Cognitive Psychology

areas of study involved in cognitive psychology Graphics presentation courtesy of Nicole Conner Opens in new window

Cognitive psychology is a cognitive science Opens in new window involved in the study of human mental processes and their role in thinking, feeling, and behaving. Such study includes the broad categories of perception Opens in new window, memory Opens in new window, acquisition of knowledge and expertise, comprehension and production of language Opens in new window, problem solving Opens in new window, creativity Opens in new window, decision making, and reasoning.

Cognitive psychology studies (or gets to know) the mental processes that affect people’s behavior. Its discoveries beckon in understanding how individuals perceive, remember, imagine, think, and create. It also seeks to understand how things such as memory, attention, problem solving, and language work.

Cognitive psychology is only one of the cognitive sciences Opens in new window. Others include behavioral and cognitive neuroscience, cognitive anthropology, and computer science.

Experimentation lies at the heart of cognitive psychology, but also significant is the role of computer simulations and mathematical models.

Cognitive psychologists measure behavior in laboratory tasks in order to reach conclusions about covert mental processes.

The related discipline of cognitive neuroscience Opens in new window uses neuroimaging methods to relate activity in the brain to behavioral measurements.

Cognitive psychology and its more inclusive partner, cognitive science Opens in new window, exert a strong influence on psychology Opens in new window as a whole and promise a scientific understanding of the human mind in all its complexity and significance.

Cognitive psychology often portrays the human mind as first a processor of information: the mind computes answers to problems in a manner analogous to that used by computer software.

A digital computer represents an arithmetic problem, such as 21 + 14, in a symbolic code of “zeros” and “ones” according to an agreed convention.

Specifically, each digit is represented by eight bits of information, where each bit takes the value of either “zero” or “one”. Then, a software program processes those symbols according to the rules of addition, yielding the correct answer, 35.

Similarly, as you read this problem and verified the answer, your mind interpreted the numbers and processed the information. The analogy between mental processes and computation has proved fruitful and provides what is called the information-processing approach to cognitive psychology.

The central theme that still unites cognitive psychology and computer science Opens in new window is information processing: Both disciplines focus on how systems acquires, store, retrieve, transform, and produce information to perform intelligent activity.

The Internal Constructs of Cognitive Psychology

The internal constructs of cognitive psychology tend to be of a very specific type:

Almost always, they concern information processing, describing how the brain processes information.

Some cognitive constructs correspond to mechanisms in the brain that pick up information from the environment; others to mechanisms that store information in memory; and still others to mechanisms that retrieve information from memory, transform information in memory, and send information back into the environment.

Internal constructs in cognitive psychology typically do not represent conscious mental states. Instead, they typically represent unconscious information processing.

Most cognitive psychologists do not try to explain conscious experience. Rather than addressing conscious experience, cognitive psychology primarily addresses how the brain processes information.

In this sense, cognitive psychology is closer to neuroscience Opens in new window than it is to more mentalistic forms of psychology that address conscious experience. An analogy to computers may make this clearer.

Electronic circuitry

One way to explain a computer’s behavior is in terms of its electronic circuitry. At the electronic level of analysis, physical components, such as resistors, condensers, and silicon chips, constitute the central explanatory constructs.

These components enter various physical states, depending on the physical forces that emanate to them from other components, and together they determine computer operation.

Information flow structure

A second way to explain a computer’s behavior is in terms of its information flow structure. At this level of analysis, abstract entities such as commands, files, and directories constitute the central explanatory constructs.

During computer operation, commands operate on files to perform various operations, such as search, multiplication, and inference.

Although tremendous amounts of electronic structure and activity underlie these operations, the information processing level of analysis captures little of it. Instead, this level represents computer operations and entities only in terms of their information processing properties.

For example, informational capacity in bytes represents the size of a file, and a string of characters represents its concept; the underlying electronic circuitry that represents a file is typically irrelevant. Similarly, a name and a string of acceptable arguments represents a command; the underlying sequence of electronic events usually plays no role in its conceptualization and use.

Clearly, both the electronic and information processing accounts are essential for an adequate description of computers. The electronic account is necessary for building computers and for controlling them precisely, but is much too detailed and unwieldy for many other important uses, such as programming and word processing.

Moreover, the electronic account does not readily capture the global processing abilities of computers.

In contrast, the information processing account describes computers at a level that is suitably for the needs of most users, and it provides a global view of how computers process information. Without it, users could not see the forest for the trees and would get bogged down in unnecessary electronic details.

Neurological mechanisms and cognitive constructs in the brain are analogous to electronics and information processing in computers. Whereas neuroscience attempts to provide a detailed account of the brain’s physical components and their operation, cognitive theory attempts to provide a more global account of how these physical components process information.

Each level of analysis plays a different but complementary role (Bechtel, 1988a; Dennet, 1978; McCauley, 1986). Both are necessary for a complete understanding of the brain. Currently, our understanding of the brain’s information processing abilities probably exceeds our understanding of the neuronal mechanisms that produce them.

Note that nothing in this two-level account of the brain corresponds readily to the subjective nature of consciousness. Rather than capturing conscious experience, cognitive psychology typically describe the brain’s global, information processing properties.

Because information processing accounts of computers imply nothing about computers having conscious experiences, information processing accounts of the brain typically have little to say about people’s conscious experiences.

Clearly, we have conscious experiences, but cognitive psychology has shed little light on how the brain produces them.

Ultimately cognitive psychology will have to explain consciousness if it is to succeed, but present theories focus primarily on how the brain processes information to perform the fundamental tasks of intelligence.

It is in this regard that cognitive psychology is closer to neuroscience than to more mentalistic forms of psychology that address conscious experience.

related literatures:
  1. Bechtel, W. (1988) Philosophy of Mind: An Overview for Cognitive Science, Hillsdale, NJ, Lawrence Erlbaum Associates.
  2. Bechtel, W. and Abrahamsen, A. (2002) Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks, 2nd edition, Oxford, Blackwell.
  3. Gardner, H. (1985) The Mind’s New Science: A History of the Cognitive Revolution, New York, Basic Books.