Psychology as a Historical Science.

Notes on Contributors

Cognitive Mapping and the Origin of Language and Mind

Previous articleNext article No AccessNew Biological BooksOrigins of the Modern Mind. Three Stages in the Evolution of Culture and Cognition. Merlin Donald Harry J. JerisonHarry J. Jerison Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Quarterly Review of Biology Volume 67, Number 4Dec., 1992 Published in association with Stony Brook University Article DOIhttps://doi.org/10.1086/417877 Views: 3Total views on this site Citations: 34Citations are reported from Crossref Copyright 1992 The University of ChicagoPDF download Crossref reports the following articles citing this article:Merlin Donald Précis of Origins of the modern mind: Three stages in the evolution of culture and cognition, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 737–748.https://doi.org/10.1017/S0140525X00032647Michael A. Arbib From cooperative computation to man/machine symbiosis, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 748–749.https://doi.org/10.1017/S0140525X00032659Derek Bickerton Putting cognitive carts before linguistic horses, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 749–750.https://doi.org/10.1017/S0140525X00032660C. Loring Brace “Pop science” versus understanding the emergence of the modern mind, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 750–751.https://doi.org/10.1017/S0140525X00032672Bruce Bridgeman, Margarita Azmitia Mimetic culture and modern sports: A synthesis, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 751–752.https://doi.org/10.1017/S0140525X00032684Philip G. Chase Archaeology and the cognitive sciences in the study of human evolution, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 752–753.https://doi.org/10.1017/S0140525X00032696Andy Clark Symbolic invention: The missing (computational) link?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 753–754.https://doi.org/10.1017/S0140525X00032702Thomas L. Clarke A natural history of the mind: A guide for cognitive science, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 754–755.https://doi.org/10.1017/S0140525X00032714Alan Costall The place of cognition in human evolution, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 755–755.https://doi.org/10.1017/S0140525X00032726Vilmos Csányi Human evolution: Emergence of the group-self, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 755–756.https://doi.org/10.1017/S0140525X00032738Jeffrey Cynx, Stephen J. Clark Ethological foxes and cognitive hedgehogs, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 756–757.https://doi.org/10.1017/S0140525X0003274XJ. B. Deregowski What about pictures?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 757–758.https://doi.org/10.1017/S0140525X00032751R. I. M. Dunbar The modern mind: Its missing parts?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 758–759.https://doi.org/10.1017/S0140525X00032763Jerome A. Feldman From mimesis to synthesis, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 759–759.https://doi.org/10.1017/S0140525X00032775James H. Fetzer Evolution needs a modern theory of the mind, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 759–760.https://doi.org/10.1017/S0140525X00032787Liane M. Gabora Cultural transitions occur when mind parasites learn new tricks, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 760–761.https://doi.org/10.1017/S0140525X00032799K. J. Gilhooly Working memory and its extensions, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 761–762.https://doi.org/10.1017/S0140525X00032805John Halverson Mythos and logos, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 762–762.https://doi.org/10.1017/S0140525X00032817P. J. Hampson From mimetic to mythic culture: Stimulus equivalence effects and prelinguistic cognition, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 763–763.https://doi.org/10.1017/S0140525X00032829Harry J. Jerison The evolved mind, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 763–764.https://doi.org/10.1017/S0140525X00032830Leonard D. Katz The gradual evolution of enhanced control by plans: A view from below, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 764–765.https://doi.org/10.1017/S0140525X00032842Aarre Laakso Language equals mimesis plus speech, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 765–766.https://doi.org/10.1017/S0140525X00032854Rudi Lutz Lessons from evolution for artificial intelligence?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 766–766.https://doi.org/10.1017/S0140525X00032866Alexander Marshack Correct data base: Wrong model?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 767–768.https://doi.org/10.1017/S0140525X00032878Robert W. Mitchell, H. Lyn Miles Apes have mimetic culture, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 768–768.https://doi.org/10.1017/S0140525X0003288XH. C. Plotkin Hunting memes, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 768–769.https://doi.org/10.1017/S0140525X00032891Jocelyn Penny Small Memory, text and the Greek Revolution, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 769–770.https://doi.org/10.1017/S0140525X00032908Evan Thompson Language, thought and consciousness in the modern mind, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 770–771.https://doi.org/10.1017/S0140525X0003291XMichael Tomasello It's imitation, not mimesis, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 771–772.https://doi.org/10.1017/S0140525X00032921Jacques Vauclair, Joël Fagot Can a Saussurian ape be endowed with episodic memory only?, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 772–773.https://doi.org/10.1017/S0140525X00032933Christopher Wills Stages versus continuity, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 773–773.https://doi.org/10.1017/S0140525X00032945Thomas Wynn Archaeological evidence for mimetic mind and culture, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 774–774.https://doi.org/10.1017/S0140525X00032957Jiajie Zhang External representation: An issue for cognition, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 774–775.https://doi.org/10.1017/S0140525X00032969Merlin Donald On the evolution of representational capacities, Behavioral and Brain Sciences 16, no.44 (Feb 2010): 775–791.https://doi.org/10.1017/S0140525X00032970

The history of psychology in Japan

Theopsych: A Psychological Science Primer for Theologians

Learning motivated by electrical stimulation of the brain.

This article introduces a vocabulary suitable for evolutionary analyses in the human cognitive, social, and behavioral sciences. The vocabulary carves a middle way between advocates and critics of evolutionary perspectives by substituting the concept of repeated assembly for nature-nurture dualism. A model of core configurations-based on human morphology and ecology in human evolutionary history-is presented, and I argue that these configurations of face-to-face groups are the selective context for uniquely human mental systems. Hence, human cognition is "truly social,"" specialized for group living. The relevance of the core configuration model is illustrated with respect to two areas of interest to social psychologists: the self and social identity, and distributed cognition and shared reality. A final section illustrates the integrative power of the core configuration model with a brief comparison of the social and cognitive tasks faced by scientists and foragers.

The interaction of robotics with behavioral and cognitive sciences has always been tight. As often described in the literature, the living has inspired the construction of many robots. Yet, in this article, we focus on the reverse phenomenon: building robots can impact importantly the way we conceptualize behavior and cognition in animals and humans. This article presents a series of paradigmatic examples spanning from the modelling of insect navigation, the experimentation of the role of morphology to control locomotion, the development of foundational representations of the body and of the self/other distinction, the self-organization of language in robot societies, and the use of robots as therapeutic tools for children with developmental disorders. Through these examples, I review the way robots can be used as operational models confronting specific theories to reality, or can be used as proof of concepts, or as conceptual exploration tools generating new hypotheses, or used as experimental set ups to uncover particular behavioral properties in animals or humans, or even used as therapeutic tools. Finally, I discuss the fact that in spite of its role in the formation of many fundamental theories in behavioral and cognitive sciences, the use of robots is far from being accepted as a standard tool and contributions are often forgotten, leading to regular rediscoveries and slowing down cumulative progress. The article concludes by highlighting the high priority of further historical and epistemological work.

This presentation will provide a brief overview of existing and emerging funding opportunities at the National Science Foundation (NSF). The Division of Behavioral and Cognitive Sciences (BCS) at the NSF supports research to develop and advance scientific knowledge focusing on human cognition, language, social behavior and culture, as well as research on the interactions between human societies and the physical environment. BCS programs consider proposals that fall squarely within disciplines, but they also encourage and support interdisciplinary projects, which are evaluated through joint review among Programs in BCS, as well as a joint review with programs in other Divisions, and NSF-wide multi-disciplinary panels, as appropriate. All programs in BCS consider proposals for research projects, conferences, and workshops. Some programs also consider proposals for doctoral dissertation improvement assistance, the acquisition of specialized research and computing equipment, group international travel, and large-scale data collection. BCS participates in special initiatives and competitions on a number of topics, including cognitive neuroscience, children’s research, human origins, and the development of infrastructure to improve data resources, data archives, collaboratories, and centers.

Cognitive science is a network of interrelated scientific disciplines engaged in researching human cognition and its brain mechanisms. The birth of cognitive science has been the result of numerous integrated processes. Cognitive science is made up of experimental psychology cognition, philosophy consciousness, neuroscience, cognitive anthropology, linguistics, computer science and artificial intelligence. In recent years, a number of other research areas have been added to the body of cognitive science. Among researchers there have been discussions about whether cognitive science is a separate research area or it consists of a series of specialized areas. In fact, the point at issue is whether cognitive science is still a multidisciplinary project or already an interdisciplinary one. P. Thagard believes that cognitive science has reached the level of interdisciplinarity and explains the advances in this area through the metaphor of “trading zones”. The success elements of cognitive science are: fruitful unification of scientific interests of cognitive science founders; organizational structure of the scientific community – universities, where a special interdisciplinary intellectual environment has been created; a large number of joint research projects supported by governments and business; integrated use of scientific methods and fundamental ideas. D. Sperber and J. Miller prefer to talk not about a unified cognitive science but cognitive sciences, i.e., the commonwealth of sciences working together on the study of a single object - human cognition, however, the extent of their interactive communication is still small. Thus, we should speak about multidisciplinarity rather than genuine interdisciplinarity of the joint research of separate sciences.

Araujo begins by criticising what he calls the “social turn” in the history of psychology. He singles out the work of Kurt Danziger for special criticism in this regard. He then outlines the emergence of an allegedly new field called “History and Philosophy of Science” (HPS) and calls for a different approach which he labels a “philosophical” history of psychology. Here I examine his criticism of Danziger’s work and suggest that it is unjustified. I also point out that there is nothing new about the field of HPS and nothing original about the idea of relating history and philosophy of psychology. I conclude by suggesting that, although Araujo’s criticism is unjustified, it can give some insight into where his alternative path for the future will lead. It is an attempt to excise the sociology of knowledge from historical discourse and to return to a more traditional history of ideas.

This chapter is organized in two main sub-chapters: Cognitive Science Approach and Management Measurement Approaches. Its objectives are to give the reader an overview of the different disciplines that constitute cognitive science and to discuss the state-of-the art of the current measurement approaches in the knowledge management literature. The study of cognitive science is interdisciplinary, and it covers the fields of philosophy, psychology, neurosciences, computational intelligence, linguistics and language, and finally culture, cognition and evolution, all of which will be discussed. For cognitive scientists the objects under study are behavior and cognition in humans, animals and machines. The examination of cognitive science can be seen as a basic explanation of how humans are perceiving, learning, thinking, speaking, and acting. Its main focus lies in the discussion of how individuals reason under conditions of uncertainty and how perceived information is processed in the brain to build knowledge. A detailed explanation of all views, concepts, methods and methodologies in cognitive science is beyond this research.KeywordsCash FlowBayesian NetworkMental ModelStructural CapitalIntellectual CapitalThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Cognitive and educational sciences share a fundamental interest in learning. While theoretical bases and practical interests seem to match well at first sight, it is well worth to take a closer look. In the different disciplines involved in the Cognitive Sciences there is a large number of approaches to study learning, but closer glance reveals a limited number of ways to conceptualize learning. In its short history, the field has seen some paradigm shifts, which changed the way we look at human cognition and thus at learning. It is worth noting that each paradigm also transports an implicit notion of knowledge. In the field of education we find these paradigms as different learning theories, which in turn determine approaches to teaching and learning. Dealing with knowledge is central to educational practice. Furthermore, educational research indicates that our personal concept of knowledge qualitatively influences the way students learn. Thus there is a deep, but the intricate relationship between our concepts learning and knowledge. If the interaction between the two fields is to go beyond the (often unsatisfying) attempt to find direct-to-classroom recipes, explicit concepts of learning and knowledge must be the starting point for any successful interdisciplinary collaboration. Key words: cognitive sciences, education, knowledge, learning.

The term `complexity' is often found in the behavioural and cognitive sciences. This paper compares the common-sense usage of the world with attempts by information theorists to provide a formal definition. The concepts of randomness, predictability, organization and complexity are reviewed and we advocate that a distinction be made between traditional `algorithmic' and a more biologically relevant `organizational' complexity. We develop the formal properties of the latter with reference to hierarchies of explanation. The utility of both measures of complexity is discussed and examples of practical application given. We discuss relationships between complexity of environment, cognition, behaviour and brain, outline a possible metacognitive function for perception of complexity, and consider the implications for evolutionary psychology of the special nature of social complexity.

Despite their distinct objects of study, the human behavioral sciences all include models of individual human behavior. Unity in the behavioral sciences requires that there be a common underlying model of individual human behavior, specialized and enriched to meet the particular needs of each discipline. Such unity does not exist, and cannot be easily attained, since the various disciplines have incompatible models and disparate research methodologies. Yet recent theoretical and empirical developments have created the conditions for unity in the behavioral sciences, incorporating core principles from all fields, and based upon theoretical tools (game theory and the rational actor model) and data gathering techniques (experimental games in the laboratory and field) that transcend disciplinary boundaries. This article sketches a set of principles aimed at fostering such a unity.