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  1. From symbols to icons: the return of resemblance in the cognitive neuroscience revolution.Daniel Williams & Lincoln Colling - 2018 - Synthese 195 (5):1941-1967.
    We argue that one important aspect of the “cognitive neuroscience revolution” identified by Boone and Piccinini :1509–1534. doi: 10.1007/s11229-015-0783-4, 2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both “from below” and “from above”—that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves, and from a greater appreciation of the problems (...)
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  • Explanation in dynamical cognitive science.Joel Walmsley - 2008 - Minds and Machines 18 (3):331-348.
    In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this (...)
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  • Structural Resemblance and the Causal Role of Content.Gregory Nirshberg - forthcoming - Erkenntnis:1-20.
    Some proponents of structural representations (henceforth, structuralists) claim that no other theory of representation can legitimatize the explanatory appeals that cognitive science makes to mental content. Because other naturalistic approaches to representation purportedly posit an arbitrary relation between representing vehicles and representational content, these approaches must appeal to the role played by a representation, i.e., how it is used by the system in which it is embedded, to ground its content. This is in supposed contrast to structural representations, in which (...)
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  • Representations in Dynamical Embodied Agents: Re-Analyzing a Minimally Cognitive Model Agent.Marco Mirolli - 2012 - Cognitive Science 36 (5):870-895.
    Understanding the role of ‘‘representations’’ in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as ‘‘standing in,’’ and I look for representations in embodied agents involved in simple categorization tasks. In a (...)
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  • Entrainment and motor emulation approaches to joint action: Alternatives or complementary approaches?Lincoln J. Colling & Kellie Williamson - 2014 - Frontiers in Human Neuroscience 8.
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  • After the Philosophy of Mind: Replacing Scholasticism with Science.Tony Chemero & Michael Silberstein - 2008 - Philosophy of Science 75 (1):1-27.
    We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...)
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  • Integrating Philosophy of Understanding with the Cognitive Sciences.Kareem Khalifa, Farhan Islam, J. P. Gamboa, Daniel Wilkenfeld & Daniel Kostić - 2022 - Frontiers in Systems Neuroscience 16.
    We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.
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