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Chapter 1 - The Prehistory of Cognitive Science
- from Part I - Historical Landmarks
- José Luis Bermúdez, Texas A & M University
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- Cognitive Science
- Published online:
- 10 November 2022
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- 10 November 2022, pp 11-28
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This chapter looks back to the pioneering studies that prefigured the emergence of cognitive science, subsequently converging into this new interdisciplinary field in the late 1970s. The first section addresses a key turning point in psychology. Whereas behaviorism holds that all explicit behaviors are the product of conditioning, it became clear that animals can manipulate representations of the environment to solve complex problems without reinforcement. The second section introduces the Turing machine developed by Turing in the 1930s, illustrating that purely mechanical procedures can process information algorithmically. The idea of a computable machine contributed to the birth of computer science and provided a model for thinking about how the mind processes information. Chomsky's transformational grammar offers a classic example of a computable model of how complex sentences convey information as a function of basic syntax rules. Finally, Miller and Broadbent's findings on attention support applying the information-processing model in psychology. These pioneering researchers were the first to lay out some of what were to be the basic concepts of cognitive science.
Atomic Event Concepts in Perception, Action, and Belief
- LUCAS THORPE
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- Journal:
- Journal of the American Philosophical Association / Volume 8 / Issue 1 / Spring 2022
- Published online by Cambridge University Press:
- 22 October 2021, pp. 110-127
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Event concepts are unstructured atomic concepts that apply to event types. A paradigm example of such an event type would be that of diaper changing, and so a putative example of an atomic event concept would be DADDY'S-CHANGING-MY-DIAPER.1 I will defend two claims about such concepts. First, the conceptual claim that it is in principle possible to possess a concept such as DADDY'S-CHANGING-MY-DIAPER without possessing the concept DIAPER. Second, the empirical claim that we actually possess such concepts and that they play an important role in our cognitive lives. The argument for the empirical claim has the form of an inference to the best explanation and is aimed at those who are already willing to attribute concepts and beliefs to infants and nonhuman animals. Many animals and prelinguistic infants seem capable of re-identifying event-types in the world, and they seem to store information about things happening at particular times and places. My account offers a plausible model of how such organisms are able to do this without attributing linguistically structured mental states to them. And although language allows adults to form linguistically structured mental representations of the world, there is no good reason to think that such structured representations necessarily replace the unstructured ones. There is also no good reason for a philosopher who is willing to explain the behavior of an organism by appealing to atomic concepts of individuals or kinds to not use a similar form of explanation when explaining the organism's capacity to recognize events.
We can form empirical concepts of individuals, kinds, properties, event-types, and states of affairs, among other things, and I assume that such concepts function like what François Recanati calls ‘mental files’ or what Ruth Millikan calls ‘substance concepts’ (Recanati 2012; Millikan 1999, 2000, 2017). To possess such a concept one must have a reliable capacity to re-identify the object in question, but this capacity of re-identification does not fix the reference of the concept. Such concepts allow us to collect and utilize useful information about things that we re-encounter in our environment. We can distinguish between a perception-action system and a perception-belief system, and I will argue that empirical concepts, including atomic event concepts, can play a role in both systems. The perception-action system involves the application of concepts in the service of (often skilled) action. We can think of the concept as a mental file containing motor-plans that can be activated once the individual recognizes that they are in a certain situation. In this way, recognizing something (whether an object or an event) as a token of a type, plays a role in guiding immediate action. The perception-belief system, in contrast, allows for the formation of beliefs that can play a role in deliberation and planning and in the formation of expectations. I distinguish between two particular types of belief which I call where-beliefs and when-beliefs, and I argue that we can model the formation of such perceptual beliefs in nonlinguistic animals and human infants in terms of the formation of a link between an empirical concept and a position on a cognitive map. According to the account offered, seemingly complex beliefs, such as a baby's belief that Daddy changed her diaper in the kitchen earlier, will not be linguistically structured. If we think that prelinguistic infants possess such concepts and are able to form such beliefs, it is likely that adults do too. The ability to form such beliefs does not require the capacity for public language, and we can model them in nonlinguistic terms; thus, we have no good reason to think of such beliefs as propositional attitudes. Of course, we can use sentences to refer to such beliefs, and thus it is possible to think of such beliefs as somehow relations to propositions. But it is not clear to me what is gained by this as we have a perfectly good way to think about the structure of such beliefs that does not involve any appeal to language.
Précis of Neural organization: Structure, function, and dynamics
- Michael A. Arbib, Péter Érdi
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- Journal:
- Behavioral and Brain Sciences / Volume 23 / Issue 4 / August 2000
- Published online by Cambridge University Press:
- 30 August 2019, pp. 513-533
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Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) Function: Control of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai.
The meaning of representation in animal memory
- H. L. Roitblat
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- Journal:
- Behavioral and Brain Sciences / Volume 5 / Issue 3 / September 1982
- Published online by Cambridge University Press:
- 04 February 2010, pp. 353-372
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A representation is a remnant of previous experience that allows that experience to affect later behavior. This paper develops a metatheoretical view of representation and applies it to issues concerning representation in animals. To describe a representational system one must specify the following: the domain or range of situations in the represented world to which the system applies; the content or set of features encoded and preserved by the system; the code or transformational rules relating features of the representation to the corresponding features of the represented world; the medium, or the representation's physical instantiation; and the dynamics, or how the system changes with time. In part because of the behaviorist assumption that the hypothetical, covert changes occurring in an organism during learning correspond to the overt physical changes that are observed, issues of representation in animal behavior have been largely ignored as irrelevant or misleading. However, it can be inferred that representations, acting as models of environmental regularities, operate at many levels of behavioral functioning, both cognitive and noncognitive. Objections to the use of this concept in explanations of animal behavior, based on the claim that it is indeterminate and on behaviorist considerations of parsimony, can be answered. Animal representations may be specialized in terms of tasks and species. Data from tasks involving spatial memory, delayed matching-to-sample, and sequence learning suggest some foundations for a general theory of animal representations.
3 - Chrysippus' dog as a case study in non-linguistic cognition
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- By Michael Rescorla, University of California, Santa Barbara
- Edited by Robert W. Lurz, Brooklyn College, City University of New York
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- Book:
- The Philosophy of Animal Minds
- Published online:
- 05 June 2012
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- 03 September 2009, pp 52-71
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To illustrate the explanatory potential of cognitive maps, this chapter deploys them against a venerable philosophical argument for languageless thought and reasoning. The explanation shows that we can accommodate Chrysippus' dog without assimilating animal minds to human minds. The chapter illustrates the explanatory resources of an intermediate position that countenances non-linguistic cognition while sharply distinguishing it from linguistic cognition. It focuses on two crucial features of human propositional attitudes: they have logical form, and they participate in deductive reasoning sensitive to that form. Discussions of Chrysippus' dog typically choose among four strategies: (1) Treat the dog as executing a deductive inference; (2) Attribute logical reasoning to the dog, but construe the attribution instrumentally; (3) Do not attribute logical reasoning to the dog; and (4) Grant that the dog records no additional relevant observations beyond those mentioned by Chrysippus. The chapter presents a Bayesian-cum-cartographic model of Chrysippus' dog.