Dan J. Stein, M.D.





Dept of Psychiatry

College of Physicians and Surgeons, Columbia University,

and the New York State Psychiatric Institute,

722 W 168 St

NY, NY 10032






Running Title: Cognitive Science and Psychiatry

Tel: 212-960-2355



















Cognitive science is a multidisciplinary field, comprising cognitive

psychology, artificial intelligence, linguistics, neuroscience, and

anthropology. In recent years, cognitive science has become a

predominant paradigm in studies of the mind. This paper reviews work

at the emerging interface between cognitive science and psychiatry.

It is argued that cognitive science has significant potential as an

integrative framework for theorizing and researching psychiatric

disorders and their treatment.












































Cognitive science is a relatively new field that incorporates concepts

and methods from philosophy, cognitive psychology, artificial

intelligence, linguistics, neuroscience and anthropology (Gardner,

1985; Posner, 1989). Whereas behaviorism dominated the psychological

sciences during the first part of this century, cognitive science has

become a central paradigm of the latter part. This "cognitive

revolution" was fostered by the promise of cognitive science as an

integrated and fertile approach to the mind. Indeed, departments of

cognitive science have become important loci of interdisciplinary

research and have generated a prodigous literature.



During the period of the cognitive revolution, significant changes

also took place in psychiatry (Lipowski, 1989). During the 1950s,

psychoanalysis comprised a dominant school in many departments of

psychiatry. In subseqent decades, however, a community-focused model

was widely touted. Most recently, neurobiological approaches have

been given pride of place. Certainly, there have been calls for a

synthetic or "biopsychosocial" approach to psychiatric disorders and

treatment. Nevertheless, there has been little progress on the

construction of an integrative framework for such an approach.



On the whole, cognitive scientists have paid little attention to

clinical phenomena, while clinicians have in turn only occasionally

employed the concepts and methods of cognitive science. In recent

years, however, dialogue between the two fields has increased (Breger,

1969; Mahoney and Freedman, 1985; Ingram, 1986; Horowitz, 1988a;

Williams, Fraser, MacLeod, and Mathews, 1988; Magaro, 1991; Stein and

Young, 1992a). In this paper I review research at this intersection,


and discuss its potentials and limitations. I suggest that cognitive

science can provide an important integrative framework for psychiatry.






What exactly is cognitive science? The following three sections

attempt to address this question. I briefly discuss descriptions and

definitions of cognitive science, its origins and subdisciplines, and

then contrast and compare cognitive science with behaviorist,

psychoanalytic and neurobiological models (Stein, 1992a).



a) Descriptions and Definitions



In general, cognitive scientists are interested in mental structures

and processes, their representational significance, and their physical

instantiation (Stillings, Feinstein, Garfield, Rissland, Rosenbaum,

Weisler, and Baker-Ward, 1987). Several authors have attempted more

rigorous definitions of cognitive science. A cognitive

information-processing account, for example, views the mind as an

information-processing system that selects, transforms, encodes,

stores, retrieves, and generates information and behavior (Lachman,

Lachman, and Butterfield, 1979). A computational view, on the other

hand, emphasizes that, "Cognitive science, sometimes explicitly, and

sometimes implicitly, tries to elucidate the workings of the mind by

treating them as computations, not necessarily of the sort that is

carried out be the digital computer, but of a sort that lies within

[the] broader theory of computation" (Johnson-Laird, 1988, p. 9).



Restrictive definitions of cognitive science may, however, include

only one or other of the divergent models that cognitive scientists


have developed. Early cognitive scientists viewed the mind as a

sequential processor, similar to the early digital computer. The mind

was seen as a passive recipient of information, which was registered

in a short-term memory, and perhaps encoded in a long-term memory.

More recent cognitive scientists have, however, pointed out that the

mind is a parallel processor (Rumelhart, Hinton, and the PDP Research

Group, 1986), and have emphasized that mental structures are active

and that they occur within a particular context (Neisser, 1976;

Lakoff, 1987). Such work may be excluded by a definition of cognitive

science that focuses solely on information-processing and computation.



On the hand, too broad a definition of cognitive science may prevent a

constrast between cognitive science models and other models often used

by clinicians. It may be useful to at least specify the broad

categories into which cognitive science models fall. Cognitive

science models typically specify cognitive architecture in one of two

ways, symbolic and connectionist. The elements of symbolic systems

are symbols, which are stored in associative structures. Symbolic

systems include levels-of-processing models (Craik and Lockhart,

1972), spreading activation constructs (Collins and Loftus, 1975), and

schema approaches (Neisser, 1976). The elements of connectionist

systems are simplified and schematized neurons which are

interconnected in a network. Again, a variety of these parallel

processing models have been developed (Rumelhart et al., 1986). In

subsequent sections the application of both symbolic and connectionist

architectures to clinical theory and practice is reviewed.



b) Origins and Subdisciplines



Further understanding of cognitive science can be gained by discussing


its origins. The development of cognitive science models was

encouraged by various factors, including the failure of behaviorism,

the invention of the computer, and various theoretical advances

(Gardner, 1985). One of the most important of these theoretical

advances was the development of computer science. The father of this

field was Turing (1936), a British mathematician who described a

simple machine (the Turing machine) that executed instructions in

binary code, and proposed that such a machine could in principle

perform any computational task. He also described the idea of a

universal Turing machine which takes a coded version of other Turing

machines as input and then emulates their behavior.



Computer science can immediately be seen as relevant to psychology,

for the question arises of whether the human mind can be instantiated

on a universal Turing machine. If so, computer science would

constitute a basic science for exploring the hypothesis (Craik, 1943)

that the mind is a symbol manipulating device. Turing (1950)

suggested it might be possible to program a machine so that a user

communicating with the machine and with a person would be unable to

differentiate the two (the Turing machine test).



A number of other developments consolidated the importance of

computational constructs for psychology. Thus, it was proposed that

certain concepts were useful in explaining both computing machines and

human brains. This was clearly formulated at a seminal meeting in

1948, the Hixon Symposium on "Cerebral Mechanisms in Behavior"

(Jeffress, 1951) at which McCulloch, a professor of psychiatry, and

Von Neumann were the opening speakers. For example, the all-or-none

property of neuronal activation can be compared with the determination

of Boolean statements as either true or false. Furthermore, neuronal


networks and Boolean statements can be described in elecrical terms as

current that passed or failed to pass in a circuit.



In addition, it was argued that certain constructs were useful in

explaining both computing machines and human minds. Hebb (1949), for

example, suggested that synaptic strengthening in neuronal networks

led to learning. Wiener (1947) proposed that machines and minds that

had feedback mechanisms that displayed purposefulness. Central to

control and communication engineering was the notion of the message,

whether this was transmitted by electrical, mechanical, or neural

means. Information, Shannon (1938) showed, was independent of its

physical instantiation.



It has been suggested that cognitive science was founded in September

1956, at the Symposium on Information Theory at MIT (Gardner, 1985).

Significant research presented at the conference included papers by

the cognitive psychologist, Miller, artificial intelligence workers,

Newell and Simon, and the linguist, Chomksy. In his paper, Miller

illustrated the importance of empirical studies of cognition by

discussing work on the constraints of short-term memory processes.

Work by other psychologists in the 1950s, including Broadbent and

Cherry in Britain, and Bruner and colleagues at Harvard, gave further

impetus to the development of cognitive psychology, and established

the discipline and its empirical methodologies as a cornerstone of

cognitive science. Newell and Simon argued that artifial intelligence

was possible, and drew comparisons between artificial and human

problem solving processes. Together with Minsky and McCarthy they

pioneered the field of artificial intelligence, and helped establish

the importance of a computational methodology for cognitive science.

Finally, Chomsky described his theory of a grammar based on linguistic


transformations. This work, together with his scathing review

(Chomsky, 1959) of Skinner's work on verbal behavior buttressed the

shift from behaviorism to cognitivism, and established linguistics as

a useful frame from which the issues of cognitive science could be




Other core disciplines of cognitive science include neuroscience,

anthropology, and philosophy. Neuroscience comprises a lower limit

for cognitive science, for human cognitive structures and processes

are ultimately based in and constrained by neuroanatomy and

neurochemistry. Anthropology and social psychology constitute an

upper limit for cognitive science, for cognitive structures and

processes vary from place to place and time to time. Finally, many of

the questions studied by cognitive scientists were first raised by

philosophers. Philosophers have also addressed the foundational

principles of the discipline, and more recently, as cognitive science

has advanced, have been faced with the meta-cognitive question of what

the mind and the world are like for this scientific advance to have

taken place.



Developmental psychology is not usually listed as a central discipline

of cognitive science. Nevertheless, one of the most important

pre-cognitivists was the developmental psychologist Piaget. Piaget

detailed the transformation of mental structures from sensorimotor

reflexes to the operations of formal thought (Piaget, 1952).

Contemporary dialogue between developmental psychology and cognitive

science is increasing (Sternberg, 1984; Meltzoff, 1990; Globerson and

Zelniker, 1989).





c) Contrasts and Comparisons



Cognitive science models can be contrasted and compared with the

clinically familiar models of behaviorism, psychoanalysis, and

neurobiology. Behaviorism, for example, self-consciously makes the

mind into a "black box", asserting that only observable stimuli and

responses can be studied. In contrast, the cognitive model holds that

what is most interesting are the mental structures in the "black box"

and the processes (operations) whereby they generate cognitive

products (thoughts and feelings).



Nevertheless, it is possible to see a continuity between behaviorist

and cognitive science models. While the behaviorist model is limited

to inputs (stimuli) and outputs (responses), the cognitivist model is

concerned with inputs, processing, and outputs. Like behaviorists,

cognitivists have adopted an empirical stance, which emphasizes the

importance of careful measurement and laboratory experimentation.



The classical psychoanalytic model of the mind was an energy-based

one. For Freud (1894), "in mental functions something is to be

distinguished - a quota of affect or sum of excitation - which

possesses all the characteristics of a quantity (though we have no

means of measuring it), which is capable of increase, dimunition,

displacement and discharge, and which is spread over the memory-traces

of ideas somewhat as an electric charge is spread over the surface of

a body". Freud described how the forces of the unconscious are

expressed, transformed, or repressed, resulting in everyday behaviors

and psychopathology.



Again, however, it is possible to demonstrate a continuity between


psychoanalysis and cognitive science. Cognitive science and

psychoanalysis both focus on the structures of the mind, and the way

in which these determine mental phenomena. Furthermore, in Freud's

later work he describes affect not in terms of energy, but in terms of

its role as a signal. Finally, post-Freudian psychoanalysts,

including the self psychologists, the objects relations school, and

the interpersonalists, have increasingly employed cognitively oriented

constructs such as self and other representations (Stein, 1992b).



Neurobiological models attempt to explain the biological basis of

mental processes and products. Proponents of these models may state

that all psychological explanations are reducible to neurobiological

ones. This view contrasts with the cognitive science argument that

cognitive phenomena necessarily require psychological explanations.

Psychological events are emergent phenomena, and psychological

explanations are not reducible to biological ones.



Once again, however, it is possible to see a continuity between the

biological model and cognitive science. Earlier neuroscience was

described as comprising a lower limit of cognitive science. While

some cognitivists are interested in information-processing in only the

most abstract sense, many others are interested specifically in how

information-processing occurs in the human neurobiological substrate.

This interest is particularly apparent in connectionist work informed

by neuroscience (Rumelhart et al, 1986).






For the clinician, the question immediately arises of whether

cognitive science models are useful in accounting for clinical


phenomena. However, standard texts of cognitive science make little

reference to psychiatric disorders and treatment. Nevertheless, a

number of developments in cognitive science have been instrumental in

allowing a bridge to clinical phenomena. This section briefly reviews

some of these bridges from cognitive science to the clinic, including

research on emotional and unconscious processing, and relevant work in

each of the subdisciplines of cognitive science.



Cognitive science has been characterized by a disregard for emotion

(Gardner, 1985). Nevertheless, humans are not only the most

intelligent of the animals, they are perhaps also the most emotional

(Hebb, 1946). Furthermore, it may be suggested that this relationship

between intelligence and emotionality is a necessary one. In a

seminal paper, Simon (1967) argued that emotion in humans is

comparable to the prioritized interruption of different processes by

one another in complex artificial intelligence systems with multiple

goals and limited resources. The idea that cognitive design problems

are solved by emotional processes remains popular in contemporary

cognitive science attempts to theorize emotion (Oatley and

Johnson-Laird, 1987; Sloman, 1987), and has helped generate a

rapidly growing empirical literature on cognitive-affective

processing. Cognitivist work on emotion has subsequently been

employed in order to understand affective experience and change in the

clinic (Mandler, 1975; Greenberg and Safran, 1990).



Another important area within cognitive science that has clinical

relevance is the study of unconscious processing. Research on the

unconscious is not new, and includes the pioneering work of Helmholtz,

Janet, and Freud (Ellenberger, 1970). However, it was not until the

emergence of cognitive science that the "cognitive unconscious"


(Kihlstrom, 1987) became a respectable area of study. Research has

focused on such areas as selective attention, subliminal perception,

implicit memory, hypnotic suggestion, and dreaming (Erdelyi, 1985;

Foulkes, 1985; Kihlstrom, 1987). While this work immediately brings

psychoanalysis to mind, there appear to be important differences

between the cognitive unconscious and the psychoanalytic unconscious

(Bowers and Meichenbaum, 1984). According to Freud, the unconscious

is a set of drives, affects, and motives that has an organization and

content more primitive than those of the consciousness, but that

nevertheless has latent the potential for interacting with other

elements of the psyche. According to cognitive science, the

unconscious is a set of cognitive processes, including attitudes and

predispositions, that act prior to consciousness, so actively

organizing and ordering experience and behavior. Nevertheless,

contemporary work on unconscious processing establishes a dialogue

between cognitive and clinical scientists (Bowers and Meichenbaum,

1984; Eagle, 1986; Horowitz, 1988b; Safran and Greenberg, 1986; Uleman

and Bargh, 1989; Singer, 1990; Prigatano and Schachter, 1991; Cloitre,

1992; Stein, 1992b).



A number of early cognitivists have been interested specifically in

psychiatric disorders. Ruesch and Bateson (1968) were among the first

to apply cybernetic concepts to psychopathology and psychotherapy.

Within cognitive psychology, Hilgard (1977), whose work will be

discussed later, employed Janet's notion of dissociation and developed

a neodissociative model of the dissociative disorders. This work

exemplified the potential utility of employing cognitive psychology

constructs to conceptualize psychiatric disorders.



In artificial intelligence, Colby (1981) pioneered the investigation


of clinical phenomena. He developed a program, PARRY, which

incorporated a model of the paranoid process, and succeeded in

simulating a paranoid patient. The difficulty of such work, and

Colby's achievement, is illustrated by the limited amount of

subsequent research in this area (Tomkins and Messick, 1963;

Clippinger, 1977). More recently, however, a number of authors have

employed computer implemented neural networks to model psychopathology

and psychotherapy (Hoffman, 1987; Hestenes, 1991; Cohen and

Servan-Schreiber, 1992l; Williams and Oaksford, 1992; Caspar,

Rothenfluh, and Segal, unpublished manuscript).



Linguists, neuroscientists, anthropologists and social psychologists

have long been interested in clinical phenomena, and some of this work

has fallen within the realm of clinical cognitive science.

Cognitivist models of the aphasias have their origins in the work of

the "diagram-makers", who constructed modular models of the mind at

the turn of the century (Morton, 1984). Current cognitive studies of

language may contribute to various clinical areas, such as treatment

of dyslexia (Swerling and Sternberg, 1992), or understanding clinical

dialogue and the mechanisms of the "talking cure" (Oatley, 1992).

Contemporary cognitive neuropsychologists continue to hold that study

of neurologically impaired patients contributes to cognitive theories

of mind (Caramazza, 1992). Clinical anthropology has tended not to

adopt cognitivist models (Stein, 1992c), but cognitively oriented work

in social psychology has been particularly relevant to clinical

science, and has tackled such important concerns as self and other

representations, and their role in mood disorders (Markus, 1977;

Cantor and Kihlstrom, 1981; Sorrentino and Higgins, 1986; Westen,

1988). Finally, it may be argued that philosophy, too, constitutes an

important foundational discipline for clinical cognitive research


(Mahoney, 1991; Lyddon, 1988; Stein, 1992d).



Developmental psychologists have long been interested in developmental

arrests and abnormalities. Since Piaget, cognitive concepts have

increasingly been used in this area. Developmental research that

draws on cognitive science constructs and focuses on clinical

implications has been particularly influential (Greenspan, 1980;

Stern, 1985; Emde, 1983).






The work of cognitive scientists interested in clinical phenomena

provides the basis for employing cognitive constructs to conceptualize

psychiatric disorders, assessment, and treatment. I will discuss each

of these areas in turn. While a variety of psychiatric disorders have

been studied from a cognitive science perspective, I will focus on

only a few in order to highlight some important methods and issues in

clinical cognitive science.



a) Major Depression



Since their introduction by Ellis, Beck and others, cognitive

therapies have become increasingly accepted as an effective treatment

of depression (Mahoney and Freeman, 1985). While these therapies are

not necessarily formal extensions of cognitive science, much of this

work has been influenced by the cognitive revolution. The growing

dialogue between cognitive science and cognitive models of depression

(Ingram and Reed, 1986; Ingram and Wisnicki, 1991) provides the most

comprehensive exemplar of the use of symbolic architectures from

cognitive science to understand psychopathology.


Symbolic architectures specify the mind in terms of cognitive

structures, operations, and processes. Cognitive structures that have

been hypothesized to be central in depression include associative

networks (Ingram, 1984; Teasdale, 1983) and self-schemas (Beck, 1967;

Kuiper, Derry, and MacDonald, 1982). Associative network theories

characterize depression as having increased availability and/or

accessiblity of negative constructs about the self. Self-schema

theory characterizes depression as activation of a self-structure that

is negative in content. While evidence for negative self-schemas in

depression is good, there is less evidence that such schemas are

present in the absence of current depression (Ingram and Reed, 1986;

Ingram and Wisnicki, 1991).



Research also suggests that cognitive processes in depression are

characterized by a negative selectivity bias (Ingram and Reed, 1986;

Ingram and Wisnicki, 1991). Studies of encoding may be divided into

studies of personal semantic information (i.e. information related to

concepts of self) and episodic information (i.e. information related

to autobiographical events). Studies of semantic encoding indicate

that enhanced negative encoding is a key factor in information

processing in depression, while studies of episodic encoding indicate

that less accurate encoding of positive information is critical.

Studies of retrieval, on the other hand, suggest that negative

information is more efficiently and positive information is less

efficiently retrieved in depression. In addition, depressed patients

selectively monitor negative information with a decrease in attention

to positive stimuli.



Finally, cognitive products in depression include attributions and

automatic thoughts (Ingram and Reed, 1986; Ingram and Wisnicki, 1991).


Depressed patients are more likely to make dysfunctional attributions

as to the cause of events. Negative automatic thoughts appear to be

characteristic of subclinical and clinical depression, and they remit

with treatment.



Cognitive science models of depression influence our conceptualization

of psychotherapy, and direct further empirical research. The finding,

for example, that depressed schemas are not present in the absence of

depression suggests that cognitive therapy works not by structural

changes in underlying schemas, but by changes in the activation level

of negative self-schemas. While cognitive structures such as schemas

are difficult to measure, methodological progress has been made

(Segal, 1988). Considerable theoretical and empirical research on

cognitive science models of depression nevertheless remains to be

done. In particular, cognitive science models of depression have,

with few exceptions (Klein, 1976), failed to incorporate

neurobiological knowledge.



b) Dissociative and Conversion Disorders



Symbolic architectures, including schema theory, have not only been

adopted by the cognitive therapy tradition, but have also been

employed in psychoanalytically informed research (Wachtel, 1982; Slap

and Saykin, 1983; Segal, 1988; Horowitz, 1988a; Horowitz, 1991). The

area in which there is perhaps most clearly an intersection between

the constructs of symbolic architecture and psychodynamic theory is

the study of dissociative and conversion disorders.



The first detailed psychological theory of dissociative and conversion

disorders was developed by Janet (1907). Like Freud, Janet studied at


Charcot's clinic at the Salpetriere. He too was interested in the

notion of cognitive processes that took place outside of awareness,

for which he coined the term "subconscious". Janet described the mind

in terms of "automatisms", or elementary structures controlling

experience, thought, and action in various domains, and which together

make up the flow of consciousness. At times of stress or exhaustion,

one or more automatisms separate from the rest, breaking the unity of

consciousness. The dissociated automatisms continue to operate, but

are no longer accessible to phenomenal awareness or amenable to

voluntary control, resulting in various dissociative or conversion




Hilgard (1977) used concepts from cognitive psychology to provide a

neodissociative account of these disorders. He described the mind in

terms of subordinate cognitive structures each with a degree of

autonomy, a hiererarchical control managing the competition between

these structures, and a central monitoring and controlling structure

(the executive ego). Subordinate cognitive structures can operate

outside of awareness, or they may be processed consciously through the

executive ego. Certain physiological (e.g. anesthesia) or

psychological (e.g. hypnosis) conditions lead to disruptions in the

connections between the subordinate structures. Information

processing in the subordinate structures may then take place outside

of phenomenal awareness or voluntary control. More recently,

Kihlstrom (1990) has used an associative-network model of memory to

further elaborate this view of the dissociative and conversion

disorders. He describes how disruption of links between

representations of memory or of sensory input and representations of

self may result in lack of awareness of particular memories or

sensations, with continued processing of related representations.


While psychoanalytic theory has also emphasized the importance of

unconscious processes in the genesis of these disorders,

neodissociative theory has a view of the unconscious that is

closer to that of cognitive science. Although there may be

theoretical difficulties with the psychoanalytic energy based view,

the success of the cognitivist revival of Janet's ideas ultimately

depends on its ability to generate empirical work on these relatively

unresearched disorders.



c) Obsessive-Compulsive Disorder



Earlier the question of the relationship between cognitive science and

neurobiological models was raised. This becomes particular relevant

for the clinical cognitive science of disorders about which

neurobiological knowledge is advancing. Current research on OCD, for

example, has demonstrated involvement of the serotonergic system and

orbitofrontal-basal ganglia-thalamic pathways, and the disorder is

increasingly seen as having a neurobiological basis (Stein and

Hollander, 1992).



Cognitive science constructs may, however, be helpful in thinking

through the relationship between neurobiological findings and the

psychology of OCD. Several authors have, for example, suggested that

neuroanatomical structures involved in OCD play a role in

goal-feedback mechanisms (Gray, 1982; Rapoport and Wise, 1988).

Disruption of cybernetic control in OCD results in psychological

features such as repetitive symptoms and strategies of seeking control

(Pitman, 1987).



Work on neuropsychiatric impairment and serotonergic dysfunction in


OCD has led Stein and Hollander (1992) to propose that OCD may involve

a biologically based impairment in determining or in evaluating

goal-feedback responses. Some patients, perhaps those with high

neurological soft signs, visuospatial difficulties and rapid erroneous

responses on neuropsychological testing, may have difficulty in

determining goal-feedback responses. Other patients, perhaps those

with serotonergic dysfunction and slow correct responses on

neuropyschological testing, may overevaluate harm associated with

goal discrepancy.



This model suggests that both biological approaches (normalizing

serotonergic function) and psychological approaches (changing harm

assessment) may be helpful in the treatment of OCD. On the other

hand, in patients where goal-feedback response impairment is

associated with evidence of structural brain damage, treatment may be

less successful. The model provides a heuristic for further research

correlating biological, cognitive, and clinical variables in OCD.



d) Psychotic Disorders



Sincle the time of Kraepelin and Jung, psychiatrists have used

techniques from experimental psychology to explore

information-processing deficits in psychotic disorders. More

recently, cognitive science methods have been used to study these

disorders. There is now a large literature on information-processing

in schizophrenia (Magaro, 1980; Neuchterlein and Dawson, 1984;

Saccuzzo, 1986), and some work on mania (Grossman and Harrow, 1991).

In their review, Neuchterlein and Dawson (1984) highlight two types of

information-processing deficits in schizophrenia - poorer detection of

single, highly familiar stimuli during vigilance, and increases in the


time required to recognize an uncomplicated stimulus.

Information-processing tasks may constitute indicators of

vulnerability, may have prognostic value, and may be useful measures

of medication response. Information-processing deficits in

schizophrenia may also be conceptualized in schema terms (Magaro,

1980). Finally, a number of theorists have attempted to integrate

information-processing and neurobiological findings (Neuchterlein and

Dawson, 1984).



Of considerable current interest, however, is work that employs

connectionist architectures from cognitive science to study psychotic

disorders. This work is of particular interest insofar as

connectionist models succeed in incorporating neurobiological

knowledge. In an early paper Hoffman noted that different

perturbations of a particular kind of network (the Hopfield network)

led to different forms of neural dysfunction (Hoffman, 1987). Memory

overload led to disturbances similar to those seen in schizophrenia,

while increased randomness led to disturbances similar to those seen

in mania. Neural dysfunction in perturbed Hopfield networks is,

however, only loosely similar to that seen in psychosis, and the

neurobiological viability of these perturbations is arguable.



A more recent connectionist model is that of Cohen and

Servan-Schreiber (1992). Their neural network simulates performance

of schizophrenic patients on tasks related to the processing of

context. Furthermore, their network incorporates the neurobiological

finding that dopamine has a modulatory effect on prefrontal cortex by

influencing the responsivity, or gain, of cells in this region. Thus,

their model simultaneously posits that schizophrenia is characterized

by a particular information-processing deficit with a specific


neurobiological underpinnning, and provides a novel and robust 17

methodology to explore this deficit.



e) Other Disorders



There are several other disorders which can be understood in terms of

cognitive science constructs. Space considerations preclude a

discussion of anxiety disorders (Rapee, 1991; Eysenck, 1991), autism

(Litrownik and McInnis, 1986), impulsive (Barratt, 1987) and

antisocial (Gorenstein, 1991) behavior, learning disability (Swerling

and Sternberg, 1992), memory disorders (Shimamura, 1989), personality

disorders (Stein and Young, 1992b), and substance abuse (Hull and

Reilly, 1986).






Conceptualizing various psychiatric disorders in terms of cognitivist

constructs immediately raises the question of employing cognitive

science in clinical assessment. Cognitive science has assessment

constructs that differ from those of more traditional frameworks

(106). In general, cognitivists attempt to use empirical methods to

assess the particular psychological structures and processes

responsible for generating mental events. Many of these methods may

be useful in clinical assessment, for example, of neuropsychological

impairment (Delis, Kramer, Fridlund, Kaplan, 1990), or of maladaptive

schemas of self and other (Young, 1990; Horowitz, 1991).



The variety and range of paradigms and techniques developed by

cognitive scientists holds promise for their application to clinical

measurement (Merluzzi, Rudy, and Glass, 1981). It may however be


necessary to modify cognitive science laboratory methods before

employing them in the clinic. For example, early

information-processing studies in patients with depression did not to

use stimuli with negative and depressive content, and therefore failed

to elucidate relevant cognitive structures and processes (Ingram and

Reed, 1986).



On the other hand, the clinical setting may allow for more precise

assessment than is available to most cognitive scientists. For

example, measurement of schemas in personality disorder by self-report

questionnaires is problematic, as patients may not be aware of or may

avoid their schemas. However, during psychotherapy schemas are

explored in various ways and links are drawn between the patient's

behaviors and these schemas (Young, 1990). In this way psychotherapy

techniques allow assessment to move beyond laboratory based cognitive

science methods.






How can a cognitive science approach to psychiatric disorders and

their assessment contribute to psychiatric treatment? Clearly, the

reformulation of any particular disorder in cognitivist terms will

lead to conceptualization of the treatment of that disorder in the

same terms. Thus, the paper has already alluded to the treatment of

negative self-schemas in depression, and the treatment of maladaptive

person schemas in personality disorder. Perhaps more important,

however, is the idea that cognitive science contributes to the theory

of treatment integration. In recent years there have been frequent

calls for psychotherapy integration and for the integration of

psychotherapy and pharmacotherapy, but there has been little work on


the development of theoretical frameworks that allow such an

integration to take place.



It is notable, however, that within contrasting schools of therapy,

there have been shifts to an increasingly cognitive orientation. The

cognitive-behavioral treatment tradition has moved from behaviorist

models to linear cognitive models to more complex cognitive models

(Dobson, 1988). Psychoanalysis has moved away from energy based

models to more cognitivist ones, and several psychoanalysts, beginning

with Blum (1961) and Peterfreund (1971), have pointed to the value of

cognitive science for psychoanalytic meta-theory (Clippinger, 1977;

Erdelyi, 1985; Westen, 1988; Horowitza, 1988; Stein, 1992b). Finally,

neurobiological findings are increasingly being incorporated into

clinical cognitive science models.



Schema theory, for example, has allowed both cognitive-behaviorists

(Beck, 1967; Young, 1990; Beck, Freeman and Associates, 1991) and

psychoanalysts (Horowitz, 1988a, 1991; Klein, 1976; Wachtel, 1982;

Slap and Saykin, 1983) to focus on mental structures, their biological

basis, their development and change, and on the way in which they

direct psychological events (Stein, 1992e). Similarly, neural network

models may allow an integrative conceptual approach to these issues

(Caspar, Rothenfluh, and Segal, unpublished manuscript; Forrest,

1991). Insofar as cognitive science has conceptual continuities with

other approaches, but does not have their weakness (e.g., emphasizes

empirical methods but avoids reduction of mind to stimulus-response

chains, focuses on mental structures but avoids an energy based

meta-psychology), it may have theoretical advantages. Furthermore,

conceptual reformulation may also foster technical integration.

During psychotherapy, for example, schema change can then be


undertaken by means of affective, cognitive, behavioral, and

interpersonal interventions (Young, 1990).






A number of advantages of clinical cognitive science are immediately

apparent. First, it offers integrative theoretical models of clinical

disorders, assessment, and treatment. Whereas so much contemporary

clinical science may be criticized for being either mindless or

brainless (Lipowski, 1989), clinical cognitive science offers a

multifaceted approach that incorporates and extends earlier paradigms.

In addition, it employs a number of methodologies which encourage

empirical research. Clinical cognitivists have researched clinical

phenomena outside the office, and have introduced new scales and

measures into the clinic. Conversely, the study of clinical phenomena

may enrich cognitive science (Stein, 1992a). Nevertheless, a number

of criticisms of clinical cognitive science may also be offered. The

foundations of cognitive science have been extensively debated in its

subdiscipline of philosophy; here I will focus on more clinically

oriented issues.



A first objection states that clinical cognitive science is overly

general or that it is "old wine in a new bottle". The psychoanalytic

clinician may feel that he or she uses cognitive science concepts and

methods, but simply employs an older terminology. Clinicians with a

cognitive-behavioral orientation may feel that clinical work is

primarily a pragmatic exercise and that it is unnecessary to introduce

extraneous theoretical baggage. Thus cognitive science may be seen as

only reframing cinical theory, rather than advancing it. I would

argue, however, that more accurate reframing constitutes an essential


part of scientific progress. Psychoanalysts who reject energy based

models, for example, are faced with the choice of discarding

metapsychology or of viewing psychoanalysis as a hermeneutic rather

than scientific enterprise. In providing a possible theoretical

conceptualization of psychodynamic work, cognitive science immediately

goes beyond mere translation of older terminology (Stein, 1992b).

Similarly, while cognitive therapists and cognitive scientists could

conceivably work independently of one another, reframing clinical

phenomena in terms of cognitive science may have immediate advantages.

Successful reframing leads to more comprehensive and powerful models,

and encourages novel methods of treatment and research (Stein, 1992e).



A converse objection is that cognitivist and computational models are

overly restricted or insufficiently complex. The word "cognitivist"

itself points to a lack of focus on emotion. Computational machines

operate along automatic and rigid lines, whereas humans have

context-dependent and fallible minds. Clinicians with a strong

neurobiological or sociocultural orientation may doubt the ability of

cognitivist models to include biological or sociocultural findings.

Clinicians with an experiential or phenomenological orientation are

particularly likely to question the value of a computational model in

understanding human perceptions, feelings, and experiences.



I would suggest that this criticism is partially correct and partially

incorrect. The criticism is wrong insofar as it suggests that the

object of cognitive science models is to replicate human minds. It is

a truism that there are differences between computers and humans, but

it does not follow that computational models cannot help us understand

human minds. This distinction can be illustrated by the debate

between Colby (1977), the author of PARRY, and Weizenbaum (1976), who


developed a program called ELIZA, that simulated a psychotherapy

session. Colby is a strong supporter of clinical cognitive science.

However, when Weizenbaum noted that people took his program as an

indication that psychotherapists could be replaced by computers, he

emphasized the limitations of cognitive science, noting that computers

should not be allowed to take over certain human tasks. However, the

issue is not whether computers can or should replace minds, but rather

whether cognitive science models can and ought to be used to

conceptualize and investigate minds. It is noteworthy that whereas

PARRY was based on a specific model of paranoid processes (and

therefore directly contributed to the science of psychopathology),

ELIZA was not a model of psychotherapy per se (and did not make a

direct contribution to the science of psychotherapy), but rather a

study of the rules of dialogue.



What is right about this criticism is that it points to the complexity

of human minds. Furthermore, early cognitivist models conceived of

the mind as a linear information-processor and may have contributed to

the development of overly simplistic clinical cognitive models.

However, current cognitive science models and clinical cognitive

models have become increasingly sophisticated. Gardner (1) has

described these developments in terms of the "computational paradox";

namely, that it took the early formal cognitivist models to describe

and elaborate the differences between the serial digital computer and

the human mind. These advances are increasingly apparent in clinical

cognitive science as well. Thus clinical cognitive science is

beginning to address both the neurobiological and the sociocultural

limits of cognitive processing. Furthermore, it may be argued that

clinical cognitive science models have begun to succeed in

incorporating both positivist concerns with empirical measurement and


hermeneutic concerns with meaning and context (72). The complexity of

human minds therefore constitutes a challenge rather than an a priori

objection to clinical cognitive science.



An important criticism of clinical cognitive science that employs

symbolic architectures involves questions of theoretical precision.

Cognitive science models of mental structures and processes vary in

important ways, and their adoption by clinicians has led to further

diversification. For example, whereas Horowitz's (1988a) division of

schemas into motivational, role, and value schemas is consistent with

Freud's division of the psyche into id, ego, and superego; Beck and

colleagues' (1991) division of schemas into cognitive, affective, and

action schemas is consistent with their view of the linear progression

of thoughts, feelings, and behaviors. Furthermore, a variety of

related concepts such as scripts, self-systems, personal constructs,

plans, and frames are popular in the cognitive and clinical

literature. This diversity may in part reflect the theoretical

fertility of cognitive science, and may be helpful in providing a

range of ideas and models. Nevertheless, the diversity also reflects

a lack of agreement about the taxonomy of representation, and a lack

of detailed knowledge about the complexities of human cognitive

architecture. Clearly, further work is necessary to clarify and

consolidate the theoretical apparatus of clinical cognitive science.



Theoretical diversity contributes to the difficulties that researchers

have experienced in measuring constructs such as schemas. Problems in

measurement are to some extent expectable with research on posited

entities which underly observable behavior. Nevertheless, there are

important unresolved complexities in determining how best to approach

the processing of information that differs in target, favorability,


content, congruence, and personal relevance (Ingram and Wisnicki,

1991). Detailed clinical observation and advances in assessment

techniques will be necessary to resolve these methodological

difficulties (Horowitz, 1991).



Clinical cognitive science that employs connectionist architectures

has emerged only recently. This field has the potential advantages of

methodological precision and of close links with neuroscience.

However, current paradigms sometimes appear removed from clinical

experience and the dialogue between connectionism and neurobiology

remains rudimentary. Further work is necessary to narrow the gap

between behavior of neural nets and clinical phenomenology, and to

integrate mechanisms of neural net perturbation with knowledge of

pathogenic mechanisms in biological psychiatry.






The interdisciplinary nature and rapid development of cognitive

science is of immediate interest to psychiatry. In this paper, I have

reviewed areas in which cognitive science and clinical science have

established a dialogue. Clinical cognitive science appears to provide

an integrative and sophisticated framework for conceptualizing and

researching psychiatric disorders and their treatment. Further

theoretical and empirical work needs to be done to consolidate this

early work. Nevertheless, there has been sufficient progress to

suggest the promotion of cognitive science as an important theoretical

framework for psychiatry, and to encourage further exploration of this









Barratt, E.S. (1987). Impulsiveness and anxiety: Information

processing and electroencephalograph topography. Journal of

Research in Personality, 21:453-463.


Beck, A.T. (1967). Depression: Clinical, Experimental, and

Theoretical Aspects. New York: Harper and Row.

Beck, A.T., & Freeman, A., and Associates (1991). Cognitive Therapy

of Personality Disorders. New York: Guilford.

Blum, G.S. (1961). A Model of the Mind. New York: Wiley.


Bowers, K.S., & Meichenbaum, D. (eds) (1984). The Unconscious

Reconsidered. New York: Wiley.

Breger, L. (ed) (1969). Clinical-cognitive Psychology: Models and

Integrations. Englewood Cliffs, NJ: Prentice-Hall.


Cantor, N., Kihlstrom, J. (eds) (1981). Personality, cognition, and

social interaction. Hillsdale, NJ: Erlbaum.


Caramazza, A. (1992). Is cognitive neuropsychology possible? Journal

of Cognitive Neuroscience, 4:80-94.


Caspar, F., Rothenfluh, T., & Segal, Z. (unpublished). The appeal of

connectionism for clinical psychology.



Chomsky, N. (1959). A review of B.F. Skinner's Verbal Behavior.

Language, 35:26-58.


Clippinger, J. (1977). Meaning and Discourse: A Computer Model of

Psychoanalytic Speech and Cognition. Baltimore: Johns Hopkins

University Press.



Cloitre, M. (1992). The avoidance of emotional processing: A

cognitive science perspective, in Stein, D.J., & Young,

J.E. (eds), Cognitive Science and Clinical Disorders. San Diego:

Academic Press.



Cohen, J.D., & Servan-Schreiber, D. (1992), Context, cortex, and

dopamine: A connectionist approach to behavior and biology in

schizophrenia. Psychol. Rev., 99:45-77.


Colby, K.M. (1981). Modeling a paranoid mind. Behavioral and Brain

Sciences, 4:515-560.


Collins, A.M., & Loftus, E.F. (1975). A spreading-activation theory

of semantic processing. Psychol. Rev., 82:407-428.


Craik, F.I.M., & Lockhart, R.S. (1972). Levels of processing: A

framework for memory research. J. Verb. Learning Verb. Behav.,




Craik, K. (1943). The Nature of Explanation. Cambridge: Cambridge

University Press.



Delis, D.C., Kramer, J.H., Fridlund, A.J., & Kaplan, E. (1990). A

cognitive science approach to neuropsychological assessment, in

McReynolds, P., Rosen, J.C., & Chelune, G.J. (eds), Advances in

Psychological Assessment. New York: Plenum Press.


Dobson, K.S. (1988). Historical and philosophical bases of the

cognitive-behavioral therapies, in Dobson, K.S. (ed). Handbook of

Cognitive-Behavioral Therapies. New York, Guilford.


Eagle, M.N. (1986). The psychoanalytic and the cognitive

unconscious, in Stern, R. (ed), Theories of the Unconscious and

Theories of the Self. Hillsdale, NJ: Erlbaum.


Ellenberger, H.F. (1970). The Discovery of the Unconscious: The

History and Evolution of Dynamic Psychiatry. New York: Basic




Emde, R.N. (1983). The prerepresentational self and its affective

core. Psychoanalytic Study of the Child. New Haven: Yale

University Press.



Erdelyi, M.H. (1985). Psychoanalysis: Freud's Cognitive Psychology.

New York: WH Freeman.



Eysenck, M.W. (1991). Anxiety and cognitive functioning: A

multifaceted approach, in Lister, R.G., & Weingartner, H.J. (eds),

Perspectives on Cognitive Neuroscience. Oxford: Oxford University




Forrest, D.V. (1991). Mind, brain, and machine: Object recognition.

J. Am. Acad. Psychoanal., 19:555-577.


Foulkes, D. (1985). Dreaming: A cognitive-psychological analysis.

Hillsdale, NJ: Erlbaum.



Freud, S. (1894). The neuro-psychoses of defense. Standard Edition,

3. London: Hogarth Press, 1962



Gardner, H. (1985). The Mind's New Science: A History of the

Cognitive Revolution. New York: Basic Books.


Globerson, T., & Zelniker, T. (eds) (1989). Cognitive Style and

Cognitive Development. Norwood, NJ: Ablex.


Gorenstein, E.E. (1991). A cognitive perspective on antisocial

personality, in Magaro, P.A. (ed), Cognitive Bases of Mental

Disorders. Newbury Park, CA: Sage.


Gray, J.A. (1982). The Neuropsychology of Anxiety. New York:

Oxford University Press.



Greenberg, L.S., & Safran, J.D. (1990). Emotion in Psychotherapy.

New York: Guilford.



Greenspan, S.I. (1980). Intelligence and Adaptation: An Integration

of Psychoanalytic and Piagetian Developmental Psychology. New

York: International Universities Press.



Grossman, L.S., & Harrow, M. (1991). Thought disorder and cognitive

processes in mania, in Magaro, P.A. (ed), Cognitive Bases of Mental

Disorders. Newbury Park, CA: Sage.


Hebb, D.O. (1946). On the nature of fear. Psychol. Rev.,




Hebb, D.O. (1949). The Organization of Behavior. New York: Wiley.


Hestenes, D. (1991). A neural network theory of manic-depressive

illness, in Levine D.S., Leven, S.J. (eds), Motivation, Emotion,

and Goal Direction in Neural Networks. Hillside, NJ: Lawrence




Hilgard, E.R. (1977). Divided Consciousness: Multiple Controls in

Human Thought and Action. New York: Wiley.


Hoffman, R.E. (1987). Computer simulations of neural information

processing and the schizophrenia-mania dichotomy. Arch. Gen.

Psychiatry, 44:178-188.


Horowitz, M.J. (ed) (1988a). Psychodynamics and Cognition. Chicago:

University of Chicago Press.



Horowitz, M.J. (1988b). Introduction to psychodynamics: A new

synthesis. New York: Basic Books.


Horowitz, M.J. (1991). Person schemas and maladaptive interpersonal

behavior patterns. Chicago: Chicago University Press.


Hull, J.G, & Reilly, N.P. (1986). An information processing approach

to alcohol use and its consequences, in Ingram, R.E. (ed),

Information Processing Approaches to Clinical Psychology. San

Diego: Academic Press.



Ingram, R.E. (1984). Toward an information processing analysis of

depression. Cognitive Therapy and Research, 8:443-478.


Ingram, R.E. (ed) (1986). Information Processing Approaches to

Clinical Psychology. San Diego: Academic Press.


Ingram, R.E., & Reed, M.E. (1986). Information encoding and

retrieval processes in depression: Findings, issues, and future

directions, in Ingram, R.E. (ed), Information Processing Approaches

to Clinical Psychology. San Diego: Academic Press.


Ingram, R.E., & Wisnicki, K. (1991). Cognition in depression, in

Magaro, P.A. (1991). Cognitive Bases of Mental Disorders.

Newbury Park, CA: Sage.



Janet, P. (1907). The Major Symptoms of Hysteria. New York:




Jeffress, L.A. (ed) (1951). Cerebral Mechanisms in Behavior. The

Hixon Symposium. New York: Wiley.


Johnson-Laird, P.N. (1988). The Computer and the Mind: An

Introduction to Cognitive Science. Cambridge: Harvard University




Kihlstrom, J.F. (1987). The cognitive unconscious. Science,




Kihlstrom, J.F., & Hoyt, I.P. (1990). Repression, dissociation, and

hypnosis, in Singer, J.L. (ed), Repression and Dissociation:

Implications for Personality Theory, Psychopathology, and Health.

University of Chicago Press: Chicago.



Klein, G.S. (1976). Psychoanalytic Theory: An Exploration of

Essentials. New York: International Universities Press.


Koukkou, M. (1988). A psychophysiological information-processing

model of cognitive dysfunction and cognitive treatment in

depression, in Perris, C., Blackburn, I.M., & Perris, H. Cognitive

Psychotherapy: Theory and Practice. Berlin: Springer Verlag.


Kuiper, N.A., Derry, P.A., & MacDonald, M.R. (1982). Self-reference

and person perception depression, in Weary, G., Mirels, H. (eds),

Integrations of Clinical and Social Psychology. New York: Oxford




Lachman, R., Lachman, J.L., & Butterfield, E.C. (1979). Cognitive


Psychology and Information Processing: An Introduction.

Hillsdale, NJ: Erlbaum.



Lipowski, Z.J. (1989). Psychiatry: Mindless or brainless, both or

neither? Can. J. Psychiatry, 34:249-254.


Lakoff, G. (1987). Women, Fire, and Dangerous Things: What

Categories Reveal about the Mind. Chicago: University of Chicago




Litrownik, A.J., McInnis, E.T. (1986). Information processing and

autism, in Ingram, R.E. (ed), Information Processing Approaches to

Clinical Psychology. San Diego: Academic Press.


Lyddon, W.J. (1988). Information-processing and constructivist

models of cognitive therapy: A philosophical divergence. Journal

of Mind and Behavior, 9:137-166.


Magaro, P.A. (1980). Cognition in schizophrenia and paranoia: The

integration of cognitive processes. Hillsdale, NJ: Erlbaum.


Magaro, P.A. (ed) (1991). Cognitive Bases of Mental Disorders.

Newbury Park, CA: Sage.



Mahoney, M.J. (1991). Human Change Processes. New York: Basic




Mahoney, M.J., & Freeman, A. (eds) (1985). Cognition and

Psychotherapy. New York: Plenum.


Mandler, G. (1975). Mind and Emotion. New York: Wiley.


Markus, H. (1977). Self-schemata and processing information about the

self. J. Pers. Soc. Psychol., 35:63-78.


Meltzoff, A.N. (1990). Towards a developmental cognitive science:

The implications of cross-modal matching and imitation for the

development of representation and memory in infancy. Ann. N.Y.

Acad. Sci., 608:1-37.


Merluzzi, T.V., Rudy, T.E., & Glass, C.R. (1981). The information

processing paradigm: Implications for cognitive science, in

Merluzzi, T.V., Glass, C.R., & Genest, M. (eds), Cognitive

Assessment. New York: Guilford Press.


Morton, J. (1984). Brain-based and non-brain-based models of

language, in Caplan, D., Lecours, A.R., Smith, A. (eds), Biological

Perspectives on Language. Cambridge: MIT Press.


Neisser, U. (1976). Cognition and Reality. San Francisco: WH




Neuchterlein, K.H., & Dawson, M.E. (1984). Information processing

and functioning in the developmental course of schizophrenic

disorders. Schizophr. Bull., 10:160-203.


Oatley, K. (1991). Best Laid Plans. Cambridge: Cambridge University




Oatley, K., & Johnson-Laird, P.N. (1987). Towards a cognitive theory

of emotion. Cognition and Emotion, 1:29-50.


Peterfreund, E. (1971). Informations, Systems, and Psychoanalysis:

An Evolutionary Biological Approach to Psychoanalytic Theory. New

York: International Universities Press.



Piaget, J. (1952). The Origins of Intelligence in Children. New

York: International Universities Press.



Pitman, R. (1987). A cybernetic model of obsessive-compulsive

psychopathology. Compr. Psychiatry, 28:334-343.


Posner, M.I. (ed) (1989). The Foundations of Cognitive Science.

Cambridge: MIT Press.



Prigatano, G.P., & Schachter, D.L. (eds) (1991). Awareness of

Deficit after Brain Injury: Clinical and Theoretical Issues.

Oxford University Press: Oxford.



Rapee, R.M. (1991). Psychological factors in generalized anxiety, in

Rapee, R.M., Barlow, D.M. (eds), Chronic Anxiety: Generalized

Anxiety Disorder and Mixed Anxiety-Depression. New York:




Rapoport, J., & Wise, S. (1988). Obsessive-compulsive disorder: A

basal ganglia disease? in Rapoport, J. (ed), Obsessive-Compulsive

Disorder in Children and Adolescents. Washington, DC: APPI Press.


Ruesch, J., & Bateson, G. (1968). Communication: The Social Matrix

of Psychiatry. New York: Norton.


Rumelhart, D.E., Hinton, G.E., and the PDP Research Group (1986).

Parallel Distributed Processing: Explorations in the

Microstructure of Cognition. Cambridge: MIT Press.


Saccuzzo, D.P. (1986). An information processing interpretation of

theory and research in schizophrenia, in Ingram, R.E., Information

Processing Approaches to Clinical Psychology. San Diego: Academic




Safran, J.D., & Greenberg, L.S. (1986). Affect and the unconscious:

A cognitive perspective, in Stern, R. (ed), Theories of the

Unconscious and Theories of the Self. Hillsdale, NJ: Erlbaum.


Shannon, C.E. (1938). A symbolic analysis of relay and switching

circuits. Master's thesis, Massachusetts Institute of Technology.


Shimamura, A.P. (1989). Disorders of memory: the cognitive science

perspective, in Boller, F., & Grafman, J. (eds), Handbook of

Neuropsychology, 3. Amsterdam: Elsevier Science Publications.


Simon, H. (1967). Motivational and emotional controls of cognition.

Psychol. Rev., 74:29-39.


Singer, J.L. (ed) (1990). Repression and Dissociation: Implications

for Personality Theory, Psychopathology, and Health. University of

Chicago Press: Chicago.



Slap, J.W., & Saykin, A.J. (1983). The schema: Basic concept in a

nonmetapsychological model of the mind. Psychoanalysis and

Contemporary Thought, 6:305-325.


Sloman, A. (1987). Motives, mechanisms, and emotions. Cognition and

Emotion, 1:217-233.


Sorrentino, R.M., & Higgins, E.T. (eds) (1986). Handbook of

Motivation and Cognition: Foundations of Social Behavior. New

York: Guilford Press.



Stein, D.J. (1992a). Clinical cognitive science: Possibilities and

limitations. In Stein, D.J., & Young, J.E. (eds), Cognitive

Science and Clinical Disorders. San Diego: Academic Press, 1992.


Stein, D.J. (1992b). Psychoanalysis and cognitive science:

Contrasting models of the mind. J. Am. Acad. Psychoanal.,




Stein, D.J. (1992c). Medical anthropology and psychotherapy

integration: A cognitivist approach. Presented at the Annual

Meeting of the Society for the Exploration of Psychotherapy

Integration, San Diego.



Stein, D.J. (1992d). Cognitive science and clinical knowledge.

Integrative Psychiatry.


Stein, D.J. (1992e). Schemas in the cognitive and clinical sciences:

An integrative construct. Journal of Psychotherapy Integration




Stein, D.J., Hollander, E. (1992). Cognitive science and

obsessive-compulsive disorder, in Stein D.J., Young, J.E. (eds),

Cognitive Science and Clinical Disorders. San Diego: Academic




Stein, D.J., & Young, J.E. (eds) (1992a). Cognitive Science and

Clinical Disorders. San Diego: Academic Press.


Stein, D.J., & Young, J.E. (1992b). A schema-focused approach to

personality disorder, in Stein, D.J., & Young, J.E. (eds),

Cognitive Science and Clinical Disorders. San Diego: Academic




Stern, D. (1985). The Interpersonal World of the Infant. New York:

Basic Books.



Sternberg, R.J. (ed) (1984). Mechanisms of Cognitive Development.

New York: WH Freeman.



Stillings, N.A., Feinstein, M.H., Garfield, J.L., Rissland, E.L.,

Rosenbaum, D.A., Weisler, S.E., & Baker-Ward, L. (1987). Cognitive

Science: An Introduction. Cambridge: MIT Press.


Swerling, L.C., & Sternberg, R.J. (1992). Information processing,

experience, and reading disability, in Stein, D.J., & Young, J.E.

(eds), Cognitive Science and Clinical Disorders. DJ, Young JE.

San Diego: Academic Press.



Teasdale, J.D. (1983). Negative thinking in depression: Cause,

effect, or reciprocal relationship? Advances in Behavioural

Research and Therapy, 5:3-25.


Tomkins, S.S., & Messick, S. (eds) (1963). Computer Simulation of

Personality: Frontier of Psychological Theory. New York: Wiley.


Turing, A. (1936). On computable numbers, with an application to the

Entscheidungsproblem. Proceedings of the London Mathematical

Society, 2nd Series, 42:230-265.


Turing, A. (1950). Computing machinery and intelligence. Mind,




Uleman, J.S., & Bargh, J.A. (eds) (1989). Unintended Thought. New

York: Guilford Press.



Wachtel, P.L. (1982). Resistance: Psychodynamic and behavioral

approaches. New York: Plenum Press.


Weizenbaum, J. (1976). Computer Power and Human Reason. San

Francisco: WH Freeman.



Westen, D. (1988). Transference and information-processing. Clinical

Psychology Review, 8:161-179.


Wiener, N. (1947). Cybernetics. Cambridge: MIT Press.


Williams, J.M.G., Fraser, N.W., MacLeod, C., & Matthews, A. (1988).

An Information Processing Analysis of the Emotional Disorders. New

York: Wiley.



Williams, J.M.G, & Oaksford, M. (1992). Cognitive science, anxiety,

depression: From experiments to connectionism, in Stein, D.J., &

Young, J.E. (eds), Cognitive Science and Clinical Disorders.

San Diego: Academic Press.



Young, J.E. (1990). Cognitive therapy for personality disorders: A

schema-focused approach. Sarasota: Professional Resource