14.4: Cognition- Categories, Concepts, Schemas and the Brain

Learning Objectives

1. Describe cognition.
2. Discuss concepts and prototypes.
3. Explain schemas and how they contribute to the adaptive organization of behavior and its efficiency.
4. Discuss the brain structures involved in category formation.
5. Describe the types of characteristics of things which affect where in the brain their categories are stored.
6. Describe the roles of similarity, prototypes, and typicality in categorization.
7. Explain prosopagnosia.
8. Describe the fuzzy nature of concepts.
9. Explain category hierarchies.
10. Discuss the representation of concepts and knowledge.

Overview

Cognitive psychology is dedicated to examining how people think, including interactions among human thinking, emotion, creativity, language, and problem solving, and how we organize thoughts and information gathered from our environments into meaningful categories. As discussed earlier, the generation of categories, based on similarity, is an example of an ability that has arisen from the genetic internalization, by natural selection, of an enduring fact of the world. That fact is that things in the world are similar to other things, in various properties, and in varying degrees of abstraction (see Section 14.2). A brain unable to form categories would be crippled; every experience would seem unrelated to every other, and the brain's ability to find order in the world would not exist. Much of thinking involves the formation and use of categories. Inferences about the properties of new instances of a category based on knowledge about the category is an essential component of intelligence and thinking in humans and in a number of other animal species. The high level of abstraction that the human brain is capable of provides humans with categories of very high degrees of abstraction, giving great cognitive power to our species compared to other animals. Human concepts can range from classification based on simple concrete properties such as shape or color to high order abstract properties leading to concepts such as mammal, illegal, commerce, electrostatic force, or beauty. Corticostriatal loops involving connections between a number of cortical areas and the striatum, composed of several nuclei of the basal ganglia, appear to be crucially involved in category formation in humans.

Concepts and Prototypes

The senses serve as the interface between the mind and the external environment, receiving stimuli and translating it (transducing it via sensory receptors) into nervous impulses that are transmitted to the brain. The brain then processes this information and uses the relevant pieces to create thoughts, which can then be expressed through language or stored in memory for future use. When thoughts are formed, the brain also pulls information from emotions and memories, powerful influences on both our thoughts and behaviors.

Concepts are abstract representations or cognitive structures formed from classes or groupings of things, events, or relations based on common properties. Concepts can be about concrete things such as the concepts "car," "bird," or "swimming," or about complex and abstract things, like "justice" or "success". In psychology, for example, Piaget’s stages of development are abstract concepts. Some concepts, like tolerance, are agreed upon by many people, because they have been used in various ways over many years. Other concepts, like the characteristics of your ideal friend or your family’s birthday traditions, are personal and individualized. In this way, concepts touch every aspect of our lives, from our many daily routines to the guiding principles behind the way governments function.

A prototype is the best example or representation of a concept. For example, for the category of civil disobedience, your prototype could be Rosa Parks. Her peaceful resistance to segregation on a city bus in Montgomery, Alabama, is a recognizable example of civil disobedience. Or your prototype could be Mohandas Gandhi, sometimes called Mahatma Gandhi. Mohandas Gandhi served as a nonviolent force for independence for India. Prototypes apply to more concrete concepts as well. In your mind, is the prototype bird a penguin, an eagle, a sparrow, or is there some other type of bird that is the best example of the concept, bird? Which of the birds listed in the previous sentence is most typical of the category "birds"? Is "typical" simply a function of frequency of occurrence?

Schemas

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). In other words, a schema is a collection of knowledge and beliefs about some entity or situation that directs behavior and guides expectations. Schemas help organize knowledge and often help us predict event sequences and attributes of things we encounter in the world. For example, the schema "library" suggests the presence of books, desks, shelves, and a quiet place to study. It also suggests a sequence of actions including searching the stacks, selecting a book, and taking the book to a librarian at a check out desk before leaving the library with the book. There are many different types of schemas, and they all have one thing in common: schemas are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed and using this information contained in the schema to organize behavior.

There are several types of schemas. A role schema makes assumptions about how individuals in certain roles will behave (Callero, 1994). For example, imagine you meet someone who introduces himself as a firefighter. When this happens, your brain automatically activates the “firefighter schema” and begins making assumptions and generating expectations (predictions) that this person is brave, selfless, and community-oriented. Despite not knowing this person, already you have unknowingly made judgments and formed expectations about him. Notice how the schema is predictive in the sense that it allows you to form expectations about something in the future, in this case, what behaviors this person might be expected to engage in. A common feature of many forms of cognition, including schemas, is projections or expectations about probable events in future time.

Schemas also help you fill in gaps in the information you receive from the world around you. While schemas allow for more efficient information processing, there can be problems with schemas, regardless of whether they are accurate most of the time: Perhaps this particular firefighter is not brave, he just works as a firefighter to pay the bills while studying to become a children’s librarian. Schemas involve generalization--inference based on prior experience with similar things in the past. Like schemas, all forms of generalization permit prediction allowing us to fill in gaps in our direct knowledge including what might be expected to occur in the future. Although there is always the chance that our predictions or inferences based on generalization might be wrong, nevertheless, schemas and generalizations from them are powerful forms of cognition. They permit us to form expectations from incomplete information about the future and thus allow us to prepare and plan for what is to come next. This anticipatory property of cognition is highly adaptive and likely has been powerfully selected for during the course of brain evolution.

An event schema, also known as a cognitive script, is a knowledge structure about a sequence of events. An event schema can lead to a set of behaviors that can feel like a routine. Think about what you do when you walk into an elevator. First, the doors open and you wait to let exiting passengers leave the elevator car. Then, you step into the elevator and turn around to face the doors, looking for the correct button to push. Like all schemas, event schemas are learned from environmental regularities we experience in the world.

Event schemas can vary widely among different cultures and countries. For example, while it is quite common for people to greet one another with a handshake in the United States, in Tibet, you greet someone by sticking your tongue out at them, and in Belize, you bump fists (Cairns Regional Council, n.d.) Because event schemas are automatic, they can be difficult to change. Imagine that you are driving home from work or school. This event schema involves getting in the car, shutting the door, and buckling your seatbelt, and putting the key in the ignition, and driving a particular route. How many times have you driven your route home only to remember as you pass your turn that you were intending to stop at the store first?

Concepts, Prototypes, Schemas, and Evolution of General Intelligence

Concepts, prototypes, and schemas all rely upon abstract, higher order features of the world which the brain captures and utilizes when it forms these knowledge structures. For example, concepts and prototypes are knowledge structures which capture similarities among individual instances of things (e.g. all birds have beaks, feathers, and wings). As discussed in an earlier section, the brain appears to be innately organized to find similarities and to generate higher order representations based on similarity. This leads to formation of concepts, categories, and predictions or expectations based on partial information. Also, as previously discussed, the brain has evolved to readily recognize and represent cause-effect and the predictive relations (correlation or covariation) of environmental events (Koenigshofer, 2017), leading to the formation of event schemas, as well as knowledge about the predictive and causal relations among events in the world--all of these help generate sophisticated knowledge and understanding of one's environment, facilitating adaptive organization of behavior and increasing biological fitness.

Perhaps one of the strongest examples of human thinking and intelligence is scientific discovery, a process which demonstrates abilities for categorization, often of a highly abstract nature, and causal understanding, talents which are evident in humans at an early age. As one researcher and his colleagues state,

"Causal induction, i.e., identifying unobservable mechanisms that lead to the observable relations among variables, has played a pivotal role in modern scientific discovery, especially in scenarios with only sparse and limited data. Humans, even young toddlers, can induce causal relationships surprisingly well in various settings despite its notorious difficulty" (Zhang, et al., 2021, p. 1).

Combined, these innate, evolved properties of the brain help the brain develop understanding of the relations among things in the world, thereby guiding adjustments in behavior for successful adaptation to the environment. Recall from earlier sections that these abilities comprise central components of general intelligence (the recognition "of relations and correlates," according to Spearman, 1904, 1925), found not only in humans, but in many animals ranging from crows and ravens to the great apes (see Koenigshofer, 2017). Although it is likely that the abilities that underlie general intelligence are distributed widely in the brain, the frontal and parietal lobes of the cerebral cortex appear to be especially important in human general intelligence (Bruner, 2010). Also recall that one additional component of general intelligence is the ability to imagine possible future behaviors and their probable outcomes in visual-like mental images, an ability which may involve visual and motor cortex and parts of the parietal lobe involving, as discussed in an earlier module, a frontoparietal network. This ability to imagine, as already noted, may play an important role in response selection and planning for the future, key features of human cognition and intelligence (Koenigshofer, 2017).

Brain Mechanisms in Category Formation

How the brain forms categories, and the brain areas involved, is not yet settled. However, evidence from studies of brain damage and brain imaging sheds light on the issue.

One thing is certain. Category formation is essential to cognitive processes. According to Seger and Miller (2010), the ability to form groupings of things and events into categories is a fundamental property of "sophisticated thought." Intelligence depends upon the ability to form meaningful categories. Disruption of this key feature of thinking and intelligence leads to behavioral and cognitive pathology. The importance of category formation is suggested by Seger and Miller (2010). Without the ability to form categories, "the world would lack any deeper meaning. Experiences would be fragmented and unrelated. Things would seem strange and unfamiliar if they differed even trivially from previous examples. This situation describes many of the cognitive characteristics of neuropsychiatric disorders such as autism" (Seger & Miller, 2010, p. 203).

Category formation, as discussed in earlier sections, reflects a fundamental fact of the world--that things and events in the world are similar to other things and events. Ability of the brain to exploit this fundamental property of the world to allow inference from the properties of a known category to new instances of the category has enormous, favorable consequences for survival and reproduction. A general principle is operating here. Natural selection has organized brain systems to reflect biologically significant regularities of the world (Koenigshofer, 2017; Shepard, 2001). This is consistent with the view expressed earlier that intelligence and thinking evolved as sophisticated guidance systems which produce neural models or cognitive maps of the world for the production of adaptively successful behavior.

The ability to form categories is dependent upon many brain areas which interact during the learning of categories. According to Seger and Miller (2010), these areas include the visual cortex, the prefrontal cortex, the parietal cortex, the basal ganglia, and the medial temporal lobe, including "interactions within and between corticostriatal loops connecting cortex and basal ganglia and between the basal ganglia and the medial temporal lobe." This provides "a balance between acquisition of details of experiences and generalization across them" to form and use categories (Seger & Miller, 2010, p. 203). According to Seger and Miller (2010), the inferotemporal (IT) cortex is likely a participating brain area in visual categorization given that it contains the fusiform face area (FFA), rich in face cells, active during learning of new face categories. Furthermore, IT cortical neurons in trained monkeys fire selectively to trees or fish with relatively little variation of firing within categories, suggesting that these neurons within the IT cortex encode specific categories of stimuli.

           

Figure \(\PageIndex{1}\): (Top Left and center) Striatum (shown in red) is a main input area of the basal ganglia, which receives input primarily from the cerebral cortex. (Right top and bottom left) Cerebral cortex: temporal lobe in green, parietal lobe in yellow, frontal lobe in brown (stationary photo) and in blue (bottom left rotating figure), occipital lobe in pink (stationary photo) and in rust (bottom left rotating figure). (Bottom right rotating figure) Human brain (hypothalamus=red, amygdala=green, hippocampus/fornix=blue, pons=gold, pituitary gland=pink).

(Images from Wikimedia, (top left) Striatum; File:Striatum.svg; https://commons.wikimedia.org/wiki/File:Striatum.svg; licensed under the Creative Commons Attribution-Share Alike 4.0 International license. Rotating (top center), File:Striatum.gif; https://commons.wikimedia.org/wiki/File:Striatum.gif; by Life Science Databases(LSDB); licensed under the Creative Commons Attribution-Share Alike 2.1 Japan license. Cortical lobes. (Top right) File:Brain - Lobes.png; https://commons.wikimedia.org/wiki/F...in_-_Lobes.png; by John A Beal, PhD, Dep't. of Cellular Biology & Anatomy, Louisiana State University Health Sciences Center Shreveport; Modifications: Hemispheres in color by DavoO; licensed under the Creative Commons Attribution 2.5 Generic license. (Bottom left, rotating) File:Four lobes animation small.gif; https://commons.wikimedia.org/wiki/F...tion_small.gif; by Database Center for Life Science(DBCLS); licensed under the Creative Commons Attribution-Share Alike 2.1 Japan license. Retrieved 10/25/21. (Bottom right, rotating: File:Rotating brain colored.gif; https://commons.wikimedia.org/wiki/F...in_colored.gif; by lifesciencedb; licensed under the Creative Commons Attribution-Share Alike 2.1 Japan license.).

Mahon and Caramazza (2009) reviewed research on categorization involving brain imaging and brain damage. They note that one generalization from this research is that "object domain and sensory modality jointly constrain the organization of knowledge in the brain." In other words, localization of particular items of knowledge in the brain depends on the object category (e.g. faces, tools) and also upon which sensory system (e.g. visual, auditory) is involved in representing the knowledge. Specifically, studies of the effects of brain damage on verbal categorization have been interpreted by some researchers to indicate that broad categories of objects (object domains) may be represented separately in different cortical regions. Research with brain damaged patients with damage in different brain areas has revealed "disproportionate or even selective impairments" for one category compared to other categories. This supports the view that different categories of objects are represented in different areas of brain. Cases of verbal category impairments have been found for the categories "animals," "fruit/vegetables," "conspecifics" (other humans), and "non-living things." For many patients, the deficits included failure to understand knowledge about the concepts, not just in naming them. For example, patients with impairment of the category "animals" could not answer simple questions about the features of specific animals, such as "Does a whale have legs" (Mahon and Caramazza, 2009, p. 28). Another patient had deficits in conceptual knowledge about people as evidenced by a severe inability to name famous people, even though this patient did not have prosopagnosia (inability to recognize familiar faces, such as family members or even one's own face in a photograph, while still being able to recognize a familiar person by other sensory modalities such as by voice).

According to Mahon and Caramazza, in addition to the theory that different categories may be localized in different modality-specific regions of brain (e.g. visual areas, somatosensory areas), other theories of categorical knowledge have been proposed, including the idea that category formation is "constrained by evolutionarily important distinctions such as animate, inanimate, conspecifics, and tools," or that categories are based on "statistical regularities in the co-occurrence of object properties in the world," implying wide distribution of neural representations of specific categories in the brain.

According to Mahon and Caramazza (2009), Damasio et al. (1996) found that inability to name pictures of famous people was related to "left temporal pole lesions," while impairment for naming animals occurred "with (more posterior) lesions of anterior left ventral temporal cortex." Additional studies confirmed that impairments naming animals occur with lesions of anterior temporal cortex. Studies by Damasio and colleagues and others found deficits for recognizing and naming tools with lesions to the posterior and lateral temporal cortex, overlapping the left posterior middle temporal gyrus. fMRI studies reveal that "nonliving things, and in particular tools, differentially activate the left middle temporal gyrus" as does mechanical motion. "Living animate things such as faces and animals elicit differential neural responses in the lateral fusiform gyrus, whereas nonliving things (tools, vehicles) elicit differential neural responses in the medial fusiform gyrus." Interestingly, brain areas involved in emotional processing and theory of mind (attribution of mental states in others) are part of the neural network activated during processing of information about living animate things (Mahon & Caramazza, 2009).

Ishibashi et al. (2016) reviewed "neuroimaging studies . . . to identify tool-related cortical circuits dedicated either to general tool knowledge or to task-specific processes. The results indicate the following: (a) Common, task-general processing regions for tools are located in the left inferior parietal lobule (LIPL) and ventral premotor cortex; and (b) task-specific regions are located in superior parietal lobule (SPL) and dorsal premotor area for imagining/executing actions with tools and in bilateral occipito-temporal cortex for recognizing/naming tools."

An approach to cognition known as embodied cognition hypothesizes that abstract concepts necessarily involve experience with previous sensorimotor interactions involving the whole body and thus may include encoding by sensory and motor areas of the brain. For example, we speak of an idea that we are not grasping as being "over our head," and we speak of affection in terms of warmth as represented in the fact that affection often is expressed in ways that allow us to feel the physical warmth of the body of another for whom we have affection. The concept of justice is often represented by a scale in balance. So, on this view, abstract concepts are often expressed in terms that are analogous to sensory and motor experiences of a body embedded in a concrete physical world.

Summary

In this section, you were introduced to topics within cognitive psychology, which is the study of cognition, or the brain’s ability to think, perceive, plan, analyze, and remember. Concepts and their corresponding prototypes help us quickly organize our thinking by creating categories into which we can sort new information. We also develop schemas, which are clusters of related concepts. Some schemas involve routines of thought and behavior, and these help us function in various situations without having to “think twice” about them. Schemas show up in social situations and routines of daily behavior. Concepts, prototypes, and schemas arise from fundamental dispositions of the brain to form knowledge structures based on similarity, causal relations, and correlations or predictive covariations of events. Natural selection favored brain organization capable of exploiting these abstract properties of the world leading to the evolution of general intelligence. General intelligence equipped humans and many other species with capacity to solve a wide range of adaptive challenges. In humans especially, this involves reasoning, planning, and imagination of possible future actions and their probable outcomes (Koenigshofer, 2017).

References

Bruner, E. (2010). Morphological differences in the parietal lobes within the human genus. Current Anthropology, 51(S1), S77-S88.

Damasio, H., Grabowski, T. J., Tranel, D., Hichwa, R. D., & Damasio, A. R. (1996). A neural basis for lexical retrieval. Nature, 380 (6574), 499-505.

Koenigshofer, K. A. (2017). General Intelligence: Adaptation to Evolutionarily Familiar Abstract Relational Invariants, Not to Environmental or Evolutionary Novelty. Journal of Mind & Behavior, 38 (2).

Mahon, B. Z., & Caramazza, A. (2009). Concepts and categories: a cognitive neuropsychological perspective. Annual review of psychology, 60, 27-51.

Ishibashi, R., Pobric, G., Saito, S., & Lambon Ralph, M. A. (2016). The neural network for tool-related cognition: an activation likelihood estimation meta-analysis of 70 neuroimaging contrasts. Cognitive Neuropsychology, 33(3-4), 241-256.

Seger, C. A., & Miller, E. K. (2010). Category learning in the brain. Annual review of neuroscience, 33, 203-219.

Shepard, R. N. (2001). Perceptual-cognitive universals as reflections of the world. Behavioral and brain sciences, 24 (04), 581-601.

Spearman, C. (1904). "General Intelligence," objectively determined and measured. American Journal of Psychology, 15 (2), 201-292.

Spearman, C. (1925). Some issues in the theory of`'g' (including the law of diminishing returns). Nature, 116, 436-439.

Zhang, C., Jia, B., Edmonds, M., Zhu, S. C., & Zhu, Y. (2021). ACRE: Abstract Causal REasoning Beyond Covariation. arXiv preprint arXiv:2103.14232. https://arxiv.org/pdf/2103.14232.pdf retrieved April 2, 2021.

Attributions

• Adapted by Kenneth A. Koenigshofer, PhD., from What is Cognition? by OpenStax Colleg licensed CC BY-NC 4.0 via OER Commons
• "Concepts, Prototypes, Schemata, and Evolution of General Intelligence" and "Brain Mechanisms of Category Formation" is original work written by Kenneth Koenigshofer, PhD, licensed under CC BY-NC 4.0