Intelligence

 Humans, the most numerous large land animal on Earth, exercise an extensive but limited dominance over the surface of the planet’s crust. In the two million or so years in which their genus has existed, they have spread over the Earth’s continents, and have adapted to an astounding array of different environments. The evolution of Homo Sapiens some 250,000-300,000 ybp saw a vast expansion of human knowledge and skills, an expansion which has made humans—at least temporarily—the most advanced species in the biosphere. Through means of society and culture, humans have passed what they have learned (or think they have learned) to those born after them.

The human ability to learn is extraordinary, as we have just seen. Many factors, of course, affect this ability. Key among these is intelligence, one of the more complex subjects in human psychology. It is human intelligence that has given our species the ultimate advantage over the rest of Kingdom Animalia. But the definition of this trait, and the study of how individual humans come to possess it, are areas riven by disputes.

The Many Definitions of Intelligence

In its broadest definition, intelligence might be thought of as the ability to understand a situation, recognize challenges and problems that may be associated with that situation, and take appropriate action in a timely manner to deal with them. (That appropriate action can sometimes be to do nothing.) A team of brain researchers has given a more formal definition:

…‘intelligence’ can be understood as mental or behavioural 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. This includes forms of associative learning and memory formation, behavioural flexibility and innovation rate, as well as abilities requiring abstract thinking, concept formation and insight.¹

It should be noted immediately that there is no universally accepted definition of intelligence. (One indefatigable researcher has found no fewer than 71 different definitions.)² A prominent neuroscientist has noted that most definitions center around the concept of problem solving. As he puts it, “More complex problems require higher levels of intelligence. For example, it requires more intelligence to be able to solve differential equations than simply to be able to add two single-digit numbers.”³  It should also be noted that the definition of intelligence is not limited solely to the ability to master academic subjects. Intelligence has much broader applications.

In 1983 the American psychologist Howard Gardner published his theory of multiple intelligences. Gardner saw nine specialized forms of intelligence, or areas in which different sets of intellectual skills were required. They are as follows:

Verbal-linguistic intelligence

Logical-mathematical intelligence

Spatial-visual intelligence (the ability to think in pictures and visualize possibilities)

Bodily-kinesthetic intelligence (particular to athletics)

Musical intelligences

Interpersonal intelligence (the ability to relate effectively to others)

Intrapersonal (self-examination)

Naturalist intelligence (recognizing and categorizing elements of the natural world)

Existential intelligence (the ability to think about “big” issues)⁴

Gardner’s ideas have come under criticism from many sources. Some see Gardner’s categories as simply a list of different talents people have with the word “intelligence” tied to them. Others contend that Gardner’s ideas are not truly scientific but are rather a neuromyth. One critic defines the term neuromyth as “a commonly accepted but unscientific claim about brain function.”⁵ Gardner’s work, in her view, was based on an understanding of the brain’s physiology that has been superseded, and that his hypothesis is not supported by empirical data.

Gardner’s MI theory was not a neuromyth initially because it was based on theories of the 1980s of brain modularity for cognition, and few researchers then were concerned by the lack of validating brain studies. However, in the past 40 years neuroscience research has shown that the brain is not organized in separate modules dedicated to specific forms of cognition.⁶

I think it would therefore be fair to say that Gardner identified various ways that intelligence is manifested rather than distinct kinds of intelligence that arise from areas of the brain dedicated to these manifestations.

There is a distinction between crystallized intelligence and fluid intelligence. This idea was first formulated by the psychologist Raymond Cattell in 1943. To put it succinctly, crystallized intelligence is the sum of what one has learned and one’s ability to bring this knowledge to bear when required. Fluid intelligence is the ability to deal with novel problems and new situations, situations in which previously learned information cannot be applied. In Cattel’s view, crystallized intelligence can be increased throughout adult life (unless senescence ends this accumulation of knowledge) while fluid intelligence is most critical in childhood and adolescence and plateaus in young adulthood.⁷

Neural Correlates of Intelligence

A great deal of research has been done to determine which areas of the human brain are most closely associated with intelligence. Two brain researchers in the UK, referring to the contention “that the cognitive basis of intelligence is the ability to make fluid or creative analogical relationships between distantly related concepts or pieces of information”⁸, decided to use functional magnetic resonance imaging (fMRI) to examine subjects engaged in tasks requiring the ability to make analogies. Their findings:

An analysis using covariates determined per subject by analogical depth revealed significant bilateral neural activations in the superior, inferior, and middle frontal gyri and in the anterior cingulate/paracingulate cortex. These frontal areas have been previously associated with reasoning tasks involving inductive syllogisms, syntactic hierarchies, and linguistic creativity.⁹

In 2009, a team of neurologists from UCLA published an overview of the ways in which advanced scanning technologies can be used to ascertain intelligence levels in humans. Based on their wide-ranging, multi-sourced research, they attempted to identify those anatomical features of the brain that affect the level of an individual’s intelligence. These scientists stressed that what they were observing were correlations, and that conclusions about the relationship between the brain’s anatomy and human intelligence remain speculative. With these caveats in mind, what factors and brain regions may have an influence on intelligence? One of these is overall brain volume, with important reservations. It is the authors’ opinion that “increased global brain volumes observed in more intelligent individuals may be accounted for by selectively enlarged volumes in brain regions especially relevant for higher cognitive function”.¹⁰ Other regions and factors include the frontal, temporal, and parietal lobes, the hippocampus, the cerebellum, significant volumes of gray matter (particularly in the lateral and medial frontal cortex), cortical thickness, and the thickness of the corpus callosum.¹¹

General Indicators of Intelligence

The rapidity, accuracy, and/or scope of one’s situational awareness, comprehension, knowledge base, and logical abilities are measurable aspects of intelligence, although the methods used to measure them are sometimes controversial. (This discussion is not the place to examine the controversies over these measures.) As we saw, Gardner’s neuromyth gives us an overview of the ways in which humans exhibit intelligence. Looking more deeply, we can say that the ability of a human brain to deal with abstract ideas and the language needed to express them, the ability to command language in general and use it effectively, the ability to reasonably predict immediate outcomes of actions, the ability to apply reason and precedent to novel or unexpected situations, the ability to conceive of possible realities and assess the degree of their probability, the ability to focus on the most salient aspects of a situation or problem, and the ability to adapt quickly to a given set of circumstances are, I think, the foundations of our intellectual prowess.

Overall, the meta-talent of the human species is, as I have already said, its adaptability. Not all individuals will display this quality, but as a collectivity, our ability to change with changing circumstances has been our most vital survival asset. Human intelligence gives us a vast superiority over most living things. Humans, as a group, can often change in something very close to real time (when measured in geological terms). Most living things can only change in evolutionary time, meaning that the processes of natural selection and genetic drift must act with their characteristic slowness to allow them to adapt. Moreover, human intelligence can deal with an impressive variety of challenges. As we have seen, many animals exhibit intelligence. But it is the range and depth of human intelligence that has given us our limited power over the biosphere.

Intelligence, Both Heritable and Malleable

In Volume One (p. 433) we saw there is evidence that, to a degree, intelligence is heritable. The fact of intelligence’s heritability is not really in question, but rather the degree to which it is heritable and the role of environmental/cultural factors in the shaping of intellect. Two neuroscientists researching this issue have arrived at a conclusion that I think warrants attention. They contend that intelligence is the result of the interaction of genetic and environmental factors.

The high heritability of intelligence could have emerged from independent genetic effects, while its high malleability could have arisen from independent environmental effects. However, in isolation, these possibilities have little explanatory value. Accordingly, since intelligence is demonstrably malleable, independent genetic effects cannot possibly run the show. Likewise, since intelligence is demonstrably heritable, independent environmental effects cannot possibly run the show. This leads us to the conclusion that gene-environment interplay is the ring master. [My emphasis.]While seemingly straight-forward, this conclusion has been sublimated by methodological/conceptual biases (the first dibs to genetics) and its elusive nature (the hidden iceberg of interactions). Here, we have presented evidence that the GE solution is theoretically and empirically sound, even though at first glance it seems improbable. Paraphrasing Sherlock Holmes’ maxim: since we have eliminated the now implausible options, whatever remains, however well hidden, must be the truth (or at least a closer approximation).¹²

There has been extensive research done on the degree of genetic influence on intelligence, and although research methodologies have been improved, there is still no definitive answer to the (perhaps meaningless) question, “What is the exact percentage of intelligence accounted for by genetic influences?” A pair of scientists in the UK have looked deeply at this issue, and they report the following:

A.  The degree of heritability is not fixed, but rather increases in a linear fashion over time. It rises from about 20% in infancy to 60% in adulthood. What seems to account for this is something known as genetic amplification. This is to say that genetic propensities in children are amplified by the ways in which these children arrange and organize their environment. The implication, in my view, is that as people mature, and the ways in which they arrange their environments become more elaborate, the more indicative of their genetic inheritance these arrangements become.

B. Genetic differences in intelligence are largely attributable to those genes that influence cognitive abilities such as vocabulary, memory, and the brain’s executive functions. These genes display a high level of pleiotropy [when a single gene can have multiple effects].

C.  Assortative mating has a major impact on intelligence levels. Assortative mating is the tendency of people to marry and mate with people who are similar to them. On the scale in which 0.00 equals no correlation and 1.00 equals absolute correlation, assortative mating for intelligence is about 0.40 for intelligence generally and about 0.50 for verbal intelligence. (By way of comparison, the correlation for height and weight is about 0.20.) Interestingly, there is about a 0.60 correlation for years of education. Further, inbreeding has a negative effect on intelligence.¹³

If, indeed, environmental factors play a role in intelligence, what factors seem to be the most significant ones? A team of medical researchers in India, after studying a large sample of children, came to these conclusions:

In the present study, we found that various environmental factors such as place of residence, physical exercise, family income, parents' occupation and education influence the IQ of a child to a great extent. Hence, a child must be provided with an optimal environment to be able to develop to his/her full genetic potential.¹⁴

Research indicates that adequate early childhood nutrition is an important factor in good cognitive development.¹⁵ The educational level of parents is a factor in their children’s cognitive development.¹⁶ Family stability is also key. A Princeton University study indicates that stability is a major factor in cognitive development. Interestingly, an unstable two parent home is not as good in this regard as a stable single-parent home.¹⁷

It should also be noted that research finds no significant difference between the intelligence of women and that of men. Further, the assertion that one “race” (a specious term, in my view) is naturally intellectually superior to others, is an idea that finds no broad scientific support.¹⁸ And it bears repeating that the assertion that humans “only use 10% of their brain” is complete nonsense.

The Critical Junctures in the Rise of Human Intelligence

In tracing the evolution of the anatomically modern human, the evolution of the human brain, and the rise and manifestations of human consciousness, we have largely traced the rise of human intelligence. Those studying these phenomena have looked for certain critical junctures in the history of intellect’s development. We have already come across Merlin Donald’s hypothesis about the significance of self-triggered recall and rehearsal loop in the evolution of memory (pp. 617-618). As I have already noted, tool making gave a selective advantage to imaginative thinking. Human social life’s increasing complexity worked in a reciprocal way with the evolution of the brain, and the advent of gestural and vocal communication gave a strong selective advantage to those who mastered these skills. We can say that the transition from Homo erectus to Homo sapiens (taking into account the crucial offshoot from erectus of Homo heidelbergensis, the African variant of which might be the true precursor to sapiens) was the biggest juncture of all in the development of human intelligence. We face the world with, essentially, the same sensory and cognitive apparatus with which a Homo sapiens tribe in prehistoric Ethiopia or southern Africa faced it.

Human intelligence was also affected by the oral history and storyteller traditions, which put a premium on training the memory, and the rise of written symbols and the storage of information outside of the human body. Research indicates that reading and writing use existing brain structures, repurposing them. Stanislas Dehaene explains this:

…new cultural inventions such as writing are only possible inasmuch as they fit within our preexisting brain architecture. Each cultural object must find its neuronal niche—a set of circuits that are sufficiently close to the required function and sufficiently plastic to be partially “recycled.” The theory stipulates that cultural inventions always involve the recycling of older cerebral structures that originally were selected by evolution to address very different problems but manage, more or less successfully, to shift toward a novel cultural use.

How can this view explain why all readers possess a specialized and reproducibly located area for a recent cultural invention? The idea is that the act of reading is tightly constrained by the preexisting brain architectures for language and vision. The human brain is subject to strong anatomical and connectional constraints inherited from its evolution, and the crossing of these multiple constraints implies that reading acquisition is channeled to an essentially unique circuit.¹⁹

The evidence shows that even under the constraints imposed by the need to repurpose existing brain anatomy, reading can have a major impact on intelligence. Research on identical twins has revealed that reading improves both verbal and non-verbal cognitive abilities in children.²⁰

Consequences of Intelligence

Our intelligence, as noted, has allowed us to dominate the other animal species, with consequences that are, in the long run, unpredictable. As we will examine more closely in the next volume of this work, human intelligence has created amazingly complex societies and cultures. But these societies and cultures also, almost paradoxically, display the limits and fallibility of human intelligence. Humans have created social and cultural entities that are utterly beyond their ability to fully understand. Individual humans very often find themselves struggling to navigate life in such societies, often overwhelmed by the contradictions and randomness they encounter. We have unintentionally created situations that may be beyond our ability to stabilize or correct. It is the sense among some of us that we will require a non-human intelligence to pull us out of these difficult situations that has given rise to machine “intelligence”—a move which might be even more dangerous than the situations the machines have been devised to rectify.

Moreover, humans have often tended to overestimate their own intelligence. This has led many of them to have an unwarranted sense of certainty. Others have been held back by deficiencies in their intellect, and have often been unfairly dealt with by those taking advantage of these deficiencies. Both in evolution and in everyday human life, intelligence is a survival advantage.

But our intelligence is not absolute, and everywhere we turn, we run into its limits. One of the ways the human mind tries to find these limits and gain control of complex situations is through the processes of reasoning. It is to the operations of reasoning we now turn, mindful that even the most patiently reasoned chains of thought can lead us in unexpected directions—or even dead ends.

1.   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4685590/

2.   https://calculemus.org/lect/08szt-intel/materialy/Definitions%20of%20Intelligence.html

3.  Lee, Daeyeol. Birth of Intelligence: From RNA to Artificial Intelligence (p. 4). Oxford University Press. Kindle Edition

4.    https://www.sciencedirect.com/science/article/abs/pii/S1053811905000819

5.    https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1217288/full

6.    https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1217288/full

7.    https://pmc.ncbi.nlm.nih.gov/articles/PMC11595727/

8.    https://www.sciencedirect.com/science/article/abs/pii/S1053811905000819

9.    https://www.sciencedirect.com/science/article/abs/pii/S1053811905000819

10.  https://pmc.ncbi.nlm.nih.gov/articles/PMC2770698/

11.  https://pmc.ncbi.nlm.nih.gov/articles/PMC2770698/

12.  https://pmc.ncbi.nlm.nih.gov/articles/PMC5754247/

13.  https://pmc.ncbi.nlm.nih.gov/articles/PMC4270739/

14.  https://pmc.ncbi.nlm.nih.gov/articles/PMC5479093/

15.  https://pmc.ncbi.nlm.nih.gov/articles/PMC8839299/

16.  https://www.sciencedirect.com/science/article/abs/pii/S0160289621000817

17. “Family Structure and Stability Effects on Child Cognitive Performance”. Terry-Ann Craigie Center for Research on Child Wellbeing Office of Population Research Princeton University December 31, 2009

18. https://www.scientificamerican.com/article/silicon-valley-is-reviving-the-discredited-and-discriminatory-idea-of-race/

19.  https://pmc.ncbi.nlm.nih.gov/articles/PMC3704307/

20.  https://pmc.ncbi.nlm.nih.gov/articles/PMC4354297/#sec11

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Learning

 The human ability to gather, interpret, and remember aspects of the reality in which they find themselves immersed, and of which they are a part, is key to the survival of both individual humans and the species itself. The acquisition of knowledge includes not only the gathering of facts but also the acquisition of skills necessary for the acquisition of more facts and the performance of tasks which call for the use of these facts. In general terms, the more information a human possesses, and the more skills that human commands, the greater the likelihood of survival and the possibility of reproductive success. The possession of facts and skills allows for an emergent phenomenon to manifest itself in a human mind: a concept of the world and a (partial) understanding of the processes by which it works. The growth of a human’s knowledge and skills base is the general definition of the term learning. The ability of a human to bring this knowledge and these skills to bear in given situations is of crucial importance to that human’s general well-being. As we will soon see, learning involves physical alterations of the brain itself. These alterations manifest themselves as changes in the density of connections between neurons and the establishment of new neuronal pathways, pathways which facilitate the recall of learned knowledge and methods of applying it in real-life situations. Memory and learning are therefore closely connected.

 The Physiology of Learning

 As we have already noted, learning is intimately connected to memory. It is ultimately another example of neuroplasticity, the brain’s ability to physically modify itself. We should note that a full picture of how the brain’s neurons are modified by memory and learning (two of the foundations of cognition) is still being pieced together. Remarkable progress has nonetheless been made in this area in recent times. Technological advances have greatly facilitated this progress. The aim of this research is to understand how patterns of neuronal excitation and inhibition (what neuroscientists refer to as the E:I balance), in combination with patterns of gene expression, cause neuroplasticity to occur. It should be said that inhibition comes from a variety of sources and this has an effect on particular circuits.¹

 The fundamental principle, as we have seen in our examinations of consciousness and memory, is that experience has the ability to cause physical alterations within the brain’s neural circuitry. What is the process by which this happens? First, there must be some form of stimulus that reaches an individual’s senses. As we have seen, this stimulus is converted by the process of sensory transduction into electrical impulses which are then processed in the brain’s association areas. We briefly touched on Associative Memory in the chapter on memory. Now, we will look at those regions of the brain that neuroscientists call the association areas. We looked at these in a general way in our brief introduction to cognition. Now, we will examine their more specific components. Some of these areas are involved with the relationship between stimulus and motor response. Others are primarily oriented toward the processing of language and other symbolic forms of communication.

 Two specialists in brain research characterize the association area in the following manner:

 …higher-order association cortex is characterized by connectivity to association zones located in widely distributed positions throughout the cortex. Association regions in one zone of cortex (e.g. the inferior parietal lobule) will receive and send projections to zones of temporal, prefrontal, and midline association cortex.²

 In effect, the association areas of the brain form a network. As we have already seen, the formation of neural networks among and between cortical areas is a fundamental feature of the human brain. Two Harvard neuroscientists have hypothesized that during the evolution of the brain, the expansion of the association cortex “may have allowed for an archetype distributed network to fractionate into multiple specialized networks.” It is these specialized networks, they contend, that support the various higher order cognitive processes, including language.³

 A neuroscientist studying learning has identified these brain structures as part of the association regions: the medial temporal lobe (especially the hippocampus), motor regions of the frontal lobe (which are crucial in associating visual stimulus with motor response), the prefrontal cortex (also involved in linking visual stimulus to response), and the striatum.⁴ A pair of neuroscientists at Yale describe the striatum as follows:

 The striatum is a critical component of the brain that controls motor, reward, and executive function. This ancient and phylogenetically-conserved structure forms a central hub where rapid instinctive, reflexive movements and behaviors in response to sensory stimulation or the retrieval of emotional memory intersect with slower planned motor movements and rational behaviors…The convergence of excitatory glutamatergic activity from the thalamus and cortex, along with dopamine release in response to novel stimulation, provide the basis for motor learning, reward seeking, and habit formation.⁵

 In regard to those regions of the cortex involved in learning and using language, physiologists have identified regions of the brain’s left hemisphere involved in these processes.

 From different overviews…it is clear that the language-relevant cortex includes Broca's area in the inferior frontal gyrus (IFG), Wernicke's area in the superior temporal gyrus (STG), as well as parts of the middle temporal gyrus (MTG) and the inferior parietal and angular gyrus in the parietal lobe. Within these macroanatomically defined regions, microanatomical subregions can be specified.⁶

More broadly, the physiology of the brain’s language centers allows for language acquisition, the learning of a language. We will examine these structures more closely in the chapter Speech and the Evolution of Language.

As we noted in this chapter’s introduction, learning causes changes in neural interconnectedness. Now we will focus more intently on the processes by which this occurs. We should emphasize that in learning it is the synapse itself that is being strengthened. A psychology professor and brain researcher has explained the phenomenon as follows:

The connections between neurons, through the synapses, however, are constantly changing throughout all of our life and are predominantly responsible for learning and memory in the brain. These changes in connections involve forming new connections, known as synaptogenesis, or strengthening existing connections, known as long-term potentiation (LTP)…

The researcher goes on to say that in laboratory experiments with rats, the rats’ synapses can form “more extensive interconnections between their neurons…with a greater number of synapses” when the rats are given suitable stimulation.⁷

Further, he points to a critical fact: when multiple neurons respond to a stimulus at the same time, the connections between them are strengthened, a hypothesis first proposed by the Canadian psychologist Donald Hebb.

 …Hebb described an important process for learning in the brain, known as Hebbian learning (1949), summed up by the phrase, “neurons that fire together wire together...”Put simply, when two or more neurons respond or fire at the same time (i.e., from some thought, action, or event in the environment) the connection or synapse between them is strengthened, leading to a stronger association. This means that if some situation (or thought or action) is encountered in the future causing one of those neurons to respond, it will now be more likely to trigger a response in the other connected neurons, recalling and further reinforcing that association.⁸

What are the mechanisms of neuroplasticity? Neurogenesis, as we noted above, apoptosis, or programmed cell death, (which we encountered in Volume One), and degrees of synaptic change caused by activity or non-activity. To quote one brain researcher, “Repetitive stimulation of synapses can cause long‐term potentiation or long‐term depression of neurotransmission.” These changes can cause physical alterations in dendritic spines. They can also alter neuronal circuits, and with them, behavior. These processes appear to have a major impact on the brain’s ability to acquire new information, react to quickly changing external circumstances, or recover from injury.⁹

We noted above that gene expression is a factor in neuroplasticity. Specifically, what that means is that there is a reciprocal relationship between synaptogenesis and a person’s genes. Gene mutations can cause errors in synaptic formation. These synaptic errors can in turn hinder neurodevelopment and damage the brain’s normal functions, sometimes very seriously so.¹⁰ In turn, synaptic formations can affect the expression of genes. As one study puts it, “…studies indicate that neuronal activity regulates a complex program of gene expression involved in many aspects of neuronal development.”¹¹

In addition to Hebbian learning, researchers also investigate synaptic scaling. Synaptic scaling refers to the ability of a neuron’s synapses to adjust their rate of firing in order to maintain their homeostatic equilibrium. Research has shown that neurons use calcium-dependent sensors to detect fluctuations in their firing rates. These sensors then allow greater or lesser accumulations of receptors for glutamate (the chief excitatory neurotransmitter) in the synapse.¹² Synaptic scaling seems to be crucial for the storage of associative memories, specifically, the ability of a person to remember important aspects and details of particular events.¹³

In humans there is, of course a relationship between learning and development, a relationship that sheds light on neural plasticity. The human brain has mechanisms that deal with experience-expectant plasticity [neuronal development based on common or nearly universal experiences such as exposure to language], and experience-dependent plasticity [neuronal development specific to the experiences of an individual, development which facilitates the ability to learn throughout life, and development that strengthens or eliminates neural connections]. The two forms of plasticity are deeply intertwined and both influence each other. Experience-dependent plasticity tends to be greater in children than adults, but plasticity in adults takes place in a different context. As one researcher has put it,  

…modifying synapses that are already committed (e.g. learning a motor skill such as juggling) is very different than committing the synapse for the first time (e.g. learning the motor coordination necessary for the first time a baby holds himself up).¹⁴

Researchers are also exploring the structure of the neocortex itself to gain insight into the learning process. One team of researchers, noting the hierarchical arrangement of the regions of the neocortex and the arrangement of cortical neurons into columns, has proposed a hypothesis about how the brain learns to recognize objects. In their words,

We believe each cortical column learns a model of “its” world, of what it can sense. A single column learns the structure of many objects and the behaviors that can be applied to those objects. Through intra-laminar [within layers] and long-range cortical-cortical connections, columns that are sensing the same object can resolve ambiguity.¹⁵

So the sensory stimulus that begins the processes of learning undergoes complex processing in the brain. This processing physically transforms the brain itself. From this, a synergy arises. The more the brain’s synapses are strengthened and the more neuronal circuitry is expanded, the greater the ability of the brain to absorb additional learning, which in turn will cause new waves of synaptic transformation.

Forms of Learning

What are the general ways in which humans learn? Perhaps the most basic one is imitation. How might imitation be defined? One team of researchers has put it this way:

…we use the broadest and simplest definition of imitation as follows—we call an action imitation if there is a relationship between the behaviour of a copier and a model, such that observing the movements of the model causes the parts of the copier's body to move in the same way relative to one another as the parts of the model's body…

In their description of it, imitative behavior is variable. People can use various parts of their body to imitate, such as their hands and faces. They can also imitate using their voices. Their imitations vary in accuracy and can be imitations of things which are new to them or familiar in varying degrees. Imitations can be conscious actions, or they can be spontaneous. And the result of these imitations is unpredictable.¹⁶

In the study of imitation, a major debate is over the issue of when children begin to imitate the actions of others. One researcher in the field of early childhood development contends that no genuine imitation occurs in humans until early in their second year, and that claims of newborns engaging in imitation rest on preformationism, “the view that development is the growth of pre-formed complex structures”. She finds no convincing evidence to support preformationist ideas, and contends that:

…imitation will be the emergent, stable product of the coming together of a range of distinct kinds of knowledge and skill. Such multi-component systems are not deterministic and do not follow a built-in blueprint for the development of behaviours. They are self-organizing and can generate new behaviours through their own activity.¹⁷

And a team of experts in the study of child psychology finds that toddlers can use imitation to communicate with others and are can take steps to ensure others see their imitation.¹⁸

It goes without saying that the ability to imitate is deeply ingrained in the human brain. Brain researchers have identified specific regions of the brain that facilitate imitation.

[The] Human ability to imitate movements is instantiated in parietal, premotor and opercular structures, often referred to as the human homologue of the macaque mirror neuron system…Critically, the activity of the parietal opercula bilaterally was associated with the anatomical compatibility effect. [NB: The anatomical compatibility effect is when a physical response to an observed phenomenon appears to be the most appropriate one, a response that increases with repetition.]  Furthermore, increased activity of the left middle frontal gyrus and right superior temporal sulcus (extending to the temporo-parietal junction) was found in those trials in which the spatial mapping between the seen and executed movements was detrimental for the anatomical task.¹⁹ 

Imitation plays a crucial role in language acquisition, as we will see in detail later. And in general imitation is so pervasive in the human experience that it may be the origin of human communication itself, a topic we will examine in a subsequent chapter.

Humans can also learn by means of conditioning. By conditioning we mean, in its most basic sense, a learned response to a given stimulus. Classical conditioning, also known as associative learning, means getting a subject to give a particular response to a neutral stimulus.  Operant conditioning is getting a subject to associate a given behavior with a specific consequence, either a reward or a punishment of some sort. Rewards naturally tend to increase the behaviors that result in them and punishments tend to decrease behaviors. These rewards or punishments are sometimes referred to as positive or negative reinforcement.

As is the case with imitation, conditioning is a pervasive feature of human life. (Operant conditioning governs much of child raising, for example.) One needn’t fall into the error of thinking that operant conditioning is the only factor that governs human behavior to see that in many cases it influences such behavior. But this influence always falls within a larger cognitive and experiential context.

In a later volume of this work, we will examine how the educational systems in human societies evolved and the methods by which they have attempted to build on the basic foundations of human learning.

The Relation Between Innate Behaviors and Learned Behaviors

There is a distinction between behaviors which require no learning process and those that do. Behaviors that require no learning are called innate. These are genetically-determined behaviors, such as reflexes or other bodily reactions to stimuli. Innate and learned behaviors are usually considered to be distinct, but in recent years many researchers have come to see them as deeply intertwined. There is evidence that certain neural circuits once considered to be innate demonstrate plasticity. It now seems certain that all complex behaviors are a synthesis of innate and learned behaviors, which shape each other in a synergistic fashion.²⁰ We will examine the relationship between genetic predisposition and experience in greater detail in a subsequent chapter.

It is sobering to remember that a great deal of what humans learn is utterly wrong. Humans learn “facts” (such as the belief that there was an actual Noah’s Ark) that bear no relationship to reality. They also learn prejudices. They learn ways to harm others. They learn bad habits and self-destructive behavior. My point is that learning is not always a benign thing, although in fact the vast majority of what humans learn is quite ordinary and mundane. But at its best learning exalts a human being, opening up realms of knowledge that transform them for the better, broaden their outlook on life and the world, give them skills which will prepare them for a variety of tasks, and help them to understand at least something about their place in reality. The learning process is vastly influenced by an individual’s intelligence. It is to the definition and nature of intelligence that we now turn, seeking in them clues to our success as a species. More darkly, we will see how the possession of intelligence is a two-edged sword, enabling us to dominate the world while at the same time giving us the power to destroy it.

1.    https://www.sciencedirect.com/science/article/pii/S0896627319308347

2.    https://www.sciencedirect.com/science/article/pii/S2352154621000772?via%3Dihub

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4.    https://www.sciencedirect.com/science/article/abs/pii/S0079612307000192?via%3Dihub

5.    https://pmc.ncbi.nlm.nih.gov/articles/PMC6656632/

6.    https://journals.physiology.org/doi/full/10.1152/physrev.00006.2011#:~:text=From%20different%20overviews%20(67%2C%20118,gyrus%20in%20the%20parietal%20lobe%20(

7. https://solportal.ibe-unesco.org/wp-content/uploads/_pdfs/neuroplasticity-how-the-brain-changes-with-learning.pdf

8.   https://solportal.ibe-unesco.org/wp-content/uploads/_pdfs/neuroplasticity-how-the-brain-changes-with-learning.pdf

9.   https://pmc.ncbi.nlm.nih.gov/articles/PMC6871182/

10. https://pmc.ncbi.nlm.nih.gov/articles/PMC5095804/

11. https://pmc.ncbi.nlm.nih.gov/articles/PMC2728073/#:~:text=Experience%2Ddriven%20synaptic%20activity%20causes,a%20variety%20of%20neurological%20disorders.

12.  https://pmc.ncbi.nlm.nih.gov/articles/PMC2834419/

13.  https://www.sciencedirect.com/science/article/pii/S0960982221003638#:~:text=Here%2C%20we%20show%20that%20synaptic,memory%20formation%20and%20memory%20generalization.

14.  https://pmc.ncbi.nlm.nih.gov/articles/PMC6871182/

15.  https://pmc.ncbi.nlm.nih.gov/articles/PMC5661005/

16.  https://pmc.ncbi.nlm.nih.gov/articles/PMC6175014/

17.  https://pmc.ncbi.nlm.nih.gov/articles/PMC2865075/

18.  https://www.sciencedirect.com/science/article/abs/pii/S0022096523000309?via%3Dihub#preview-section-introduction

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20.   https://www.sciencedirect.com/science/article/abs/pii/S0166223625000578