Cognitive Psychology Research Paper

2. The Scope Of Cognitive Psychology

At present, Cognitive Psychology is a broad field concerned with many different topic areas, such as, for instance, human memory, perception, attention, pat-tern recognition, consciousness, neuroscience, representation of knowledge, cognitive development, language, and thinking. The common denominator of these phenomena appears to be that all of the phenomena reflect the operation of ‘intelligence’ in one way or another, at least if intelligence is broadly defined as skill of an individual to act purposefully, think rationally, and interact efficiently with the environment. Thus, at a general level, Cognitive Psychology is concerned with explaining the structure and mental operations of intelligence as well as its behavioral manifestations.

3. Historical Roots Of Cognitive Psychology

3.1 The Term Cognitive Psychology

The term Cognitive Psychology (latin: cognoscere; greek: gignoskein = to know, perceive) is rather young. Although we do find the related term ‘cognition’ mentioned occasionally in the psychologies of the late nineteenth and early twentieth century (e.g., James, Spence, Wundt) where it denoted the basic elements of consciousness and their combinations, the present meanings of the term cognitive psychology owe little to the early theoretical and philosophical considerations of the human mind. Rather, the current modern meanings of the term owe much more to (a) the fact that the study of cognition emerged in opposition to the prevailing behavioristic view in the 1940s and 1950s that was trying to explain human behavior primarily in terms of its antecedent environmental conditions, and to (b) the availability of both new theoretical concepts (e.g., information theory [Shannon], cybernetics [Wiener], systems theory [von Bertalanffy]) and practical computing machines that offered new insights into the potential nature of the mental device intervening between the outside world and human behavior.

Accordingly, the history of Cognitive Psychology can be parsed into four distinct periods: philosophical, early experimental, the cognitive revolution, and modern cognitive psychology. Early philosophy (ancient Egyptians, Greek philosophers, British empiricists) provided a context for understanding the mind and its processes (i.e., associations), and identified many of the major theoretical issues that were later studied empirically (e.g., how does perception work? how are concepts represented?). Early experimental work began, at the latest, during the middle part of the nineteenth century, when Fechner empirically studied the relation between stimulus properties (e.g., weight) and accompanying internal sensations, and when, in 1879, Wilhelm Wundt founded the first department of psychology in Leipzig, Germany. The early experimental phase of Cognitive Psychology was in full swing when, during the early 1900s, Donders and Cattell conducted perception experiments on imageless thought, and Frederic Bartlett investigated memory from a naturalistic viewpoint.

4. Modern Cognitive Psychology

In the mid-1950s and early 1960s, Cognitive Psychology experienced a renaissance. Cognitive Psychology, a textbook that systematized the re-emerged science, was written by Neisser and was published in the United States (1967). Neisser’s book was central to the solidification of Cognitive Psychology as it gave a label to the field and defined the topical areas. Neisser used the computer metaphor to capture the selection, storage, reception, and manipulation of information in the human cognitive system. In 1966, Hilgard and Boweradded a chapter to their book Theories of Learning in which the idea of using computer pro-grams to serve as models of theories of cognition was developed.

The 1970s saw the emergence of professional journals devoted to Cognitive Psychology, such as Cognitive Psychology, Cognition, Memory & Cognition, and a series of symposia volumes, including the Loyola Symposium on Cognition and the Carnegie– Mellon Series. Cognitive laboratories were built, symposia and conferences appeared at both national and international levels, courses in Cognitive Psychology were added to the curricula, textbooks written on the topic, and professors of Cognitive Psychology hired.

In the 1980s and 1990s, serious efforts to discover the neural components that are linked to specific cognitive constructs began, and the field underwent transformations due to major changes in computer technology and brain science. As a result, Cognitive Psychology converged with computer science and neuroscience to create a new discipline called ‘Cognitive Science.’

Even more recently, with the advent of new ways to see the brain at work (e.g., functional magnetic resonance imaging fMRI, positron emission tomography PET, electroencephalogram EEG), cognitive psychologists have expanded their operations to neuroscience, in the hope of being able to empirically localize the components of the brain that are involved in specific operations of the cognitive system.

5. The Properties Of The Cognitive System: The Computer Metaphor

Currently, the dominant metaphor underlying theoretical and empirical research in Cognitive Psychology is the computer metaphor. According to the computer metaphor, the cognitive system of humans, that is, the device intervening between environmental input and behavior, can be understood best in analogy to an information-processing framework. A basic information-processing system (see Fig. 1) contains two basic components, a memory and a processor, that interact with each other. In addition, the processor interacts with the environment through receptors and effectors. Newell and Simon argue that any physical-symbol system, such as an information-processing system, has the necessary and sufficient means to generate intelligent action (physical symbol systems hypothesis).

In laymen’s terms, the information-processing framework formally described by Newell and Simon (1972, pp. 20–21) can be said to be based on seven basic ideas (Lachman et al. 1979): (a) humans are viewed as autonomous, intentional beings who interact with the external world; (b) the cognitive system is a general-purpose, symbol-processing system; (c) there exists a fundamental distinction between processes and data (i.e., memories). Data are acted on by processes that manipulate and transform data; (d) cognitive processes take time, such that predictions about response times can be made if it is assumed that processes occur in sequence and have specifiable complexity; (e) the cognitive system is a limited-capacity processor that has both structural and resource limitations; (f) the cognitive system depends on, but is not entirely constrained by, a neurological substrate; (g) the goal of psychological research is to specify the processes and representations underlying intelligent performance on cognitive tasks.

6. Current Themes Of The Computer Metaphor

The idea that a human cognitive system can be viewed as an information-processing device has had a dramatic impact on both theoretical and empirical research on the functioning of the human mind. A few select current themes in Cognitive Psychology reflecting this approach are the following.

6.1 Data-Driven Or Conceptually Driven Processes?

A data-driven mental process is one that relies almost exclusively on the ‘data,’ that is, on the stimulus information being presented in the environment. Whereas data-driven processes are assisted very little by already known information, conceptually driven processes are those that rely heavily on such in-formation. Thus, a conceptually driven process uses the information already in memory, and whatever expectations are present in the situation, to perform a task; data-driven processes use only the stimulus information.

The distinction between data-driven and conceptually driven processes has been studied intensely in, among others, the area of pattern recognition. Models of perception attempt to explain, in large part, how patterns are recognized. Early models assumed that this process was primarily data-driven. However, the results of more recent research suggests that pattern recognition is also influenced by top-down conceptual processes.

6.2 Attention

Attention is often assumed to be a critical mental resource that is necessary for the operation of any mental process. Most theories that discuss attention assume that it is a limited mental resource and that the amount of attention that is available determines how many separate processes can be simultaneously per-formed.

One of the perhaps most interesting problems surrounding the role of attention has been concerned with the question of whether attentional selection occurs early or late within the cognitive system. Much of the early research on this topic focused on the extent to which unattended stimuli are processed. Early selection models hold that selection occurs at a relatively early level in the cognitive system, that is, before meaning has been extracted. Initial support for this notion came from dichotic listening tasks in which listeners had to verbally repeat information presented to one ear while different (or the same) information was simultaneously presented to the other ear. Results suggested that little of the information presented to the unattended ear was noticed. However, it was soon realized that attentional selection was not an all-or-none phenomenon. Thus, at least under some circumstances unattended information seems to reach higher levels of the cognitive system.

The topic of attentional selection has received rather widespread interest not only in studies with normal adults but also with neuropsychological samples be-cause in some patient populations (e.g., attention-deficit disorder, schizophrenia), the attentional selection system appears to be impaired.

6.3 Separate Or Unitary Memory Systems?

The debate over memory types has a long history in Cognitive Psychology. For example, in the 1960s Atkinson and Shiffrin introduced an information-processing model containing sensory, short-term, and long-term memory stores. Craik and Lockheart, a few years later, advanced a unitary view of memory. More recently, distinctions have been made between declarative explicit (intentionally recollecting earlier experiences) and procedural implicit (nonintentional influences from earlier exposure) memory systems, that, in turn, have been challenged by the argument that many apparent dissociations can be accommodated when one considers the match between encoding operations and retrieval operations (transfer-appropriate processing). At present, it is unclear how many distinct memory systems exist in the human cognitive system. However, recent studies with amnesic patients and brain-imaging studies seem to suggest that memory may not be unitary.

6.4 The Nature Of The Cognitive Architecture

Cognitive architectures specify the permanent proper-ties of the human cognitive system, akin to the hardware of a modern computer. Recent proposals sketch the human cognitive architecture in a much more fine-grained and detailed manner than was apparent in Newell and Simon’s earlier proposal of a basic information-processing device.

Fig. 2 depicts the basics of a cognitive architecture, that has been proposed by Anderson (1983), called ACT* (adaptive control of thought). In Anderson’s architecture, the existence of a long-term declarative memory for basic facts that are connected to each other in a semantic net is assumed. In addition, Anderson proposes a second long-term, procedural, memory that consists of productions. Each production has a set of conditions that test elements of working memory and a set of actions that create new structures in working memory. Strengths are associated with each long-term memory element (both network nodes and productions) as a function of its use. Working memory itself is activation based and contains the activated portion of declarative memory plus declarative structures generated by production firings and perception.

Activation spreads automatically (as a function of node strength) through working memory and from there to other connected nodes in declarative memory. Activation, along with production strength, deter-mines how fast the matching of production proceeds. Selection of productions to fire is a competitive process between productions matching the same data.

New productions are created by compiling the effects of a sequence of production firings and retrievals from declarative memory. Whenever a new element is created in working memory, there is a fixed probability that it will be stored in declarative memory. Cognitive architectures like ACT* are important not only in their own rights, that is, because they are theories of the structural and processing components of the human cognitive system, but also because they set important constraints for more specific theories that address more local characteristics of the cognitive system.

7. Recent Challenges To The Computer Metaphor

In recent years, an increasing number of theorists have come to reject the view that the human cognitive system operates like a computer. Two new metaphors have been proposed. First, some theorists have argued that the human cognitive system might be better understood in terms of a brain metaphor, assuming that cognitive systems consist of elementary, neuron-like units that are connected and produce behavior as a whole. Second, at least some areas within Cognitive Psychology have adopted an ecological, or context metaphor, arguing that cognitive systems need to be understood in terms of organism-environment relations.

7.1 The Brain Metaphor

According to the brain metaphor, human cognition is best understood in terms of the properties of the brain. The brain metaphor, and more specifically, so-called neural-like, connectionist networks as computational implementations of how our brain might work, have become highly popular in recent years and have seriously challenged the premier status of the computer metaphor when it comes to theorizing about the nature of human cognition.

Connectionist networks, neural networks, or parallel distributed processing models as they are variously called, differ from theories based on the computer metaphor in various respects. For example, in theories adhering to the computer metaphor, all processes assumed to underlie human behavior need to be explicitly described. Connectionist networks, on the other hand, can to some extent ‘program’ them-selves in that they can learn to produce specific outputs when certain inputs are given to them. Furthermore, connectionist theorists often reject the use of explicit rules and symbols and use distributed representations, in which concepts are characterized as patterns of activation in a network.

Current connectionist networks typically have the following characteristics:

 (a) the network consists of elementary or neuron-like units or nodes that are connected to each other such that a single unit has many links to other units;

(b) units affect other units by exciting or inhibiting them;

(c) the units usually takes the weighted sum of all input links and produces a single output to another unit if the weighted sum exceeds some threshold value;

(d) the network as a whole is characterized by the properties of its units, by the manner in which the units are connected to each other, and by the algorithms or rules used to change the strength of connections among units;

(e) networks can have different structures of layers; they can have a layer of input units, intermediate layers (of so-called ‘hidden units’), and a layer of output units;

(f ) a representation of a concept is stored in a distributed manner by a pattern of activation through- out the network;

(g) the same network can store many different patterns without them necessarily interfering with each other;

(h) one algorithm or rule used in networks to permit learning to occur is known as backward propagation of errors.

How do individual units act when activation impinges on them? Any given unit can be connected to several other units (see Fig. 3). Each of these other units can send an excitatory or an inhibitory signal to the first unit. This unit generally takes a weighted sum of all these inputs. If the sum exceeds some threshold, then the unit produces an output that may feed into other units.

This type of network can model cognitive behavior without recourse to the kinds of explicit rules found in the domain of the computer metaphor. The networks do so by associating various inputs with certain outputs, and by storing patterns of activation in the network. The networks typically make use of several layers to deal with complex behavior. One layer consists of input units that encode a stimulus as a pattern of activation. Another layer is an output layer that produces some response, again as a pattern of activation. When the network has learned to produce a particular response at the output layer following the presentation of a particular stimulus at the input layer, it can exhibit behavior that very much looks like a rule being applied.

One of the most critical aspects of connectionist networks is the learning rule or algorithm used to form patterns of activation. One algorithm that has been used to permit connectionist networks to learn is called backward propagation. At the beginning of a learning episode, the network is set up with random connection weights among the units. During the early stages of learning, when the input pattern has been presented, the output units often produce a response that is not the required output pattern. Backword propagation compares this imperfect pattern with the known required response, noticing the differences. It then back-propagates activation through the network such that the units are adjusted in such a way that they will tend to produce the required pattern on the next learning cycle. This process is repeated with a particular stimulus pattern until the network produces the required response pattern.

Networks have been used to produce very interesting results. For example, Sejnowski and Rosenberg produced a connectionist network called NET-talk that takes an English text as its input and produces reasonable English speech as its output. Thus, the network appears to have learned the ‘rules of English pronunciation’ but has done so without requiring explicit rules that combine and encode sounds in various ways.

7.2 The Ecological Metaphor

Ecological psychology focuses specifically on the interdependencies of humans and their environments, which typically are studied under real-world conditions rather than in the laboratory. The approach has given rise to a variety of very different approaches and lines of research, only two of which will be briefly considered. One approach is concerned with explaining and understanding perception, and can be traced to E. Brunswick and more recently, J. J. Gibson; the other approach is concerned with social behavior and appears to go back to K. Lewin and R. Barker. Although the two lines of research share the ecological perspective of examining functional adaptations of organisms to their environment, they are concerned with different issues and employ different methods. The two theoretical lines are much less explicit about the actual properties of the assumed cognitive system that intervenes between perception and action than are the computer and brain metaphors discussed above, and both have much less influence in con-temporary Cognitive Psychology as do their two contenders. Nevertheless, they represent a succinctly different understanding of how the cognitive system might function and belong, at least in part, to the realm of Cognitive Psychology.

7.2.1 Gibson’s Ecological Psychology. Following classical ecological theory, Gibson regards organism and environment to be an inseparable pair. A critical feature of this conception is that environment is not defined independently of organisms, nor are organ-isms defined independently of environments.

Gibson considers the first task of ecological psychology to be an adequate description of the environment. Environment consists of a medium, sub-stances, and surfaces separating substance from medium. In a successful adaptation, organisms need to perceive which aspects of surface, substance, and medium persist and which aspects change in regard to specific environmental events.

The ecological approach to visual perception assumes that senses represent evolved adaptations to an organism’s environment. These adaptations develop in relation to environmental factors contributing to an organism’s survival. Evolutionary success re-quires sensory systems that directly and accurately depict the environment. The key stimulus features that contribute to an organism’s survival which Gibson termed ‘affordances’ are invariant. Affordances differ according to situation and species and are perceived directly from the pattern of stimulation arising from them. They do not change as the needs of observers change; affordances have both objective and subjective properties, becoming a fact of the environment and a fact of behavior.

Gibson’s approach is sometimes referred to as the theory of direct perception, and has received empirical support from, among others, research by E. J. Gibson, studying the development of perceived invariance in infancy. E. J. Gibson’s research, for instance, has demonstrated that one of the properties of perceptual learning and development does appear to be the increasing ability to extract information about the permanent properties of objects.

7.2.2 Barker’s Ecological Psychology. According to R. Barker, behavior should be studied without out-side manipulation or imposition of structure. Rather than contrive artificial settings, Barker advocated the study of behavioral settings that already exist, using methodology that exerts minimal influence upon the situation.

To collect systematic records of behavior in natural contexts, Barker argued for the establishment of so-called field stations, established organizational units that were to continue over time and whose staff included both continuing and visiting researchers. Barker and co-workers established the Midwest Psychological Field Station in Oskaloosa, Kansas, where for a period of 24 years detailed systematic records were kept of community life. Observers were stationed throughout the town, and recorded everyday activities of children. Barker concluded that the behavior of a child could often be predicted more accurately from knowing the situation the child was in, than from knowing individual characteristics of the child.

Barker’s conception of ecological psychology rests on several assumptions, (a) human behavior must be studied at a level that recognizes the complexity of systems of relations linking individuals and groups with their social and physical environments; (b) environment–behavioral systems have properties that develop over long periods of time; (c) change in one part of the system is likely to affect other parts of the system; and (d) the challenge of ecological psychology is to obtain sufficient understanding to be able to predict and control the effects of planned and un-planned interventions.

Barker’s conception of ecological psychology has been extended and refined in recent years (e.g., J. Barker, K. Fox, A. Wicker). For example, Fox has linked it to social accounting theory, showing how data from large-scale inventories of behavior settings can reveal changes in the quality of life in communities.

From the brief desciption of ecological psychology above, it should be clear that despite the fact that the ecological metaphor has more than some intuitive appeal to it, both its level of precision and its scope are far smaller than those of the computer and the brain metaphors. Consequently, the ecological metaphor plays a very minor role in current Cognitive Psychology.

8. Research Methods In Cognitive Psychology

Cognitive psychologists rely heavily on the experimental method, in which independent variables are manipulated and dependent variables are measured to provide insights into the specifics of the underlying cognitive system. To statistically evaluate the results from experiments, Cognitive Psychology relies on standard hypothesis testing, along with inferential statistics (e.g., analyses of variance).

The research methods Cognitive Psychology utilize depend, in part, on the area of study and consist primarily of chronometric methods, memory methods, cross-population studies, case studies, measures of brain activity, and computational modeling.

8.1 Chronometric Methods

Beginning with early work by Donders (1868–1969), cognitive psychologists have used reaction times to measure the speed of mental operations. Donders developed the so-called subtractive method. For example, task A might be assumed to require Process 1, whereas task B might require Processes 1 and 2. Donders assumed that cognitive operations are in-dependent of each other and are processed in a strictly serial manner. Thus, the duration of Process 2 can be estimated by subtracting the response time for task A from the reaction time for task B.

To circumvent some of the restrictive assumptions of the subtractive method, Saul Sternberg introduced an additive factors logic. According to this logic, if a task contains distinct processes, then there should be variables that selectively influence the speed of each process. Thus, if two variables influence different processes, their effects should be statistically additive. By contrast, if two variables affect the same process, their effects should statistically interact.

More recently, researchers have empirically identified for so-called cascaded systems in which neither the assumptions of Donders nor of Sternberg hold because mental processes occur simultaneously at different information-processing levels. New measures have been developed that combine reaction time measurement with the measurement of other properties of the cognitive system (e.g., speed-accuracy tradeoff functions, eye-tracking methods).

8.2 Memory Methods

One of the first to experimentally study human memory was Hermann Ebbinghaus who developed the savings technique to assess retention of nonsense syllables. Retention was measured in terms of the number of trials necessary to relearn a list of syllables relative to the number of trials necessary to learn the list for the first time.

More recently, researchers have begun to distinguish between three different aspects of memory, encoding, retention, and retrieval, and have developed methods to study the three aspects in isolation. For example, one way of investigating encoding processes is to manipulate humans’ expectancies by way of intentional vs. incidental learning instructions. By contrast, retrieval processes are often studied in one of two general ways. On an explicit memory test, participants are presented a list of materials and at some later point in time are given a test in which they are asked to retrieve the earlier presented material. Retrieval is measured in terms of recall, recognition, or cued recall. On implicit memory tests, participants are not directly asked to recollect an earlier episode, but rather, are asked to engage in a task where performance might benefit from earlier exposure to the stimulus items. Interestingly, recent research has demonstrated that some neuropsychological populations (e.g., amnesic patients) can be unimpaired on implicit memory tests, but can show considerable impairment in explicit memory tests.

8.3 Case Studies

Although relatively rarely used in Cognitive Psychology, single case studies can provide vital information on how the cognitive system may be structured and which specific processes might be necessary to complete specific tasks. The classic case of HM, who as a consequence of an earlier epilepsy operation, acquired severe memory loss on explicit tasks though not implicit tasks, might serve as a striking example arguing for the dissociation of different memory structures. Case studies can provide rather convincing constraints for cognitive psychologists’ understanding of the architecture of human cognition.

8.4 Cross-Population Studies

Cognitive Psychology relies heavily on college students as their research participants. Recently, however, there has been an increasing interest in comparing both the structure and the processes of the cognitive system across distinct populations. For example, studies of cognition from early childhood to older adulthood attempt to trace developmental changes in specific mental operations, such as speed of processing and memory. In addition, studies with special clinical populations are conducted in order to understand breakdowns in mental functioning, such as they occur in Alzheimer’s disease, schizophrenia, or amnesia.

8.5 Measures Of Brain Activity

In recent years a variety of possibilities to measure some correlates of mental activity in the brain (e.g., evoked potentials, positron emission tomography [PET], functional magnetic resonance imaging [fMRI]) have become available. Evoked potentials measure the electrical activity of systems of neurons; PET measures blood flow. Because the measures differ widely in their invasiveness and in terms of their temporal and spatial resolutions, a combination of these methods, together with behavioral measurements (e.g., reaction time, accuracy) appears to be an extremely promising candidate for increasing under-standing of the interaction between Neuropsychology and Cognitive Psychology.

8.6 Computational Modeling

Since the early research of Newell and Simon on the General Problem Solver, theoretical assumptions concerning both the structure of, and the processing within, the cognitive system have been tested by implementing the assumptions in running computer programs. Recently, the modeling has been of two different varieties, connectionist versus symbolic modeling (see above). For example, in order to model the processes underlying human language learning, the symbolic modeling approach assumes that humans acquire a set of rules that specify how language constituents can be combined within a language and can be specified in a running program. Alternatively, the cognitive system might acquire the ‘rules of language’ without directly specifying these rules as symbols at all, that is, within a distributed representational system (connectionist theory). At present, the controversy surrounding these two alternative modeling accounts is far from settled, and, importantly, reflects a fundamental issue regarding the nature of the human cognitive system that was addressed in more detail above (computer metaphor vs. brain metaphor).

9. The Future Of Cognitive Psychology

If the past is a good predictor of the future, then the future of Cognitive Psychology is difficult to predict. Most likely, however, neither the theoretical scope nor the empirical methods of the field are going to change dramatically. If there will be disagreement among scientists, it will concern the nature of the mental system intervening between environmental input and behavior. The most desirable future scenario is per-haps one in which the three main metaphors (i.e., computer, brain, ecological) will be integrated into a coherent one. Because the three metaphors deal with distinct levels of the human mind, this scenario is perhaps not an unlikely, remote theoretical possibility.

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