In this chapter, we explore the concept of self-control through a comparative and evolutionary perspective, we discuss how it is measured, and we outline the mechanisms that underlie this capacity (i.e., motivational factors, cognitive control, perception and learning, grit or perseverance, inhibition, as well as choice and commitment). An important concept addressed herein is the distinction between behavioral inhibition and self-control as related yet separate terms. In this endeavor, we briefly review tests of behavioral inhibition (e.g., the detour task, reverse reward contingency task) and self-control (working for more, intertemporal choice, delay of gratification, exchange, tool use, and sequenced travel tasks), outlining how these tasks shed light on the different mechanisms underlying inhibition versus self-control. We also discuss the role of control mechanisms within executive function tasks, such as the Stroop test, and how performance in these tasks is reflective of varying degrees of self-regulation and inhibition.

Metacognition, or thinking about thinking, can adaptively modulate cognitive processing. For example, a student preparing for an exam may introspectively evaluate what she knows well already so that she can allocate more time to studying material she does not know as well. Such metacognition involves feedback between metacognitive monitoring, which assesses the current state of cognition, and metacognitive control that effects changes in cognitive processing. Some interesting and complex forms of cognition likely involve metacognition. Metacognition is also linked to explicit memory, executive control, theory of mind, consciousness, and other phenomena central to cognitive science. Like learning, memory, and cognition, metacognition is likely present in at least rudimentary forms in some animals other than humans. Information about the extent to which metacognition occurs in animals other than humans informs our understanding about the evolution of cognition. Metacognitive monitoring likely evolved because it supports effective metacognitive control.

Decades of research contend with the notion that animals come prepared by evolution to learn about some stimuli and responses better than others. Biological preparedness – and contrapreparedness – can influence how potential information is acquired, processed, and used in decision-making. Theory predicts that preparedness is the result of patterns of reliability of stimuli in predicting reward across the evolutionary history of the lineage. The evolution of preparedness can be tested experimentally, and also by considering the natural history and the pattern of reliability of stimuli and rewards for a given species. We present predictions as well as explanations for how evolution can prepare animals to make choices about their environment. Why animals learn some things better than others is at the heart of what makes behavior adaptive and by working from relatively simple theory it is possible to directly test these hypotheses and analyze traits both underlying and evolving with prepared learning.

In his Nichomachean ethics, Aristotle suggested that absolute judgments precede relative judgments. This chapter places this notion in an evolutionary context by centering on comparative research on successive negative contrast (SNC). SNC occurs when a downshift from a more preferred to a less preferred reward deteriorates behavior. SNC is observed in experiments with mammals, but not in experiments with goldfish (bony fish), toads (amphibian), or turtles (reptile). Pigeons and starlings (birds) have produced a mixed set of results. Since E. L. Thorndike, an understanding of animal learning has been influenced by the notion that rewards strengthen behavior and nonrewards weaken behavior — the strengthening/weakening principle.Outcomes fitting this principle provide evidence of control by absolute reward value, whereas results that violate this principle, like SNC, suggest control by relative reward value. Comparative research suggests that absolute reward effects are more general than relative reward effects.

Integrating an appreciation of natural behavior into laboratory studies, and laboratory techniques into field studies allows researchers to examine and control proximate factors while identifying adaptive problems faced by particular species. This focus reveals both important similarities and differences across phylogenetic lineages. Carnivores other than canids have been relatively neglected in the study of cognition. An examination of members of the ursid family reveals the important role of foraging ecology in shaping learning and memory in both wild and captive settings. Whereas top-down approaches tend to be anthropocentric, a bottom-up approach focused on the unique capacities and traits of individual species bears the most fruit in terms of understanding the selective pressures responsible for the emergence and maintenance of those traits.

Memory is encoded in the neuronal circuit, which undergoes continuous development driven by everyday experiences. While synaptic plasticity allows the experience-dependent modifications of the existing circuit, another essential issue is to keep the existing memory stable while simultaneously facilitating new memory formation for the novel experiences. Apparently, epigenetic regulatory mechanisms are involved in such regulation. Memory engram neurons in the brain are the hubs of the memory circuit and provide the cellular representation of specific memories. The cellular mechanisms, including epigenetic regulators, thus govern the development of neuronal circuits to store the information. Various epigenetic regulators control the landscape of information storage in the neural network in a temporal-spatial-specific manner, but regulating molecules do not code the specific content of the information. The main effects of epigenetic regulation include the gating mechanism and the stabilization mechanism to alter the ability of subneuronal networks to encode new information and preserve stored information in the memory circuit during the experience-dependent development of the brain network.

Although reductionistic studies of mechanisms of learning in a broad range of model species have advanced our understanding of neural mechanisms, our integrated understanding of mechanisms, behavior, ecology, and evolution of learning remains patchy. A more wholistic research approach in a model lineage of species related to the sea hare, Aplysia californica, has revealed a complete loss of mechanisms of sensitization in one sea-hare genus, Dolabrifera, with concomitant changes in its behavior and ecology. A partial loss of sensitization via different mechanisms in a sister genus, Phyllaplysia, provides further information for our evolving understanding of the evolution of learning and memory. Does a relatively specific “change in diet” hypothesis, or a more universal “generalist versus specialist” hypothesis better predict the patterns? Further analyses of sensitization in a half-dozen additional sea-hare genera will distinguish the predictive powers of these and other synthetic evolutionary theories.

Memory provides information for decision making and determines partly what animals can and cannot do. Here we categorize memory systems in animals in terms of their generality and their temporal characteristics, and we explore how evolution has tailored memory systems, considering both the benefits of having access to information and the costs of acquiring and remembering information. General associative memories are flexible and can last for years. In contrast, general short-term memories decay rapidly. We find no evidence of general memory systems used to store sequences of stimuli faithfully. Importantly, seeming limitations of general memory systems may be adaptive as they minimize storage and learning costs. In addition to general memory systems, animals have evolved specialized memories when they need more faithful or longer-lasting memories than afforded by general memory systems. We discuss the consequences of these findings for animal cognition research.

It is a traditional hope of comparative psychology that animal minds might be unitary, parsimonious, associative. In contrast, cognitive researchers acknowledge multiple learning systems, including humans’ capacity for explicit hypothesis testing and rule learning. The authors describe new paradigms that may dissociate the explicit from the associative and demonstrate animals’ explicit capabilities. These paradigms include matched tasks that foster explicit or associative category learning, and paradigms that disable crucial components of associative learning. Given this disabling, animals may adopt instead an alternative, more explicit learning system. The authors review this area, including research on humans, monkeys, rats, and pigeons. They also consider the evolutionary and fitness factors that might favor the development of complementary associative and explicit learning systems.

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.