12.2: Cognition and Intelligence as Psychological Adaptations

Learning Objectives

1. Explain what is meant by the claim that psychological processes, including intelligence, serve adaptive movement
2. Explain why intelligence and cognition are examples of psychological adaptations
3. Describe some of the environmental regularities, including several universal recurrent relational features of the world, that may have been genetically incorporated into brain organization generating intelligence, including general "fluid" intelligence
4. Describe the brain areas that are involved in intelligence, broadly defined as brain systems that guide behavior toward successful adaptation
5. Describe the role that visualization abilities play in intelligence

Overview

After a general review of cortical functions in the previous section, we now examine higher cognitive functions as modes of achieving biological adaptation to the environment.

Early work by psychologists interested in human intelligence took a practical approach. These psychologists in the first part of the twentieth century focused on the development of methods of measuring intelligence in humans. This approach to the study of psychological attributes is called psychometrics. Though early research emphasized the creation and refinement of intelligence tests, rather than the biological origins and functions of intelligence, psychometric analysis of the performance of large groups of people on intelligence tests (Spearman, 1904, 1925) ultimately led to theories of the structure of human intelligence (Carroll, 1993; Cattell, 1987). These theories are important to biological psychology because they have influenced much of the modern thinking and research on the genetic and brain mechanisms involved in human thinking and intelligence.

More recently, intelligence research by psychologists and neuroscientists has expanded to include the study of brain mechanisms underlying intelligence in humans and in other species. This approach has led to conceptions of intelligence and cognition in a broader biological and evolutionary context. On this view, thinking, intelligence, and language are products of evolution, just like other genetic traits of organisms.

One of the key evolutionary trends responsible for the evolution of intelligence and cognition was genetic incorporation of information about biologically significant regularities of the world into the circuitry and operations of the brain. As a consequence, the brain is equipped with many "cognitive instincts" and innate implicit knowledge about biologically important, enduring regularities of the terrestrial environment, forming the groundwork for much of our genetically evolved intelligence as a species.

This view contrasts with and rejects the "blank slate" view of the mind/brain assumed in the Standard Social Science Model (SSSM), the set of assumptions that much of psychology and the social sciences were founded upon--the view that humans lacked any innate psychological nature and that the mind and brain were essentially blank at birth, leaving it to learning and culture to form human behavior free of genetics and biological evolution. In this chapter, we take a different point of view--that biology, genes and evolution, are the primary determinants of human cognition and behavior, in interaction with learning and cultural influences, which themselves are ultimately biological in nature.

Figure \(\PageIndex{1}\): (Left) Lioness hunting in the Serengeti region of Tanzania. Its mechanisms of sensation and perception, emotion, and intelligence are pitted against these same guidance systems for movement found in its prey. Predator-prey interactions may have been an escalating evolutionary impetus for the development of intelligence in both predator and prey. (Right) A single-celled organism featuring its cilia which it uses to move toward favorable parts of its fluid environment and away from harmful regions, thereby facilitating its adaptation. Approach to beneficial elements of the environment and avoidance of and withdrawal from harmful elements is a primary rule governing guidance systems for movement in all motile species. (Image on left is from Wikimedia Commons, CC BY-SA 2.5 Generic. Caption by Kenneth A. Koenigshofer, PhD. Image on right is from Wikimedia Commons, CC BY SA 4.0 International. Caption by Kenneth A. Koenigshofer, PhD).

Thinking and Intelligence Serve the Adaptive Organization of Movement

When we consider thinking and intelligence from a biological and evolutionary perspective, it is important to ask what functions they perform for the organism. The brain does all kinds of complex processing, but it is important to understand that for that processing to have any effect on the environment, brain activity must ultimately converge onto motor neurons in the spinal cord ("the final common path") that stimulate the muscles to produce movement--behavior (see the chapter on movement). Like every aspect of our psychology and its corresponding brain activity, the function of thinking and intelligence is to generate adaptive behavior, movement, to successfully meet environmental challenges to survival and reproduction and to exploit opportunities, thereby increasing biological fitness.

Consider plants, for a moment. They don't have human-like intelligence or thinking--they don't need to, because they depend very little upon movement for survival and reproduction--instead, water and their source of energy, sunlight, come to them. Yes, plants can move slowly in a limited way, but contrast this with all the complex social behaviors modern humans engage in to just to get food and water--e.g. agriculture, supply chains, plumbing, dams, water companies, shopping). Neither do plants have to flee or hide from predators; they protect themselves with thorns or poisons or simply grow back if partially eaten. Neither do they need to move for reproduction--wind and insects and other animals carry the reproductive cells for them.

But none of this is true for animals. For animals, including the human animal, movement is key to survival and reproduction, and, as noted above, the movement must be guided to form patterns of action that solve adaptive problems and exploit adaptive opportunities. According to Darwin's theory of evolution, which he explained as "descent with modification," the roots of human cognition and intelligence lie deep in our species' evolutionary ancestry. Evidence for this can be found in Darwin's principle of the "continuity of species" applied to psychology, as shown by the great degrees of

Figure \(\PageIndex{2}\): Movement is essential for survival and reproduction in animals. The great Wildebeest migration with over 2 million animals follows the rains to lush new feeding grounds. (Image from Wikimedia Commons; CC BY SA 4.0 International. Caption by Kenneth A. Koenigshofer, PhD).

similarity in the guidance and control systems for movement and their underlying brain mechanisms across mammalian species--for example, all mammals have similar brain structures, including limbic structures and cerebral cortex. All species respond to potentially harmful stimuli with threat, attack, or escape. All mammals respond to sexual signals by moving toward and making contact with their source. Each suggests common behavioral control mechanisms evolutionarily conserved across species

But intelligence also exists in non-mammalian species. Intelligence in distantly related species including some birds, such as Corvids (e.g. ravens, jays, crows) and parrots, and in invertebrates such as the octopus and cuttlefish (Adams & Burbeck, 2012; Mather, 2019; Mather & Dickel, 2017), illustrate convergent evolution, suggesting the high adaptive utility of intelligence in diverse ecological niches. Intelligence and thinking, like all psychological processes, evolved to serve the organization of movement to make behavior adaptive, successful, in the Darwinian struggle for survival and reproduction (Koenigshofer, 2011, 2016).

Cognition and Intelligence are Psychological Adaptations

Intelligence and thinking (i.e. cognition) are psychological adaptations evolved by natural selection over millions of years. A psychological adaptation is a psychological or behavioral trait that has developed through evolutionary processes such as natural and sexual selection and which is encoded into a species' DNA (see Ellis & Ketelaar, 2002). Dicke and Roth (2016) offer a comprehensive definition of intelligence recognizing its role in adaptation to the environment in a wide range of animals and humans:

According to the majority of behaviorists and animal psychologists, ‘intelligence’ can be understood as mental or behavioral flexibility or the ability
of an organism to solve problems occurring in its natural and social environment, culminating in the appearance of novel solutions that are not
part of the animal’s normal repertoire.

By contrast, Colom et al. (2010) define intelligence simply as "a general mental ability for reasoning, problem solving, and learning."

Figure \(\PageIndex{3}\): Because animals cannot photosynthesize, they must move in order to obtain their sources of energy found in plants and other animals--animals which can hide, run, and fight back--unlike the plants' source of energy, the sun. Movement is organized by brain circuitry which has been configured by natural selection over evolutionary time to solve adaptive problems. Here a hyena on the plains of Africa solves the problem of getting sufficient energy to survive and ultimately reproduce its genes. (Image from Wikimedia Commons; CC BY SA 4.0 International. ).

A typical definition of general intelligence shows how intelligence and general intelligence are terms sometimes used interchangeably, even by psychologists. General intelligence is often defined as "ability to reason deductively and inductively, to think abstractly, use analogies, to synthesize information, and to apply that information to new domains" (Gottfredson, 1997; Neisser et al., 1996).

In spite of some differences in definition among researchers, there is unanimous agreement that intelligence and cognition are properties of brain processes which have been shaped and refined over millions of years of evolution. To help us understand human intelligence and cognition and their evolutionary origins, many biological psychologists study these processes in other animals, including apes, monkeys, rats, dogs, parrots, and Corvids, such as ravens, jays, and crows. Animals often surprise us with the sophistication of their emotional sensitivity and their intelligence even though they lack language (Huber & Gajdon, 2006; Wasserman, et al., 2006).

An interesting anatomical feature of the cerebral cortex is what we might call microprocessors or "chips" in the human cortex. These are columnar structures, known as cortical columns, containing approximately 3,000 neurons each. There are approximately 150,000 cortical columns in the human cerebral cortex (Hawkins, et al., 2017) . These structures are very similar from one part of the cortex to another and from one mammalian species to the next and suggest highly generalized computational functions in cerebral cortex, whereas specialized modules or genetically dedicated circuits for processing of emotional and motivational information are localized to subcortical regions of the brain, shared by all mammals (Panksepp & Panksepp, 2000).

Intelligence and cognition (i.e. thinking) are exceedingly complex processes. As a consequence, the brain mechanisms involved in these processes are not well understood. As you can see, even definitions of these processes vary widely in the scientific community. However, all of the definitions above include terms such as reasoning, abstract thinking, insight, or problem solving, processes which themselves are not well defined or clearly understood by psychologists and neuroscientists. This highlights the fact that psychologists and neuroscientists are still in the early stages of gaining a real understanding of how intelligence and thinking work and what neural processes in the brain produce them.

Conditions required for evolution of psychological adaptations

Understanding the evolutionary origins of intelligence and thinking may offer insights about how they work and about their underlying brain mechanisms. First of all, remember the claim made above that intelligence and cognition are psychological adaptations, or more correctly, a collection of psychological adaptations, each evolved by natural selection to process certain types of information in specific ways.

By this reasoning, long-term, across-generation regularities of the world that have adaptive significance should be expected to play a special role in the evolution of the mind/brain. As evolutionary psychologists, Tooby and Cosmides (1992, p. 69), state: “Long-term, across-generation recurrence of conditions ... is central to the evolution of adaptations." And as former Stanford psychologist, Roger Shepard, put it, there has evolved "a mesh between the principles of the mind and the regularities of the world" (Shepard, 1987a). This means that the organization of the mind reflects regularities of the world, because of the fact that natural selection operates on conditions that repeat regularly over long periods of time. In other words, the brain is filled with circuitry that operates by genetically programmed rules derived from information about enduring environmental regularities.

Examples of such long-term regularities or enduring properties of the world are: the widespread presence of environmental stimuli that can damage body tissue; that some things in the environment contain sources of nutrition while others are poisonous; that some potential mates are more likely than others to be healthy and fertile; and so on. In response to biologically important regularities in the world such as these, neural circuitry has evolved in animal and human brains that causes withdrawal from harmful stimuli in response to pain, consumption of sources of nourishment and avoidance of foods that cause illness, and powerful innate drives to mate with sexual partners possessing features indicative of health and reproductive potential (Ellis & Ketelaar, 2002, p. 162; Gangestad & Simpson, 2000).

Figure \(\PageIndex{4}\): (Left) For most people, spiders like this one induce a strong aversive reaction motivating avoidance and withdrawal behavior, an example of a psychological adaptation evolved to protect us from possible poisoning from this class of stimulus. (Right) Humans have evolved a preference for fats, sweets, and salt, a psychological adaptation from the Pleistocene which can be harmful to health if followed too frequently in the modern urban environment full of fast food restaurants--a very different environment from that of our hunter-gatherer ancestors. (Image on left from Wikimedia Commons, CC BY SA 2.0 Generic license. Image on right from Wikimedia Commons, CC BY-SA 4.0 International license. Captions by Kenneth A. Koenigshofer, PhD).

Each of these innate behaviors evolved in response to specific regularities of the world, "recurrence of conditions," that consistently had important adaptive consequences--consequences for survival and reproduction--over countless generations of evolution.

Figure \(\PageIndex{5}\): According to evolutionary psychologists, Cosmides and Tooby (2003), forming and maintaining friendships is important to us today because this was one of many adaptive problems that our human ancestors encountered and had to solve in our Pleistocene past. Friendships led to alliances that were important in securing resources within Pleistocene bands of individuals that depended upon one another for survival. For this reason, we are motivated to find friends and having them feels good, reinforcing the behavior. Information processing by the brain necessary for formation and maintenance of relationships is one of the topics studied by biological psychologists interested in intelligence and social cognitive neuroscience. (Image from Wikimedia Commons, CC BY-SA 2.0 Generic license. Caption by Kenneth A. Koenigshofer, PhD.).

Evolutionary psychologists have identified some additional recurrent problems that had to be regularly solved by our human ancestors: " . . . winning social support from [group] members, remembering the locations of edible plants, hitting game animals with projectiles, …, recognizing emotional expressions, protecting family members, maintaining mating relationships, …, assessing the character [and social valuations] of self and others, causing impregnation, acquiring language, maintaining friendships, thwarting antagonists, and so on" (Cosmides and Tooby 2003, p. 59).

In each case, evolutionary psychologists suspect that brain mechanisms have evolved to contribute to solutions of each of these adaptive problems regularly present generation after generation. On this view, cognition is believed to consist of “many mental rules that are specialized for reasoning about various evolutionarily important domains, such as cooperation, aggressive threat, parenting, disease avoidance, predator avoidance, object permanence, and object movement” (Cosmides & Tooby, 1992, p. 179). But these are not the only kinds of recurrent, across-generation conditions that have been genetically represented by natural selection in brain circuitry. Such regularities can be much more abstract and widely distributed throughout the environment.

Innate (instinctual) Knowledge of Universal Regularities of the World: The Foundations of Intelligence

One approach to understanding the nature and origins of intelligence is the idea that natural selection incorporated information about “general—perhaps even universal—properties” of the world (Shepard, 1992, p. 500) into brain organization over evolutionary time (Shepard, 1992, 1994, 2001). The core idea is that natural selection has selected genes that equip human and animal brains with fundamental information about how the physical world is organized, information that is essential for intelligent adaptation to the environment. This approach also may explain fundamental principles of how our thinking processes are organized and how they evolved.

Consequently, information about these enduring environmental regularities, such as the fact that the sun rises and sets approximately every 24 hours, becomes genetically encoded into genes which organize specific brain circuitry or other properties of the brain. Recall the innate mechanisms of this circadian rhythm in the hypothalamus and pineal glad from the previous discussion of the rest/activity cycle. These rhythms have originated from "genetic or evolutionary internalization" of information about the repeating daily cycle of light and dark into brain organization as a result of natural selection.

Figure \(\PageIndex{6}\): A woman sleeping. She does not know that daily cycles of sleep and wakefulness and other circadian rhythms are the result of genetic internalization over the course of evolution of an enduring regularity of the physical environment, the rotation of Earth on its axis (see text below and the chapter on sleep). (Image from Wikimedia Commons; CC BY-SA 2.0 Generic license. Caption by Kenneth A. Koenigshofer, PhD.).

The genetic internalization of information also exists for spatial intelligence. For example, there are "place cells" and spatial cognitive maps in the hippocampus along with areas of the parietal cortex which play a role in spatial processing. And our internalized concept of time is related to the functional organization of the cerebellum where cells which monitor time have been identified (Irvy, et al., 1989; Irvy & Spencer, 2004; Hayashi, et al., 2014). Other biologically significant regularities of the world, including regularities of the social environmenthave led to the evolution of specific components of social intelligence.

Natural Selection Favored Representations of Abstract Relational Regularities: Evolution of General Intelligence

Causality

Because the world is governed by natural causal laws, cause-effect relations between things regularly occur everywhere in the environment and have consistently existed since the beginning of evolutionary time. Such regularities, though abstract and relational, can drive natural selection (Koenigshofer, 2017; see Cosmides & Tooby, 1992, p. 48; Kaufman et al., 2011, p. 213). From the standpoint of biological adaptation, implicit knowledge about causality allows intelligent creatures to navigate and exploit an enormous variety of complex causal relations which benefit adaptation to the problems and opportunities presented by the environment. A chimpanzee who understands that putting a long stick into a termite hill will cause termites to bite onto the stick gets a lot more juicy termites to eat than a chimpanzee who does not understand this causal relationship (Goodall, 2000). Human understanding of complex causes led to the control of fire, the invention of cooking and agriculture, the construction of shelters and tools, and other innovations making it possible for our species to successfully occupy every region of the planet. At least for the time being.

Figure \(\PageIndex{7}\): Bonobo chimpanzee termite fishing. (Image from Wikimedia Commons; CC BY-SA 3.0 Unported license. Caption by Kenneth A. Koenigshofer, PhD.).

If humans and at least some animals are born with an innate disposition to understand cause and effect, we should expect to find brain structures that play a role in this understanding. In fact, brain imaging studies show that "specific brain networks are involved in the extraction of causal structure from the world" (Fugelsang, et al., 2005, p.45). Some of these studies using fMRI techniques implicate several brain structures including areas in the frontal, parietal, and temporal lobes (Fugelsang, et al., 2005). Bilateral prefrontal cortex activation was seen with tasks requiring logical inference to make a judgement of causation. T

Several other studies also support the hypothesis that extraction of causal structure is an innate property of the brain structures of the visual system (Blakemore, et al., 2001; Fonlupt, 2003; Roser et al., 2005). Perception of causality is immediate like perception of motion or perception of faces suggesting innate mechanisms for perception of causation. Some authors have suggested that the detection of causality may even be served by a specialized brain module for recognizing and understanding causality (Leslie & Keeble, 1987; Scholl & Nakayama, 2002).

The exact brain areas activated during detection of causation depends on a number of factors. Judgments of causality that require integration of a working hypothesis with relevant data activate neural tissue in prefrontal and occipital cortices. Empirical studies, such as those cited above support the theory that information about cause-effect relations has been genetically internalized into the brain and this innate understanding of causality is a highly adaptive component of intelligence.

Predictive Relations (Predictive Co-occurrence of Events)

In addition to causality, it is also an enduring property of the world that some things regularly predict the occurrence of other things (i.e. a growling bear predicts an impending attack, sudden heavy rainfall predicts possible flash flooding, an approaching range fire predicts potential danger). Clearly, predictive relations are present everywhere in the environment. Thus, we should expect that natural selection must have organized internalized brain systems that capture predictive relations between events in the world.

The brain can be characterized as "a probabilistic prediction engine" (Nave, et al., 2020, p. e1542). It is not only evolved for prediction, but to implicitly make probability assessments about how likely its predictions about future are to be true. Predictive relations exist whenever specific events, objects, or situations consistently co-vary or correlate--whenever one thing consistently follows another; for example, think of the CS and US in classical conditioning. After conditioning has occurred, the CS predicts the US. This implicit prediction then controls behavior--the dog salivates immediately after the CS is presented in anticipation of coming food, a response that prepares the dog for the expected arrival of the US. As discussed in the chapter on learning and memory classical conditioning specifically involves the cerebellum, whereas associations, in general, between co-occurring events appears to depend on long-term potentiation (LTP), and corresponding changes at synapses in hippocampus (Oishi, et al., 2019), cerebral cortex (Daw, et al., 2009; De Pasquale, et al., 2014) and other brain regions.

The adaptive significance of this property of general intelligence is hard to overestimate. An innate predisposition built into the brain to search for predictive relations in the environment and to exploit the adaptive information in those relations is an exceedingly powerful cognitive tool for understanding the world.

Figure \(\PageIndex{8}\): Contrasting behaviors to satisfy water needs in two species. The woman uses invention and technology, two products of human intelligence, to provide a more consistent and higher quality water source. (Images from Wikimedia Commons; Elephants drinking; https://commons.wikimedia.org/wiki/F...k,_Kenya_4.jpg ; by CT Cooper; licensed under the Creative Commons Attribution 3.0 Unported license. Woman pumping well; https://commons.wikimedia.org/wiki/F...an_Working.jpg; by Osaba Gerald; licensed under the Creative Commons Attribution-Share Alike 4.0 International license; caption by Kenneth A. Koenigshofer, PhD).

What makes humans so smart?

What makes humans so smart compared to other species on the planet? One key difference between human intelligence and intelligence in non-human animal species is the much higher degrees of abstraction that humans are capable of representing, compared to other animals. The ability of the human brain for high levels of abstraction, setting it apart from the brains of other species, is likely due to the greater complexity of circuits in human cerebral cortex compared to other mammals (recall that only mammals have six layered cerebral cortex and approximately 150,000 cortical columns--discussed above--while non-human mammals have significantly fewer). Humans easily detect highly abstract similarities in the environment compared to non-human animals and are capable of forming highly abstract categories and concepts based on these abstract similarities in properties or functions (Koenigshofer, 2017; Penn et al., 2008).

Research in molecular genetics suggests one possible explanation for how human ability for high levels of abstraction may have come about. Pollard (2009), comparing human and chimpanzee genomes, found “massive mutations” in humans in the “DNA switches” controlling size and complexity of cerebral cortex, extending the period of prenatal cell division in human cerebral cortex by several days compared to our closest primate relatives. Research using artificial neural networks suggests that increasing cortical complexity leads to sudden leaps in ability for abstraction and rule-like understanding of general principles (Clark, 1993), lending further support to the hypothesis that superior ability for abstraction due to cortical complexity may be the key component explaining differences in general intelligence between humans and nonhuman animals (see module on artificial neural networks in this chapter).

The frontal cortex is involved in concrete rule learning. More anterior regions of frontal cortex support rule learning at higher levels of abstraction. These abilities for high levels of abstraction may involve anterior dorsolateral prefrontal cortex in humans (Kroger et al., 2002; Reber, Stark, and Squire, 1998). Along with human language, the exceptional capacity of the human brain for abstraction may explain the unusual achievements of the human species ranging from agriculture, technology and science, to the invention of complex economies and governments (Koenigshofer, 2016, 2017).

Furthermore, cultural transmission of learned information in humans, ranging from books and educational institutions to film and the internet, allows each generation to profit from the accumulated knowledge of prior generations. Cultural transmission, along with cooperative problem solving and development of experts in different fields, creates a kind of group intelligence not typically possible in other species. Of course, human language, spoken and written, plays an enormous role in these shared cognitive processes among humans, perhaps explaining at least in part why language evolved. These considerations bring to the forefront the role of culture in human genetic evolution. Gene-culture coevolution theory proposes a multidirectional coevolution between genes and culture in which culture and human created artifacts such as tools, weapons, clothing, and pottery have driven the last 100,000 years of human evolution (Lloyd & Feldman, 2002; Durham, 1991). This theory also assumes an important role for language in cultural transmission of learned knowledge and behavior. It also postulates existence of hominin biological changes that facilitated development of sophisticated language in humans (Lloyd & Feldman, 2002).

Figure \(\PageIndex{9}\): Scientists seek cause-effect, similarity, and predictive relations between variables. Scientific methods are an example of human general intelligence at its best. Alison Gopnik (2010, 2012) at UC Berkeley has found that young children engage in logical analysis of causation, teasing out causes from non-causal factors, in much the same way that scientists do. (Image from Wikipedia, https://commons.wikimedia.org/wiki/F..._reaction).jpg; by Alenakopytova; licensed under the Creative Commons Attribution-Share Alike 4.0 International license).

Another factor that may contribute to the superior intellectual capacities of humans is the sophisticated control systems in the human prefrontal cortex. Miller and Cohen (2001) proposed that “cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represents goals and means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task.” On their view, the prefrontal cortex (PFC) guides the flow of neural activity in relevant brain areas, which allows for cognitive control of behavior. As they state: "depending on their target of influence, representations in the PFC can function variously as attentional templates, rules, or goals by providing top-down bias signals to other parts of the brain that guide the flow of activity along the pathways needed to perform a task" (Miller & Cohen, 2001).

Goldman-Rakic (1996) proposed that the prefrontal cortex represents information not currently in the environment, creating a "mental sketch pad," to hold visual images in working memory, to represent plans, and to focus attention to intelligently guide thought, action, and emotion. This includes the inhibition of distracting thoughts, actions, and feelings. Although such control does exist to some degree in some non-human animals it is less developed and less influential over behavior than in our own species. The prefrontal cortex is highly interconnected with much of the brain, including extensive connections with other cortical, subcortical and brain stem sites. The dorsal prefrontal cortex is especially interconnected with brain regions involved with attention, cognition and action, while the ventral prefrontal cortex interconnects with brain regions involved with emotion.

Brain Mechanisms, Mental Representations, Relational Reasoning and Intelligence

Research suggests that reasoning requires coding involving neurons in prefrontal cortex. "Reasoning depends on the ability to form and manipulate mental representations of relations between objects and events. . . [and] the integration of multiple relations between mental representations . . .[However,] patients with prefrontal damage exhibited a selective and catastrophic deficit in the integration of relations. . . . The integration of relations may be the fundamental common factor linking the diverse abilities that depend on prefrontal function, such as planning, problem solving, and fluid intelligence" (Waltz et al., 1999, p. 119; fluid intelligence is another term for general intelligence, and is separate from one's store of learned knowledge). These results suggest that although mental models may involve many different brain areas acting together, the prefrontal cortex appears to play a special role in high level abstract reasoning requiring the integration of multiple relations. This may explain why damage in prefrontal cortex "leads to selective decrements in performance on tasks involving hypothesis testing, categorization, planning, and problem solving, all of which involve relational reasoning" (Waltz et al., 1999, p. 119).

Recent research has identified a number of brain structures involved in mental representations of future states of the world, specifically of one's own personal future, goals, and plans, essential for intelligent control of behavior. Prospection is the ability to mentally represent the future. Behaviors controlled by mental anticipation of imagined futures can be called prosponses to distinguish them from responses to stimuli in the present or recent past (such as a CS in conditioning) (Koenigshofer, 2016). According to Spreng et al. (2015), autobiographical planning involves personal plans directed toward real-world goals. These researchers found that autobiographical planning involves "synchronized activity of medial temporal lobe memory structures as well as frontal executive regions, . . . specifically, of the default and frontoparietal control networks. [The default network consists of] the medial prefrontal cortex (PFC), medial parietal cortex, including posterior cingulate cortex (PCC) and retrosplenial cortex (RSC), the posterior inferior parietal lobule (IPL), medial temporal lobes (MTL) [including hippocampus, amygdala, and parahippocampal regions], and lateral temporal cortex. . . [This network is activated] by self-generated thought and active across multiple functional domains including memory, future-thinking, and social cognition" (Spreng et al., 2015).

Functional MRI (fMRI) studies "reveal striking overlap in the brain activity associated with remembering actual past experiences and imagining or simulating possible future experiences" (Schacter, et al., 2012, p. 677-678). Clinical observations are consistent with this hypothesis from fMRI studies. For example, amnesic patients have difficulty imagining the future. Another study of amnesic patients with hippocampal damage revealed impairments when these patients were asked to imagine novel experiences (Schacter, et al., 2012). The abilities for imagining and future-thinking are very important components of human intelligence.

General Intelligence in Humans and Non-human Animals: Neural Correlates

Historically, psychologists have focused on ways of measuring intellectual abilities that are important for success in school. Traditional IQ tests were designed to measure these abilities. As discussed above, one important observation from research based on these intelligence tests is that measures of different intellectual skills are correlated: individuals that do well in one type of intellectual ability tend to do well in all types. These positive correlations among measures of different types of intellectual activity are known among psychologists as "the positive manifold." The "positive manifold" has been interpreted by many psychologists as strong statistical evidence (from the mathematical method, factor analysis; Spearman, 1904) for the general intelligence factor, "g," which exists in addition to more specific intelligences such as verbal fluency and visual-spatial abilities (see models of human intelligence in the next module).

Perhaps unexpectedly, recent research shows that general intelligence (ability to recognize "relations and correlates," according to Spearman,1904, 1925, who originated the concept) is found to some degree in many mammals and even in some birds (Emery & Clayton, 2004). Recent research shows that degrees of general intelligence among mammals is most strongly associated with "the number of cortical neurons, neuron packing density, interneuronal distance and axonal conduction velocity—factors that determine general information processing capacity (IPC), as reflected by general intelligence" (Dicke & Roth, 2016). These researchers compare IPC in various species. They report that: "The highest IPC is found in humans, followed by the great apes, Old World and New World monkeys. The IPC of cetaceans and elephants is much lower because of a thin cortex, low neuron packing density and low axonal conduction velocity. By contrast, corvid [rooks, crows, ravens] and psittacid birds [parrots] have very small and densely packed pallial neurons and relatively many neurons, which, despite very small brain volumes, might explain their high intelligence."

Figure \(\PageIndex{11}\): Size proportion of mature rodent and non-human primate brain as well as developing and mature human brains. Dorsal view of adult mouse (A), rhesus monkey (A), and human brain (B), as well as human fetal brain around mid-gestation (A) and at term (B). (A) The size of human fetal brain already at mid-gestation has reached the size of the adult rhesus monkey brain. Nevertheless, adult rhesus monkey brain is almost 100 times larger than brain of adult mouse. (B) The adult human brain is around 3–4 times larger than newborn brain which size reaches the size of adult chimpanzee brain. Note that the pattern of gyrification (cerebral gyri--the hill portions of the cortical folds) in human newborn brain is close to the one observed in adult. The inlet in the middle of the figure is the integrative photo of all brains shown in A and B that demonstrate their actual proportions (the right brain in the upper row of insertion is from fetus at the beginning of third trimester of gestation). Image and caption from Wikimedia. https://commons.wikimedia.org/wiki/F...00050-g004.jpg; by Ana Hladnik, Domagoj Džaja, Sanja Darmopil, Nataša Jovanov-Milošević and Zdravko Petanjek; licensed under the Creative Commons Attribution 3.0 Unported license).

An approach to individual differences among humans in intelligence involves efficiency of neural processing--higher IQ people show greater processing efficiency (Haier et al., 1992; Van Den Heuvel et al., 2009). Brain imaging studies show that higher IQ individuals show lower brain activation (as indicated by glucose metabolism) than lower IQ individuals when completing the same cognitive task, indicating that individuals with higher intelligence, as measured by IQ tests, do information processing more efficiently, with less expenditure of metabolic energy by the brain, compared to lower IQ individuals whose brains work harder. Haier, et al. (1992, p. 415-416) conclude: "Intelligence is not a function of how hard the brain works but rather how efficiently it works."

Brain processing efficiency may be related to any number of factors: inherited brain circuitry configurations which are more "streamlined" as a result of more efficient neural pruning during brain development (Koenigshofer, 2011, 2016); better conduction over pathways connecting multiple regions of brain; "more long-distance connections that ensure a high level of global communication efficiency within the overall network" (Van Den Heuvel, et al., 2009, p. 7619) and many more. Resting state functional connectivity between bilateral prefrontal cortices encompassing the dorsal attention network and the right insula (salience network) was also associated with intelligence scores."

In humans, general intelligence is heritable and is dependent upon many genes interacting together (Bouchard, 2014). One can wonder whether some of these many genes determining intelligence might hold information about some of the environmental regularities in the world discussed above, including relational regularities such as causality and similarity. This is an area of research wide open for researchers in behavior genetics or cognitive genetics.

When considering human intelligence, the role of language is a significant factor. Much of human thinking involves the use of words. As Dicke and Roth (2016) state, "The evolution of a syntactical and grammatical language in humans most probably has served as an additional intelligence amplifier, which may have [also] happened in songbirds and psittacids" [parrots] as a consequence of convergent evolution--the evolution of similar characteristics in unrelated or distantly related species because of common selection pressures. As mentioned above, the precuneus of the parietal lobe may have played a significant role in the evolution of language by having involvement in the combination of ideas and concepts from different semantic domains (Rabini, et al., 2021).

Studies of brain damaged patients supply further insight into brain mechanisms involved in abstract concept formation and thinking dependent upon language. Patients with one type of frontotemporal dementia (FTD) are particularly impaired "in verbal concept formation (i.e. categorization based on abstract similarities between items). . . [with] especially the left frontal lobe, thought to be involved in abstract word processing (Lagarde, et al., 2015, p. 456).

Another Component of General Intelligence: Visual Imagery and Imagination

Significantly, visual imagery in the mind’s eye can also be employed to mentally test novel combinations of causes and effects, similarity relations, and predictive relations (covariations) to discover new knowledge about hidden causes of events in the world, eventually leading to the creation of sophisticated scientific models of how the world works—human general intelligence at its best (Koenigshofer, 2017). For example, the famous theoretical physicist, Albert Einstein, used mental imagery extensively to do "thought experiments" that played a large role in his formulation of the theories of general and special relativity. Brain imaging studies using fMRI implicate parietal cortex in the use of imagination (Nair et al., 2003). Bruner (2010, p. S84) suggests that “the parietal lobe system ‘forms a neural image of surrounding space’ (Mountcastle, 1995 p. 389),” and perhaps of one’s potential future action in that space. Significantly, parietal cortex has strong linkages with prefrontal cortex forming a frontoparietal network: the inferior parietal lobule (further subdivided into the supramarginal gyrus, the temporoparietal junction, and the angular gyrus, see Figure 14.2.8) is primarily connected with dorsolateral prefrontal cortex (Bruner, 2010; see Figure 14.2.7), associated, in part, with abilities for abstract thought, while upper parietal regions, according to Bruner, are associated in the scientific literature with functions such as abstract representation, internal mental images, “imagined world[s],. . . and thought experiment” (i.e., imagination). Significantly, a number of other research groups using fMRI brain imaging techniques in humans also find evidence of a critical role of the frontoparietal network in human intelligence and general cognitive ability (Colom, et al., 2010; Jung & Haier, 2007; Sripada, et al., 2020; Vendetti & Bunge, 2014; Wendelken, et al., 2017; Yeo et al., 2016).

Figure \(\PageIndex{13}\): Connections of posterior parietal association cortex with dorsolateral prefrontal association cortex. (Image from Wikipedia; https://commons.wikimedia.org/wiki/F...ietal_Lobe.jpg; by Paskari; licensed under the Creative Commons Attribution-Share Alike 2.5 Generic, 2.0 Generic and 1.0 Generic license. Caption by Kenneth A. Koenigshofer, PhD.).

The emergence during human evolution of this visualization ability may help account for the development of modern human cognition, first appearing some 60,000-100,000 years ago (Mellars, 2005). Speculatively, superior abilities for imagination of the type described above might account, at least in part, for human competitive advantage over Neanderthals (Koenigshofer, 2017) perhaps contributing to Neanderthal extinction about 30,000 years ago (Watson and Berry, 2009). Consistent with this view, morphological studies suggest enhanced parietal lobe development in modern humans compared to Neanderthals (Bruner, 2010); by contrast, recent studies show little relative enlargement of the frontal lobes in humans compared to apes (Barton and Venditti, 2013). At least one post-mortem anatomical study of Einstein's brain suggested unusual enlargement of the inferior parietal lobules in parietal lobes along with a number of other atypical features in the occipital lobes, and throughout the cerebral cortex (Chen et al., 2014; see Carrillo-Mora et al., 2015). Another study of Einstein's brain by Falk et al. (2013, p. 1304) reports "Einstein’s brain has an extraordinary prefrontal cortex, which may have contributed to the neurological substrates for some of his remarkable cognitive abilities. The primary somatosensory and motor cortices near the regions that typically represent face and tongue are greatly expanded in the left hemisphere. Einstein’s parietal lobes are also unusual and may have provided some of the neurological underpinnings for his visuospatial and mathematical skills, as others have hypothesized. Einstein’s brain has typical frontal and occipital shape asymmetries (petalias) and grossly asymmetrical inferior and superior parietal lobules" with relative enlargement of the left inferior parietal module. Chen et al., referred to above, found exceptional enlargement of both inferior parietal lobules (which include the supramarginal gyrus and angular gyrus (Figure 14.2.8), involved in multiple functions including number processing, "mentalizing," and spatial cognition) in Einstein's brain compared to controls. Einstein was famous for his use of visualization to explore his ideas in theoretical physics through "thought experiments" in his "mind's eye." Additional evidence regarding Einstein's exceptional parietal lobes was provided by studies of cortical glial cells. A study by Diamond et al. (1985) of Einstein's brain found that the only cortical area of the four cortical areas examined with a greater number of glial cells per neuron, compared to controls, was the left posterior parietal cortex, a finding interpreted by the authors to mean that this area of Einstein's brain must have been exceptionally active during his lifetime.

Figure \(\PageIndex{14}\): Cortical gyri, including the left inferior parietal lobule composed of the supramarginal and angular gyri. (Image from Wikimedia Commons; https://commons.wikimedia.org/wiki/F...al_Surface.png; by John A. Beal, Ph.D.; licensed under the Creative Commons Attribution 2.5 Generic license.

This capacity for visualization permitting mental trial and error likely occurs to some degree in non-human animal species as well. Kohler's (1925/1959) classic work showing the use of "insight" by chimpanzees in problem solving offers evidence for this hypothesis, assuming that insight involves mental trial and error. Additional evidence suggesting mental trial and error in imagination in a variety of animals is provided by experiments showing insight in some orangutans, gorillas, and chimpanzees (Mendes, et al., 2007; Hanus, et al., 2011) and in rooks--birds in the same Corvid family as ravens and crows (Bird & Emery, 2009a, 2009b).

One key feature of more traditional approaches to the study of human intelligence is that they emphasize aspects of human intelligence and thinking, such as language and computation, that are especially important for life in complex modern society. As described in the next module, some psychologists have hypothesized multiple kinds of human intelligence. Others focus primarily on how to measure intelligence, and still others study individual differences in intelligence among people. Because these psychologists tend to be interested in practical application of their tests in school and work settings, they tend to give relatively little attention to theories about the evolutionary origins or biological functions of intelligence. Nevertheless, intelligence tests are very useful predictors of success in environments such as school, military, and work settings. All involve measurement of mental skills important to successful adaptation to the demands of the physical and social environments typical of modern, industrialized societies.

Summary

Intelligence and cognition are complex psychological adaptations involving many different areas of the brain interacting together. Intelligence in the broadest sense involves the formation of sophisticated mental models of the world and how it works. These models include representations of things, events, and the predictive, similarity, and causal relations among them, as well as representations of space and time. Mental models of the physical and social environments permit prediction of future events, providing powerful evolutionary advantage. Mental models include the formation of categories, based on similarities, which allow inferences based on assignment of newly encountered things and events to previously formed categories. Mental models exploit the innate disposition to understand cause-effect relations in the environment, leading to knowledge about what causes what. This knowledge allows manipulation of causes to affect future environmental outcomes toward better adaptation. General intelligence emerges during evolution from genetic internalization of universal, abstract relational features of the world including cause-effect, event covariation, and similarity, each of which plays a role in thought and reasoning about the environment (Koenigshofer, 2017). Spearman (1904, 1925) discovered and was first to describe general intelligence, which he believed consisted of ability to recognize "relations and correlates" in the environment. Another aspect of general intelligence is ability to visualize, to form and manipulate visual images in imagination. This ability may have developed as an exaptation or recruitment of portions of the visual and motor systems, including parietal association cortex. This would allow some visual and motor circuits to form internally generated mental images that can be mentally manipulated to test out probable effects of possible future behaviors before committing to them in the physical world. Because this ability to visualize outcomes in the "mind's eye" is much safer and saves time and calories compared to testing outcomes in actual physical behavior, it is likely that there has been strong selection pressure for ability to manipulate mental images to plan future action. This component of intelligence provides a powerful mechanism for maximizing the adaptive outcomes of behavior and therefore provides enormous selective advantage--a strong impetus for its evolution as a central feature of intelligence (Koenigshofer, 2017).

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Attributions

"Intelligence, Cognition, and Language as Psychological Adaptations," is original material written by Kenneth A. Koenigshofer, PhD, licensed under CC BY 4.0, with the exception of the section titled "Experimental Evidence for Mental Imagery" which is adapted by Kenneth A. Koenigshofer, Ph.D., from Cognitive Psychology and Cognitive Neuroscience, Wikibooks, https://en.wikibooks.org/wiki/Cognit...cience/Imagery; text is available under the Creative Commons Attribution-ShareAlike License

This section was further edited by Alan Keys, Ph.D., Sacramento City College, Sacramento, CA