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PDF | On Feb 1, , ARRON W. S. METCALFE and others published [REVIEW] Cognitive Psychology: A Student's Handbook (6th Ed.) by M. W. Eysenck and. Rigorously researched and accessibly written, Cognitive Psychology: A Student's Handbook is widely regarded as the leading undergraduate textbook in the. Cognitive psychology: a student's handbook / Michael W. Eysenck, Mark T. . 6th ed. Hove, Eng. ; New York: Psychology Press, 1 online resource (vii,
This issue of separating psychological aspects of the program from other aspects arises because there will always be parts of the program that have little to do 1. Reproduced with permission of the author.
However, no-one would argue that such print commands form part of the psychological model. Cooper et al. Is it possible to separate psychological aspects of a program f rom other aspects? Are there differences in reaction time between programs and human participants? This would be a very precise language, like a logic, that would be directly executable as a program.
For example, it is seldom meaningful to relate the speed of the program doing a simulated task to the reaction time taken by human participants, because the processing times of programs are affected by psychologically irrelevant features.
At the very least, the program should be able to reproduce the same outputs as participants when given the same inputs. Computational modelling techniques The general characteristics of computational models of cognition have been discussed at some length. It is now time to deal with some of the main types of computational model that have been used in recent years.
Three main types are outlined briefly here: semantic networks; production systems; and connectionist networks. Semantic networks Consider the problem of modelling what we know about the world see Chapter 9. There is a long tradition from Aristotle and the British empiricist school of philosophers Locke, Hume, Mill, Hartley, Bain which proposes that all knowledge is in the form of associations.
There is a whole class of cognitive models owing their origins to these ideas; they are called associative or semantic or declarative networks. Thus, for example, a dog and a cat node may be connected by a link with an activation of 0. For example, in learning that two concepts are similar, the activation of a link between them may be increased. Part of a very simple network model is shown in Figure 1.
It corresponds closely to the semantic network model proposed by Collins and Loftus Such models have been successful in accounting for a various findings. Ayers and Reder have used semantic networks to understand misinformation effects in eyewitness testimony see Chapter 8. At their best, semantic networks are both flexible and elegant modelling schemes.
Production systems Another popular approach to modelling cognition involves production systems. There is also a working memory i. Consider a very simple production system operating on lists of letters involving As and Bs see Figure 1. The system has two rules: 1. If we give this system different inputs in the form of different lists of letters, then different things happen.
If we give it CCC, this will be stored in working memory but will remain unchanged, because it does not match either of the IF-parts of the two rules. If we give it A, then it will be notified by the rules after the A is stored in working memory.
This A is a list of one item and as such it matches rule 1.
On the next cycle, AB does not match rule 1 but it does match rule 2. As a result, the B is replaced by an A, leaving an AA in working memory. Newell and Simon first established the usefulness of production system models in characterising cognitive processes like problem solving and reasoning see Chapter However, these models have a wider applicability. Anderson has modelled human learning using production systems see Chapter 14 , and others have used them to model reinforcement behaviour in rats, and semantic memory Holland et al.
Connectionist networks Connectionist networks, neural networks, or parallel distributed processing models as they are variously called, are relative newcomers to the computational modelling scene. All previous techniques were marked by the need to program explicitly all aspects of the model, and by their use of explicit symbols to represent concepts.
Furthermore, connectionist modellers often reject the use of explicit rules and symbols and use distributed representations, in which concepts are characterised as patterns of activation in the network see Chapter 9. Early theoretical proposals about the feasibility of learning in neural-like networks were made by McCulloch and Pitts and by Hebb However, the first neural network models, called 1. Input patterns can be encoded, if there are enough hidden units, in a form that allows the appropriate output pattern to be generated from a given input pattern.
Reproduced with permission from David E. McClelland, Parallel distributed processing: Explorations in the microstructure of cognition Vol. By the late s, hardware and software develpments in computing offered the possibility of constructing more complex networks overcoming many of these original limitations e.
Connectionist networks typically have the following characteristics see Figure 1. In order to understand connectionist networks fully, let us consider how individual units act when activation impinges on them.
Any given unit can be connected to several other units see Figure 1. 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 this sum exceeds some threshold, it produces an output. Figure 1. These networks can model cognitive behaviour without recourse to the kinds of explicit rules found in production systems.
They do this by storing patterns of activation in the network that associate various inputs with certain outputs. The models typically make use of several layers to deal with complex behaviour. One layer consists of input units that encode a stimulus as a pattern of activation in those units. Another layer is an output layer, which produces some response as a pattern of activation. However, no such rules exist explicitly in the model. Networks learn the association between different inputs and outputs by modifying the weights on the links between units in the net.
In Figure 1. Various learning rules modify these weights in systematic ways. When we apply such learning rules to a network, the weights on the links are modified until the net produces the required output patterns given certain input patterns.
BackProp allows a network to learn to associate a particular input pattern with a given output pattern. At the start of the learning period, the network is set up with random weights on the links among the units. During the early stages of learning, after the input pattern has been presented, the output units often produce the incorrect pattern or response. BackProp compares the imperfect pattern with the known required response, noting the errors that occur.
It then back-propagates activation through the network so that the weights between the units are adjusted to produce the required pattern. This process is repeated with a particular stimulus pattern until the network produces the required response pattern.
Thus, the model can be made to learn the behaviour with which the cognitive scientist is concerned, rather than being explicitly programmed to do so. Networks have been used to produce very interesting results. Several examples will be discussed throughout the text see, for examples, Chapters 2, 10, and 16 , but one concrete example will be mentioned here. Sejnowski and Rosenberg produced a connectionist network called NETtalk, which takes an English text as its input and produces reasonable English speech output.
Some researchers might object to our classification of connectionist networks as merely one among 1. Indeed, if one examines the fundamental tenets of the information-processing framework, then connectionist schemes violate one or two. For example, symbol manipulation of the sort found in production systems does not seem to occur in connectionist networks. We will return to the complex issues raised by connectionist networks later in the book.
Those aspects of cognition that are intact or impaired are identified, with this information being of value for two main reasons. First, the cognitive performance of brain-damaged patients can often be explained by theories within cognitive psychology. Such theories specify the processes or mechanisms involved in normal cognitive functioning, and it should be possible in principle to account for many of the cognitive impairments of brain-damaged patients in terms of selective damage to some of those mechanisms.
Second, it may be possible to use information from brain-damaged patients to reject theories proposed by cognitive psychologists, and to propose new theories of normal cognitive functioning. According to Ellis and Young , p.
The intention is that there should be bi-directional influences of cognitive psychology on cognitive neuropsychology, and of cognitive neuropsychology on cognitive psychology. Historically, the former influence was the greater one, but the latter has become more important.
Before discussing the cognitive neuropsychological approach in more detail, we will discuss a concrete example of cognitive neuropsychology in operation. Atkinson and Shiffrin argued that there is an important distinction between a short-term memory store and a long-term memory store, and that information enters into the long-term store through rehearsal and other processing activities in the short-term store see Chapter 6.
Relevant evidence was obtained by Shallice and Warrington They studied a brain-damaged patient, KF, who seemed to have severely impaired short-term memory, but essentially intact long-term memory.
The study of this patient served two important purposes. First, it provided evidence to support the theoretical distinction between two memory systems. Second, it pointed to a real deficiency in the theoretical model of Atkinson and Shiffrin If, as this model suggests, long-term learning and memory depend on the short-term memory system, then it is surprising that someone with a grossly deficient short-term memory system also has normal long-term memory.
The case of KF shows very clearly the potential power of cognitive neuropsychology. The study of this one patient provided strong evidence that the dominant theory of memory at the end of the s was seriously deficient. This is no mean achievement for a study on one patient! Cognitive neuropsychological evidence How do cognitive neuropsychologists set about the task of understanding how the cognitive system functions?
A crucial goal is the discovery of dissociations, which occur when a patient performs normally on one task but is impaired on a second task. In the case of KF, a dissociation was found between performance on short-term memory tasks and on long-term memory tasks.
Such evidence can be used to argue that normal individuals possess at least two separate memory systems. There is a potential problem in drawing sweeping conclusions from single dissociations.
A patient may perform poorly on one task and well on a second task simply because the first task is more complex than the second, rather than because the first task involves specific skills that have been affected by brain damage. The solution to this problem is to look for double dissociations. A double dissociation between two tasks 1 and 2 is shown when one patient performs normally on task 1 and at an impaired level on task 2, and another patient performs normally on task 2 and at an impaired level on task 1.
If a double dissociation can be shown, then the results cannot be explained in terms of one task being harder than the other. In the case of short-term and long-term memory, such a double dissocation has been shown. KF had impaired short-term memory but intact long-term memory, whereas amnesic patients have severely deficient long-term memory but intact short-term memory see Chapter 7. These findings suggest there are two distinct memory systems which can suffer damage separately from each other.
If brain damage were usually very limited in scope, and affected only a single cognitive process or mechanism, then cognitive neuropsychology would be a fairly simple enterprise. In fact, brain damage is often rather extensive, so that several cognitive systems are all impaired to a greater or lesser extent.
This 1. Syndromes The traditional approach within neuropsychology made much use of syndromes. It was claimed that certain sets of symptoms or impairments are usually found together, and each set of co-occurring symptoms was used to define a separate syndrome e. This syndrome-based approach allows us to impose some order on the numerous brain-damaged patients who have been studied by assigning them to a fairly small number of categories.
It is also of use in identifying those areas of the brain mainly responsible for cognitive function such as language, because we can search for those parts of the brain damaged in all those patients having a given syndrome. In spite of its uses, the syndrome-based approach has substantial problems. It exaggerates the similarities among different patients allegedly suffering from the same syndrome. In addition, those symptoms or impairments said to form a syndrome may be found in the same patients solely because the underlying cognitive processes are anatomically adjacent.
There have been attempts to propose more specific syndromes or categories based on our theoretical understanding of cognition. However, the discovery of new patients with unusual patterns of deficits, and the occurrence of theoretical advances, mean that the categorisation system is constantly changing.
Some cognitive neuro-psychologists e. The potential problem with this rule is that a group of patients can show a significant effect even though a majority of the individual patients fail to show the effect.
Ellis argued that cognitive neuropsychology should proceed on the basis of intensive single-case studies in which individual patients are studied on a wide range of tasks. The great advantage of this approach is that there is no need to make simplifying assumptions about which patients do and do not belong to the same syndrome.
Another argument for single-case studies is that it is often not possible to find a group of patients showing very similar cognitive deficits. As Shallice , p.
If our theoretical understanding of an area is rather limited, it may make sense to adopt the syndrome-based approach until the major theoretical issues have been clarified. Furthermore, many experimental cognitive psychologists disapprove of attaching great theoretical significance to findings from individuals who may not be representative even of braindamaged patients.
A reasonable compromise position is to carry out a number of single-case studies. If a theoretically crucial dissociation is found in a single patient, then there are various ways of interpreting the data.
However, if the same dissociation is obtained in a number of individual patients, it is less likely that all the patients had atypical cognitive systems prior to brain damage, or that they have all made use of similar compensatory strategies. Modularity The whole enterprise of cognitive neuropsychology is based on the assumption that there are numerous modules or cognitive processors in the brain.
These modules function relatively independently, so that damage to one module does not directly affect other modules. Modules are anatomically distinct, so that brain damage will often affect some modules while leaving others intact. Cognitive neuropsychology may help the discovery of these major building blocks of cognition. A double dissociation indicates that two tasks make use of different modules or cognitive processors, and so a series of double dissociations can be Syndrome-based approach vs.
Allows identification of cognitive functions of brain areas. Useful while major theoretical issues remain to be clarified.
Disadvantages Oversimplification based on theoretical assumptions. Exaggeration of similarities among patients. Advantages Avoids oversimplifying assumptions, No need to find groups of patients with very similar cognitive deficits. Disadvantages Evidence lacks generalisability and can even be misleading. However, many psychologists have criticised mandatory operation and innateness as criteria for modularity. Some modules may operate automatically, but there is little evidence to suggest that they all do.
It is implausible to assume the innateness of modules underlying skills such as reading and writing, as these are skills that the human race has developed only comparatively recently.
From the perspective of cognitive neuropsychologists, these criticisms do not pose any special problems. If the assumptions of information encapsulation and domain specificity remain tenable, then data from brain-damaged patients can continue to be used in the hunt for cognitive modules. Planning of speech. Theories of speech production. Chapter summary Further reading. Problemsolving andexpertise Introduction Problem solving. Chapter summary Further reading 5 Attention and performance.
Direct perception Visually guided action. Perception ofhuman motion. Automatic processing. Autobiographical memory.
Architectureof memory. Theories offorgetting Chapter summary Further reading. Introduction Episodic vs semantic memory. Nondeclarative memory.
Chapter summary. Whorfian hypothesis. Cognitive neuropsychology. Marketing Communications. Elmes, D. Research Methods In Psychology 7th. Kantowitz, B. Results 1 - 20 of Psychology Press. Keane, Mark T. Cognitive Psychology. Oxford: Oxford University Press.
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Social cognition: From brains to culture. Higgs et al. Biological Psychology First edition Sage Edge. Workman, Lance, and Will Reader. Evolutionary psychology.
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