15-1 The Nature of Thought

Studying abstract mental processes such as thought, language, memory, emotion, and motivation is tricky. They cannot be seen but can only be inferred from behavior and are best thought of as psychological constructs, ideas that result from a set of impressions. The mind constructs the idea as being real, even though it is not tangible.

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We run into trouble when we try to locate constructs such as thought or memory in the brain. That we have words for these constructs does not mean that the brain is organized around them. Indeed, it is not. For instance, although people talk about memory as a unitary thing, the brain neither treats memory as unitary nor localizes it in one particular place. The many forms of memory are each treated differently by widely distributed brain circuits. The psychological construct of memory that we think of as being a single thing turns out not to be unitary at all.

Assuming a neurological basis for psychological constructs such as memory and thought is risky, but we certainly should not give up searching for where and how the brain produces them. After all, thought, memory, emotion, motivation, and other such constructs are the most interesting activities the brain performs.

Section 14-1 details types of memory, Section 14-4 how neuroplasticity contributes to memory processing and storage.

Psychologists typically use the term cognition (knowing) to describe thought processes, that is, how we come to know about the world. For behavioral neuroscientists, cognition usually entails the ability to pay attention to stimuli, whether external or internal, to identify stimuli, and to plan meaningful responses to them. External stimuli cue neural activity in our sensory receptors. Internal stimuli can spring from the autonomic nervous system (ANS) as well as from neural processes—from constructs such as memory and motivation.

Characteristics of Human Thought

Human cognition is widely believed to have unique characteristics. One is that human thought is verbal, whereas the thought of other animals is nonverbal. Language is presumed to give humans an edge in thinking, and in some ways it does:

The appearance of human language correlates with a dramatic brain size increase; see Section 2-3. Section 10-4 explains foundations underlying all languages.

Before you accept the linguists’ position, review Focus 1-2, featuring the chimp Kanzi.

Linguists argue that although other animals, such as chimpanzees, can use and recognize vocalizations (about three dozen for chimps), they do not rearrange these sounds to produce new meanings. This lack of syntax, linguists maintain, makes chimpanzee language literal and inflexible. Human language, in contrast, has enormous flexibility that enables us to talk about virtually any topic, even highly abstract ones like psychological constructs. In this way, our thinking is carried beyond a rigid here and now.

Neurologist Oliver Sacks illustrated the importance of syntax to human thinking in his description of Joseph, an 11-year-old deaf boy who was raised without sign language for his first 10 years and so was never exposed to syntax. According to Sacks:

Joseph saw, distinguished, used; he had no problems with perceptual categorization or generalization, but he could not, it seemed, go much beyond this, hold abstract ideas in mind, reflect, play, plan. He seemed completely literal—unable to juggle images or hypotheses or possibilities, unable to enter an imaginative or figurative realm. . . . He seemed, like an animal, or an infant, to be stuck in the present, to be confined to literal and immediate perception. (Sacks, 1989, p. 40)

Language, including syntax, develops innately in children because the human brain is programmed to use words in a form of universal grammar. But in the absence of words—either spoken or signed—no grammar can develop. Without the linguistic flexibility that grammar allows, no “higher-level” thought can emerge. Without syntactical language, thought is stuck in the world of concrete, here-and-now perceptions. Syntax, in other words, influences the very nature of our thinking.

In addition to arranging words in syntactical patterns, the human brain has a passion for stringing together events, movements, and thoughts. We combine musical notes into melodies, movements into dance, images into videos. We design elaborate rules for games and governments. To conclude that the human brain is organized to chain together events, movements, and thoughts seems reasonable. Syntax is merely one example of this innate human way of thinking about the world.

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We do not know how this propensity to string things together evolved, but one possibility is natural selection: stringing movements together into sequences is highly adaptive. It would allow for building houses or weaving threads into cloth, for instance.

Figure 11-2 diagrams the frontal lobe hierarchy that initiates motor sequences.

William Calvin (1996) proposed that the motor sequences most important to ancient humans were those used in hunting. Throwing a rock or a spear at a moving target is a complex act that requires much planning. Sudden ballistic movements, such as throwing, last less than an eighth of a second and cannot be corrected by feedback. The brain has to plan every detail and then spit them out as a smooth-flowing sequence.

Today, a football quarterback does just this when he throws a football to a receiver running a zigzag pattern to elude a defender. A skilled quarterback can hit the target on virtually every throw, stringing movements together rapidly in a continuous sequence with no pauses or gaps. This skill is uniquely human. Chimpanzees can throw, but their throws are inaccurate. No chimpanzee could learn to throw a ball to hit a moving target.

The human predisposition to sequence movements may have encouraged language development. Spoken language, after all, is a sequence of movements involving the throat, tongue, and mouth muscles. Viewed in this way, language is the by-product of a brain that was already predisposed to operate by stringing movements, events, or even ideas, together.

A critical characteristic of human motor sequencing is our ability to create novel sequences with ease. We constantly produce new sentences. Composers and choreographers earn their living making new music and dance sequences. Novel movement or thought sequences are a product of the frontal lobe.

People with frontal lobe damage have difficulty generating novel solutions to problems. They are described as lacking imagination. The frontal lobes are critical not only for organizing behavior but also for organizing thinking. One major difference between the human brain and other primates’ brains is the size of the frontal lobes.

Neural Unit of Thought

What exactly goes on within the brain to produce what we call thinking? Is thought an attribute exclusive to humans? Before you answer, consider the mental feats of Alex the parrot, profiled in Comparative Focus 15-2, Animal Intelligence.

Alex’s cognitive abilities are unexpected in a bird. In the past 40 years, the intellectual capacities of chimpanzees and dolphins have provoked great interest, but Alex’s mental life appears to have been just as rich as the mental life of those two large-brained mammals.

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The fact that birds are capable of thought is a clue to the neural basis of thought. A logical presumption may be that thinking, which humans are so good at, must be due to some special property of the massive human neocortex. But birds do not possess a neocortex. Rather, they evolved specific brain nuclei that function much as the layers of the human cortex do. This organizational difference in the forebrain of birds and mammals implies that thinking must be an activity of complex neural circuits, not of some particular brain region.

The idea of neural circuits is the essence of Donald Hebb’s (1949) concept that cell assemblies (networks of neurons) represent objects or ideas, and the interplay among the networks results in complex mental activity such as cognition. Connections among neurons are not random but rather are organized into systems and subsystems. Thinking must result from the activity of these complex neural circuits. One way to identify their role is to consider how individual neurons respond during cognitive activity.

William Newsome and his colleagues (1995) took this approach in training monkeys to identify apparent motion in a set of moving dots on a television screen. The Procedure section of Experiment 15-1 on page 524 shows how the researchers varied the difficulty of the task by manipulating the number of dots that moved in the same direction. If all the dots move in the same direction, perceiving the whole array as moving is very easy. If only a small percentage of the dots move in the same direction, however, perceiving apparent motion in that direction is much more difficult.

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COMPARATIVE FOCUS 15-2

Animal Intelligence

Intelligent animals think. We all know that parrots can talk, but most of us assume that no real thought lies behind their words. An African grey parrot named Alex proved otherwise. Irene Pepperberg, pictured here with Alex, studied his ability to think and use language for more than three decades (Pepperberg, 1990, 1999, 2006).

A typical session with Alex and Pepperberg proceeded roughly as follows (Mukerjee, 1996): Pepperberg would show Alex a tray with four corks. “How many?” she would ask. “Four,” Alex would reply. She then might show him a metal key and a green plastic one.

“What toy?”

“Key.”

“How many?”

“Two.”

“What’s different?”

“Color.”

Alex did not just have a vocabulary: words had meaning to him. He correctly applied English labels to numerous colors (red, green, blue, yellow, gray, purple, orange), shapes (two-, three-, four-, five-, six-cornered), and materials (cork, wood, rawhide, rock, paper, chalk, wool). He also labeled various items made of metal (chain, key, grate, tray, toy truck), wood (clothespin, block), and plastic or paper (cup, box).

Most surprisingly, Alex used words to identify, request, and refuse items. He responded to questions about abstract ideas, such as the color, shape, material, relative size, and quantity of more than 100 objects.

Alex’s thinking was often quite complex. Presented with a tray that contained seven items—a circular rose-colored piece of rawhide, a piece of purple wool, a three-cornered purple key, a four-cornered yellow piece of rawhide, a five-cornered orange piece of rawhide, a six-cornered purple piece of rawhide, and a purple metal box—and then asked, “What shape is the purple hide?” Alex would answer correctly, “Six-corner.”

To come up with this answer, Alex had to comprehend the question, locate the correct object of the correct color, determine the answer to the question about the object’s shape, and encode his answer into an appropriate verbal response. This task was not easy. After all, four objects were pieces of rawhide and three objects were purple.

Alex could not respond just to one attribute. Rather, he had to combine the concepts of rawhide and purple and find the object that possessed them both. Then he had to figure out the object’s shape. Clearly, considerable mental processing was required, but Alex succeeded at such tasks time and again.

Alex also demonstrated that he understood what he said. If he requested one object and was presented with another, he was likely to say no and repeat his original request. In fact, when given incorrect objects on numerous occasions in formal testing, he said no and repeated his request 72 percent of the time, said no without repeating his request 18 percent of the time, and made a new request the other 10 percent of the time.

These responses suggest that Alex’s requests led to an expectation in his mind. He knew what he was asking for, and he expected to get it.

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The African grey parrot Alex, shown here with Irene Pepperberg and a sampling of the items he could count, describe, and answer questions about. Alex died in 2007 at the age of 31.
Wm. Munoz

In fact, a threshold number of dots moving together is required to make directional motion apparent. If too few dots are moving in the same direction, the viewer gets an impression of random movement. Apparently, on the basis of the proportion of dots moving in the same direction, the brain decides whether dots are moving in a consistent direction.

Figure 9-16 locates visual regions V1 through V5 in the occipital lobe.

After the monkeys were trained in the task, the investigators recorded from single neurons in visual area V5. V5 contains cells sensitive to movement in a preferred direction. When vertical movement crosses its receptive field, a neuron that is sensitive to vertical motion responds with a vigorous burst of action potentials. But just as the observer has a threshold for perceiving coherent motion in one direction, so too does the neuron. If at some point the random activity of the dots increases to a level that obscures movement in a neuron’s preferred direction, the neuron will stop responding because it does not detect any consistent pattern.

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So how does the activity of any given neuron correlate with the perceptual threshold for apparent motion? On the one hand, if our perception of apparent motion results from the summed activity of many dozens or even thousands of neurons, little correlation would exist between the activity of any one neuron and the perception. On the other hand, if individual neurons influence our perception of apparent motion, then a strong correlation would exist between the activity of a single cell and the perception.

The results of Experiment 15-1 are unequivocal: the sensitivity of individual neurons is very similar to the perceptual sensitivity of the monkeys to apparent motion. As shown in the Results section, if individual neurons failed to respond to the stimulus, the monkeys behaved as if they did not perceive any apparent motion.

EXPERIMENT 15-1

Question: How do individual neurons mediate cognitive activity?

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This finding is curious. Given the large number of V5 neurons, it seems logical that perceptual decisions are based on the responses of a large pool of neurons. But Newsome’s results show that the activity of individual cortical neurons is correlated with perception rather than perception being the property of a particular brain region.

Figures 9-33 to 9-35 diagram functional columns in occipital and temporal cortices.

Still, Hebb’s idea of a cell assembly—an ensemble of neurons that represents a complex concept—suggests some way of converging the inputs of individual neurons to arrive at a consensus. Here, the neuronal ensemble represents a sensory event (apparent motion) that the activity of the ensemble detects. Cell assemblies could be distributed over fairly large regions of the brain, or they could be confined to smaller areas, such as cortical columns.

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Hebb’s Cell Assembly "Cells that fire together wire together."
“Cells that fire together wire together.” Image from D. O. Hebb (1949). The Organization of Behavior (Figure 9, p. 71). New York: McGraw-Hill.

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Via computer modeling, cognitive scientists have demonstrated the capacity of cell assembly circuits to perform sophisticated statistical computations. Other complex tasks, such as Alex the parrot’s detecting an object’s color, also are believed to entail neuronal ensembles. Cell assemblies provide the basis for cognition. Different ensembles come together, much like words in language, to produce coherent thoughts.

What do individual neurons contribute to a cell assembly? Each acts as a computational unit. As Experiment 15-1 shows, even one solitary neuron can decide on its own when to fire if its summed inputs indicate that movement is taking place. Neurons are the only elements in the brain that combine evidence and make decisions. Neurons are the foundation of cognitive processes and of thought. The combination of individual neurons into novel neural networks produces complex mental representations—ideas, for instance.

15-1 REVIEW

The Nature of Thought

Before you continue, check your understanding.

Question 1

Cognition, or thought, entails the abilities of ____________, ____________, and ____________stimuli.

Question 2

Unlike thought in other animals, humans have the added advantage of ____________, which adds ____________ to thought.

Question 3

The ____________ is the basic unit of thought production.

Question 4

Describe the most important way in which human thought differs from thinking in other animals.

Answers appear in the Self Test section of the book.