning and memory are rooted in evolution.

Incentive salience denotes the biopsychological process that enables reward-related cues to be approached. Accordingly, organisms often prefer a cue predictive of a food reward delivered with certainty over one predictive of the same reward delivered with uncertainty. However, a closer examination of free-choice behavior in various experimental designs suggests that the principle of reward maximization is an oversimplification. In particular, many studies of suboptimal choice (SOC) reveal that organisms exposed to conditioned stimuli may prefer a food option associated with a lower total amount and a lower probability of food to the more profitable alternative option. In this chapter, I argue that SOC illustrates one important fact: reward maximization can be a correlate of choice behavior but it is not its cause. Instead, organisms track the cues that reliably predict food delivery, independent of the amounts received or the probability of being rewarded. I show how to understand this process in psychological terms and also why this view may make more sense than reward maximization from an evolutionary perspective.

In the mid-1970s, I joined the first cohort of students studying biology at the newly founded university in Bielefeld. In those days there were only about 30 to 40 of us students and about three professors, one of whom was Klaus Immelmann. Professor Immelmann had recently been called to serve as the first chair for animal behaviour at a German university, and his goal was to make Bielefeld a hub of behavioural biology research and teaching. He quickly succeeded. The facilities in his department were phenomenal, even by international standards. It was an exciting time: the campus was populated by various species of finches, parrots, geese, marmosets, kangaroos, deer, and rodents living in spacious indoor and outdoor enclosures. The founders of behavioural biology, Lorenz, Tinbergen, and von Frisch, had just received the Nobel Prize. There was a spirit of optimism in our eastern province of Westphalia.

In 1975, the American biologist Edward O. Wilson published his foundational work, Sociobiology – The New Synthesis. In it, he coined the term ‘sociobiology’ as a new sub-discipline of behavioural biology based on the groundwork laid years earlier by scientists like William Hamilton and Robert Trivers.

Wilson saw the goal of sociobiology as deciphering the biological basis of all social behaviour of animals and humans alike. By systematically applying the theory of evolution to the social activities of insects, fish, birds, and mammals, sociobiology casts the ways in which animals form relationships, help one another, kill each other, and take on sex roles in a completely different light.

Hardly a day goes by without a news report on the debate over the ethical treatment of animals. Society is increasingly asking questions about what humane treatment looks like: what is the ideal environment for an egg-laying hen? How do polar bears and tigers feel in captivity? Should horses be kept alone in stables, or with other horses? How does a pug feel when its owner goes on holiday and it is left alone?

As we saw in the last chapter, instincts and learning interact in complex ways to produce the characteristic behaviours of each species and individual. So far, we have discussed learning in a broad sense: ducklings learn who to follow after they hatch; zebra finches learn what traits their future mates should have; guinea pigs learn to get along with members of their own species; and vervet monkeys learn which warning call to sound for a leopard and which to sound for an eagle. The pigeons Jack and Jill even learned (with help) to transmit information with symbols so efficiently that it appeared as though they were having a conversation. In this chapter we will take a closer look at which cognitive capacities animals possess: whether they can not only learn but also think, and whether they, like humans, can develop self-awareness.

Questions over the origin of behaviour have troubled science and society for generations. For one, does behaviour arise from instinct, or learning? What role do genes play in behavioural development? How important is environment? Much research has been done on this topic, and there is even more speculation. In recent years, however, new methods from genetic engineering have revealed exciting new answers to the old riddle. But let’s start at the beginning.

A revolution has recently taken place in behavioural biology. Its consequences are far-reaching, both for our self-image as humans and for our relationship with animals. Just a few decades ago, behavioural science was guided by two key dogmas: animals cannot think, and no scientific statements can be made about their emotions. Today, the same discipline holds both ideas to be false and posits the very opposite: animals of some species are capable of insight – they can recognise themselves in a mirror and exhibit at least a basic sense of self-awareness – and they have rich emotional lives that seem to be startlingly similar to those of humans. Situations that lead to strong emotional responses in humans, whether positive or negative – for example, when we fall in love or lose a partner – seem to have the same effect on our animal relatives.