The Cognitive Revolution: a Historical Perspective
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Mentalism Versus Behaviourism in Economics: a Philosophy-Of-Science
Mentalism versus behaviourism in economics: aphilosophy-of-scienceperspective⇤ Franz Dietrich Christian List CNRS & University of East Anglia London School of Economics 18 November 2012 Abstract Behaviourism is the view that preferences, beliefs, and other mental states in social- scientific theories are nothing but constructs re-describing people’s behavioural dis- positions. Mentalism is the view that they capture real phenomena, no less existent than the unobservable entities and properties in the natural sciences, such as elec- trons and electromagnetic fields. While behaviourism has long gone out of fashion in psychology and linguistics, it remains influential in economics, especially in ‘re- vealed preference’ theory. We aim to (i) clear up some common confusions about the two views, (ii) situate the debate in a historical context, and (iii) defend a men- talist approach to economics. Setting aside normative concerns about behaviourism, we show that mentalism is in line with best scientific practice even if economics is treated as a purely positive science of economic behaviour. We distinguish men- talism from, and reject, the radical neuroeconomic view that behaviour should be explained in terms of people’s brain processes, as distinct from their mental states. 1 Introduction Economic theory seeks to explain the social and economic behaviour of human (and sometimes other) agents.1 It usually does so by (i) ascribing, at least in an ‘as if’ mode, ⇤This paper was presented at the LSE Choice Group workshop on ‘Rationalizability and Choice’, July 2011, the D-TEA workshop, Paris, July 2012, and the EIPE seminar, Rotterdam, September 2012. We are grateful to the participants and especially Nick Baigent, Walter Bossert, Richard Bradley, Mika¨el Cozic, Eddie Dekel, Ido Erev, Itzhak Gilboa, Conrad Heilmann, Johannes Himmelreich, Marco Mariotti, Friederike Mengel, Clemens Puppe, Larry Samuelson, David Schmeidler, Asli Selim, Daniel Stoljar, Kotaro Suzumura, and Peter Wakker for comments and discussion. -
Cognitive Science 1
Cognitive Science 1 • Linguistics, Minor (https://e-catalogue.jhu.edu/arts-sciences/full- COGNITIVE SCIENCE time-residential-programs/degree-programs/cognitive-science/ linguistics-minor/) http://www.cogsci.jhu.edu For current course information and registration go to https://sis.jhu.edu/ Cognitive science is the study of the human mind and brain, focusing on classes/ how the mind represents and manipulates knowledge and how mental representations and processes are realized in the brain. Conceiving of the mind as an abstract computing device instantiated in the brain, Courses cognitive scientists endeavor to understand the mental computations AS.050.102. Language and Mind. 3 Credits. underlying cognitive functioning and how these computations are Introductory course dealing with theory, methods, and current research implemented by neural tissue. Cognitive science has emerged at the topics in the study of language as a component of the mind. What it is interface of several disciplines. Central among these are cognitive to "know" a language: components of linguistic knowledge (phonetics, psychology, linguistics, and portions of computer science and artificial phonology, morphology, syntax, semantics) and the course of language intelligence; other important components derive from work in the acquisition. How linguistic knowledge is put to use: language and the neurosciences, philosophy, and anthropology. This diverse ancestry brain and linguistic processing in various domains. has brought into cognitive science several different perspectives and Area: Natural Sciences, Social and Behavioral Sciences methodologies. Cognitive scientists endeavor to unite such varieties AS.050.105. Introduction to Cognitive Neuropsychology. 3 Credits. of perspectives around the central goal of characterizing the structure When the brain is damaged or fails to develop normally, even the most of human intellectual functioning. -
Literature and the Cognitive Revolution: an Introduction
Literature and the Cognitive Revolution: An Introduction Alan Richardson English, Boston College Francis F. Steen Communication Studies, UCLA Literary studies and the cognitive sciences, pursuing common interests in language, mental acts, and linguistic artifacts, have developed markedly different approaches to similar phenomena of reading, imaginative involve- ment, and textual patterning. Until quite recently, the distance between them has drawn more attention than their possible convergence (Franchi and Güzeldere ). A number of literary theorists and critics, however, have steadily been producing work that finds its inspiration, its method- ology, and its guiding paradigms through a dialogue with one or more fields within cognitive science: artificial intelligence, cognitive psychology, post- Chomskian linguistics, philosophy of mind, neuroscience, and evolution- ary biology. Reuven Tsur () has been developing his ‘‘cognitive poet- ics’’ since the s; the prominent psychoanalytic critic Norman Holland (: ) demonstrated the advantages of attending to the ‘‘more powerful psychology’’ emerging from cognitive neuroscience in ; Mark Turner (: viii) advanced his far-reaching project of a ‘‘cognitive rhetoric’’ in ; and Ellen Spolsky (: ) trenchantly brought a theory of ‘‘cogni- tive instability’’ to bear on literary interpretation in . These and like- minded critics respond to the limitations (or, in Spolsky’s case, missed op- portunities) of poststructuralist conceptions of meaning and interpretation by questioning the reigning models in the field, whether in the interest of Poetics Today : (Spring ). Copyright © by the Porter Institute for Poetics and Semiotics. Downloaded from http://read.dukeupress.edu/poetics-today/article-pdf/23/1/1/458295/01.pdf by guest on 25 September 2021 2 Poetics Today 23:1 displacing, reworking, supplementing, or fundamentally regrounding them (Hart ). -
Toward a Mechanistic Psychology of Dialogue
Edinburgh Research Explorer Toward a mechanistic psychology of dialogue Citation for published version: Pickering, MJ & Garrod, S 2004, 'Toward a mechanistic psychology of dialogue', Behavioral and Brain Sciences, vol. 27, no. 02, pp. 169-225. https://doi.org/10.1017/S0140525X04000056 Digital Object Identifier (DOI): 10.1017/S0140525X04000056 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Behavioral and Brain Sciences Publisher Rights Statement: ©Pickering, M. J., & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27(02), 169-225doi: 10.1017/S0140525X04000056 General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 28. Sep. 2021 BEHAVIORAL AND BRAIN SCIENCES (2004) 27, 169–226 Printed in the United States of America Toward a mechanistic psychology of dialogue Martin J. Pickering Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom [email protected] http://www.psy.ed.ac.uk/Staff/academics.html#PickeringMartin Simon Garrod Department of Psychology, University of Glasgow, Glasgow G12 8QT, United Kingdom [email protected] http://staff.psy.gla.ac.uk/~simon/ Abstract: Traditional mechanistic accounts of language processing derive almost entirely from the study of monologue. -
Calculation of Signal Detection Theory Measures
Behavior Research Methods, Instruments, & Computers 1999, 31 (1), 137-149 Calculation of signal detection theory measures HAROLD STANISLAW California State University, Stanislaus, Turlock, California and NATASHA TODOROV Macquarie University, Sydney, New South Wales, Australia Signal detection theory (SDT) may be applied to any area of psychology in which two different types of stimuli must be discriminated. We describe several of these areas and the advantages that can be re- alized through the application of SDT. Three of the most popular tasks used to study discriminability are then discussed, together with the measures that SDT prescribes for quantifying performance in these tasks. Mathematical formulae for the measures are presented, as are methods for calculating the measures with lookup tables, computer software specifically developed for SDT applications, and gen- eral purpose computer software (including spreadsheets and statistical analysis software). Signal detection theory (SDT) is widely accepted by OVERVIEW OF SIGNAL psychologists; the Social Sciences Citation Index cites DETECTION THEORY over 2,000 references to an influential book by Green and Swets (1966) that describes SDT and its application to Proper application of SDT requires an understanding of psychology. Even so, fewer than half of the studies to which the theory and the measures it prescribes. We present an SDT is applicable actually make use of the theory (Stanislaw overview of SDT here; for more extensive discussions, see & Todorov, 1992). One possible reason for this apparent Green and Swets (1966) or Macmillan and Creelman underutilization of SDT is that relevant textbooks rarely (1991). Readers who are already familiar with SDT may describe the methods needed to implement the theory. -
Reliability in Cognitive Neuroscience: a Meta-Meta-Analysis Books Written by William R
Reliability in Cognitive Neuroscience: A Meta-Meta-Analysis Books Written by William R. Uttal Real Time Computers: Techniques and Applications in the Psychological Sciences Generative Computer Assisted Instruction (with Miriam Rogers, Ramelle Hieronymus, and Timothy Pasich) Sensory Coding: Selected Readings (Editor) The Psychobiology of Sensory Coding Cellular Neurophysiology and Integration: An Interpretive Introduction. An Autocorrelation Theory of Form Detection The Psychobiology of Mind A Taxonomy of Visual Processes Visual Form Detection in 3-Dimensional Space Foundations of Psychobiology (with Daniel N. Robinson) The Detection of Nonplanar Surfaces in Visual Space The Perception of Dotted Forms On Seeing Forms The Swimmer: An Integrated Computational Model of a Perceptual-Motor System (with Gary Bradshaw, Sriram Dayanand, Robb Lovell, Thomas Shepherd, Ramakrishna Kakarala, Kurt Skifsted, and Greg Tupper) Toward A New Behaviorism: The Case against Perceptual Reductionism Computational Modeling of Vision: The Role of Combination (with Ramakrishna Kakarala, Sriram Dayanand, Thomas Shepherd, Jaggi Kalki, Charles Lunskis Jr., and Ning Liu) The War between Mentalism and Behaviorism: On the Accessibility of Mental Processes The New Phrenology: On the Localization of Cognitive Processes in the Brain A Behaviorist Looks at Form Recognition Psychomyths: Sources of Artifacts and Misrepresentations in Scientifi c Cognitive neuroscience Dualism: The Original Sin of Cognitivism Neural Theories of Mind: Why the Mind-Brain Problem May Never Be Solved Human Factors in the Courtroom: Mythology versus Science The Immeasurable Mind: The Real Science of Psychology Time, Space, and Number in Physics and Psychology Distributed Neural Systems: Beyond the New Phrenology Neuroscience in the Courtroom: What Every Lawyer Should Know about the Mind and the Brain Mind and Brain: A Critical Appraisal of Cognitive Neuroscience Reliability in Cognitive Neuroscience: A Meta-Meta-Analysis Reliability in Cognitive Neuroscience: A Meta-Meta-Analysis William R. -
Anthropology's Disenchantment with the Cognitive Revolution
Topics in Cognitive Science 4 (2012) 354–361 Copyright Ó 2012 Cognitive Science Society, Inc. All rights reserved. ISSN: 1756-8757 print / 1756-8765 online DOI: 10.1111/j.1756-8765.2012.01199.x Anthropology’s Disenchantment With the Cognitive Revolution1 Richard A. Shweder Department of Comparative Human Development, University of Chicago Received 25 June 2011; received in revised form 3 November 2011; accepted 28 November 2011 Abstract Beller, Bender, and Medin should be congratulated for their generous attempt at expressive aca- demic therapy for troubled interdisciplinary relationships. In this essay, I suggest that a negative answer to the central question (‘‘Should anthropology be part of cognitive science?’’) is not necessar- ily distressing, that in retrospect the breakup seems fairly predictable, and that disenchantment with the cognitive revolution is nothing new. Keywords: Cognitive revolution; Behaviorism; Anthropology; Jerome Bruner; Roy D’Andrade; Clifford Geertz; Roger Shepard Some of the leaders of the cognitive revolution of the late 1950s and 1960s began parting from the cause almost as soon as it triumphed. Jerome Bruner, for example, who always enjoyed writing essays for both the left hand and the right hand, turned to hermeneutics, the study of law, and the interpretation of narratives (see Bruner, 1979, 1990). Even in the early days of the rebellion Bruner was attentive to language pragmatics, which may be one reason he named his 1960s big tent interdisciplinary center at Harvard University the ‘‘Center for Cognitive Studies’’ and not the ‘‘Center for Cognitive Science.’’ Bruner had just as much interest in the humanistic writings of E. H. Gombrich, Nelson Goodman, and Clifford Ge- ertz as in the latest claims about basic ⁄fundamental⁄universal cognitive processes coming out of experimental labs situated in Cambridge, London, or Geneva. -
John B. Watson's Legacy: Learning and Environment
Developmental Psychology Copyright 1992 by the American Psychological Association, Inc. 1992, Vol. 28, No. 3, 360-367 OOL2-1649/92/$3.0O John B. Watson's Legacy: Learning and Environment Frances Degen Horowitz Graduate School and University Center City University of New \brk John B. Watson's contribution is evaluated in relation to his own time, with respect to his historical influence, and in light of current issues in developmental psychology. A survey of a nonrandom sample of current developmental psychologists revealed no consensus with respect to Watson's legacy to developmental psychology. The influence of Watson's insistence on an objective methodol- ogy in psychology remains, although is not necessarily acknowledged. His extreme environmental- ism has been rejected. His concern to understand the principles of learning is reflected in the subsequent work of the Hullians and the Skinnerians. The influence of his underlying premise about the importance of environment and of learning is to be found in such work as studies of the effects of intervention programs. I question the possible costs to the field of the continued rejection of a Watsonian emphasis on learning as an important process in development and behavior. In his time, John Broadus Watson (1878-1958) was contro- felt he had ignored biological variables, but the remainder versial. So he remains. In preparation for this reflective essay tended to disagree with that characterization. on his legacy to developmental psychology, I sent a question- Diversity of opinion is rife in developmental psychology to- naire to a nonrandom sample of mostly senior developmental day, but when asked to evaluate the theoretical and methodolog- psychologists.1 The 45 respondents ranged widely in their per- ical contributions of Baldwin, Binet, Darwin, Freud, Gesell, ceptions of Watson's contributions and in their evaluations. -
The Place of Modeling in Cognitive Science
The place of modeling in cognitive science James L. McClelland Department of Psychology and Center for Mind, Brain, and Computation Stanford University James L. McClelland Department of Psychology Stanford University Stanford, CA 94305 650-736-4278 (v) / 650-725-5699 (f) [email protected] Running Head: Modeling in cognitive science Keywords: Modeling frameworks, computer simulation, connectionist models, Bayesian approaches, dynamical systems, symbolic models of cognition, hybrid models, cognitive architectures Abstract I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. As explorations, simplification is essential – it is only through simplification that we can fully understand the implications of the ideas. This is not to say that simplification has no downsides; it does, and these are discussed. I then consider several contemporary frameworks for cognitive modeling, stressing the idea that each framework is useful in its own particular ways. Increases in computer power (by a factor of about 4 million) since 1958 have enabled new modeling paradigms to emerge, but these also depend on new ways of thinking. Will new paradigms emerge again with the next 1,000-fold increase? 1. Introduction With the inauguration of a new journal for cognitive science, thirty years after the first meeting of the Cognitive Science Society, it seems essential to consider the role of computational modeling in our discipline. -
Author: Edwin Hutchins Title: Cognitive Ecology Affiliation: Department of Cognitive Science, University of California San Dieg
Author: Edwin Hutchins Title: Cognitive Ecology Affiliation: Department of Cognitive Science, University of California San Diego Tel: 858 534-1134 Fax: 858 822-2476 email: [email protected] Running Head: Cognitive Ecology Abstract: Cognitive ecology is the study of cognitive phenomena in context. In particular, it points to the web of mutual dependence among the elements of a cognitive ecosystem. At least three fields were taking a deeply ecological approach to cognition thirty years ago: Gibson’s ecological psychology, Bateson’s ecology of mind, and Soviet cultural-historical activity theory. The ideas developed in those projects have now found a place in modern views of embodied, situated, distributed cognition. As cognitive theory continues to shift from units of analysis defined by inherent properties of the elements to units defined in terms of dynamic patterns of correlation across elements, the study of cognitive ecosystems will become an increasingly important part of cognitive science. Keywords: units of analysis for cognition, ecological psychology, ecology of mind, activity theory, embodied cognition, situated cognition, distributed cognition, brain-body-world systems, human culture. Cognitive Ecology Choosing units of analysis for cognition Cognitive ecology is the study of cognitive phenomena in context. Elements of cognitive ecology have been present in various corners, but not the core, of cognitive science since the birth of the field. It is now being rediscovered as cognitive science shifts from viewing cognition as a logical process to seeing it as a biological phenomenon. Everything is connected to everything else. Fortunately, not all connectivity is equally dense. The non- uniformity of connectivity makes science possible. -
A Signal Detection Theory Analysis of Several Psychophysical Procedures Used in Lateralization Tasks
Loyola University Chicago Loyola eCommons Master's Theses Theses and Dissertations 1984 A Signal Detection Theory Analysis of Several Psychophysical Procedures Used in Lateralization Tasks Joseph N. Baumann Loyola University Chicago Follow this and additional works at: https://ecommons.luc.edu/luc_theses Part of the Psychology Commons Recommended Citation Baumann, Joseph N., "A Signal Detection Theory Analysis of Several Psychophysical Procedures Used in Lateralization Tasks" (1984). Master's Theses. 3330. https://ecommons.luc.edu/luc_theses/3330 This Thesis is brought to you for free and open access by the Theses and Dissertations at Loyola eCommons. It has been accepted for inclusion in Master's Theses by an authorized administrator of Loyola eCommons. For more information, please contact [email protected]. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. Copyright © 1984 Joseph N. Baumann A SIGNAL DETECTION THEORY ANALYSIS OF SEVERAL PSYCHOPHYSICAL PROCEDURES USED IN LATERALIZATION TASKS by Joseph N. Baumann A Thesis Submitted to the Faculty of the Department of Psychology of Loyola University of Chicago in Fulfillment of the Master's Thesis Requirement in Psychology December 1983 ACKNOWLEDGMENTS The following thesis is the product of much collaboration, and I would like to express my gratitude, and acknowledge those people who greatly contributed to its completion. First, I would like to thank my committee, Richard R. Fay, Ph.D., and Raymond H. Dye, Jr., Ph.D., for their continued help and suggestions, both in data collection and analysis. I have learned greatly from the experience. I would also like to thank William A. -
The Rising Field of Bioinformatics
Serena Hughes Case Study Spring 2019 The Rising Field of Bioinformatics Overview. Bioinformatics is an up-and-coming field within the intersection of biology and computer science. Biology and computer science were initially thought of separately, but with technological advances it soon became clear that there was an overlap where computer science algorithms could be used to further biological discoveries and biological systems could be used as a basis for computational models. The growth of research combining the two has led to the recent growth of the field of bioinformatics. Currently, bioinformatics is still relatively small, often housed as a specialization of biology, computer science, or other departments at universities. In 2009, only approximately 17% of bioinformatics programs were part of a bioinformatics department, with most programs being housed under biology or biomedical departments.[7] While it has been ten years since this data was collected, even in 2018 U.S. News’ ranking of bioinformatics programs included only 6 schools total.[11] Bioinformatics is a small and growing field, so the importance of the organization of bioinformatics is also growing. What is Being Organized? Bioinformatics has become increasingly interdisciplinary as it has grown, building on other scientific and mathematical fields. These subfields and the types of research they enable are the resources being organized. In organizing these resources, we will shed light on the structure of the field of bioinformatics as a whole. Why is it Being Organized? The term “bioinformatics” has been in use since the 1970s. Around that time, bioinformatics was “defined as the study of informatic processes in biotic systems”.