Behaviorism’s emphasis on objectivity and focus on external behavior had pulled psychologists’ attention away from the mind for a prolonged period of time. The early work of the humanistic psychologists redirected attention to the individual human as a whole, and as a conscious and self-aware being. By the 1950s, new disciplinary perspectives in linguistics, neuroscience, and computer science were emerging, and these areas revived interest in the mind as a focus of scientific inquiry. This particular perspective has come to be known as the cognitive revolution (Miller, 2003). By 1967, Ulric Neisser published the first textbook entitled Cognitive Psychology, which served as a core text in cognitive psychology courses around the country (Thorne & Henley, 2005).
Although no one person is entirely responsible for starting the cognitive revolution, Noam Chomsky was very influential in the early days of this movement. Chomsky (1928–), an American linguist, was dissatisfied with the influence that behaviorism had had on psychology. He believed that psychology’s focus on behavior was short-sighted and that the field had to re- incorporate mental functioning into its purview if it were to offer any meaningful contributions to understanding behavior (Miller, 2003).
Figure 16. Noam Chomsky was very influential in beginning the cognitive revolution. In 2010, this mural honoring him was put up in Philadelphia, Pennsylvania. (credit: Robert Moran)
European psychology had never really been as influenced by behaviorism as had American psychology; and thus, the cognitive revolution helped reestablish lines of communication between European psychologists and their American counterparts. Furthermore, psychologists began to cooperate with scientists in other fields, like anthropology, linguistics, computer science, and neuroscience, among others. This interdisciplinary approach often was referred to as the cognitive sciences, and the influence and prominence of this particular perspective resonates in modern-day psychology (Miller, 2003).
Noam Chomsky
In the middle of the 20th century, American linguist Noam Chomsky explained how some aspects of language could be innate. Prior to this time, people tended to believe that children learn language soley by imitating the adults around them. Chomsky agreed that individual words must be learned by experience, but he argued that genes could code into the brain categories and organization that form the basis of grammatical structure. We come into the world ready to distinguish different grammatical classes, like nouns and verbs and adjectives, and sensitive to the order in which words are spoken. Then, using this innate sensitivity, we quickly learn from listening to our parents about how to organize our own language [ 5] [ 6] For instance, if we grow up hearing Spanish, we learn that adjectives come after nouns (el gato amarillo, where gato means “cat” and amarillo is “yellow”), but if we grow up hearing English, we learn that adjectives come first (“the yellow cat”). Chomsky termed this innate sensitivity that allows infants and young children to organize the abstract categories of languagethe language acquisition device (LAD).
According to Chomsky’s approach, each of the many languages spoken around the world (there are between 6,000 and 8,000) is an individual example of the same underlying set of procedures that are hardwired into human brains. Each language, while unique, is just a set of variations on a small set of possible rule systems that the brain permits language to use.
Chomsky’s account proposes that children are born with a knowledge of general rules of grammar (including phoneme, morpheme, and syntactical rules) that determine how sentences are constructed.
Although there is general agreement among psychologists that babies are genetically programmed to learn language, there is still debate about Chomsky’s idea that a universal grammar can account for all language learning. Evans and Levinson [ 7] surveyed the world’s languages and found that none of the presumed underlying features of the language acquisition device were entirely universal. In their search they found languages that did not have noun or verb phrases, that did not have tenses (e.g., past, present, future), and some that did not have nouns or verbs at all, even though a basic assumption of a universal grammar is that all languages should share these features. Other psychologists believe that early experience can fully explain language acquisition, and Chomsky’s language acquisition device is unnecessary.
Nevertheless, Chomsky’s work clearly laid out the many problems that had to be solved in order to adequately explain how children acquire language and why languages have the structures that they do.
Connectionism – Parallel Distributive Processing
Connectionism was based on principles of associationism, mostly claiming that elements or ideas become associated with one another through experience and that complex ideas can be explained through a set of simple rules. But connectionism further expanded these assumptions and introduced ideas like distributed representationsand supervised learning and should not be confused with associationism.
Connectionism and Network Models
Network models of memory storage emphasize the role of connections between stored memories in the brain. The basis of these theories is that neural networks connect and interact to store memories by modifying the strength of the connections between neural units. In network theory, each connection is characterized by a weight value that indicates the strength of that particular connection. The stronger the connection, the easier a memory is to retrieve. Network models are based on the concept of connectionism. Connectionism is an approach in cognitive science that models mental or behavioral phenomena as the emergent processes of interconnected networks that consist of simple units. Connectionism was introduced in the 1940s by Donald Hebb, who said the famous phrase, “Cells that fire together wire together.” This is the key to understanding network models: neural units that are activated together strengthen the connections between themselves.
There are several types of network models in memory research. Some define the fundamental network unit as a piece of information. Others define the unit as a neuron. However, network models generally agree that memory is stored in neural networks and is strengthened or weakened based on the connections between neurons. Network models are not the only models of memory storage, but they do have a great deal of power when it comes to explaining how learning and memory work in the brain, so they are extremely important to understand.
Parallel Distributed Processing Model
The parallel distributed processing (PDP) model is an example of a network model of memory, and it is the prevailing connectionist approach today. PDP posits that memory is made up of neural networks that interact to store information. It is more of a metaphor than an actual biological theory, but it is very useful for understanding how neurons fire and wire with each other.
Taking its metaphors from the field of computer science, this model stresses the parallel nature of neural processing. “Parallel processing” is a computing term; unlike serial processing (performing one operation at a time), parallel processing allows hundreds of operations to be completed at once—in parallel. Under PDP, neural networks are thought to work in parallel to change neural connections to store memories. This theory also states that memory is stored by modifying the strength of connections between neural units. Neurons that fire together frequently (which occurs when a particular behavior or mental process is engaged many times) have stronger connections between them. If these neurons stop interacting, the memory’s strength weakens. This model emphasizes learning and other cognitive phenomena in the creation and storage of memory.
Figure 17. Neural connections: As neurons form connections with each other through their many dendrites, they can form complex networks. Network models propose that these connections are the basis of storing and retrieving memories.
