9 found
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  1. The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective.David Michael Kaplan & Carl F. Craver - 2011 - Philosophy of Science 78 (4):601-627.
    We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...)
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  2. Explanation and description in computational neuroscience.David Michael Kaplan - 2011 - Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...)
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  3. How to demarcate the boundaries of cognition.David Michael Kaplan - 2012 - Biology and Philosophy 27 (4):545-570.
    Advocates of extended cognition argue that the boundaries of cognition span brain, body, and environment. Critics maintain that cognitive processes are confined to a boundary centered on the individual. All participants to this debate require a criterion for distinguishing what is internal to cognition from what is external. Yet none of the available proposals are completely successful. I offer a new account, the mutual manipulability account, according to which cognitive boundaries are determined by relationships of mutual manipulability between the properties (...)
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  4. Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience.J. Brendan Ritchie, David Michael Kaplan & Colin Klein - 2019 - British Journal for the Philosophy of Science 70 (2):581-607.
    Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...)
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  5. Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience.J. Brendan Ritchie, David Michael Kaplan & Colin Klein - 2016 - British Journal for the Philosophy of Science:axx023.
    Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...)
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  6. Moving parts: the natural alliance between dynamical and mechanistic modeling approaches.David Michael Kaplan - 2015 - Biology and Philosophy 30 (6):757-786.
    Recently, it has been provocatively claimed that dynamical modeling approaches signal the emergence of a new explanatory framework distinct from that of mechanistic explanation. This paper rejects this proposal and argues that dynamical explanations are fully compatible with, even naturally construed as, instances of mechanistic explanations. Specifically, it is argued that the mathematical framework of dynamics provides a powerful descriptive scheme for revealing temporal features of activities in mechanisms and plays an explanatory role to the extent it is deployed for (...)
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  7.  45
    Explanation and Integration in Mind and Brain Science.David Michael Kaplan (ed.) - 2017 - Oxford, United Kingdom: Oxford University Press.
    Is the relationship between psychology and neuroscience one of autonomy or mutual constraint and integration? This volume includes new papers from leading philosophers seeking to address this issue by deepening our understanding of the similarities and differences between the explanatory patterns employed across these domains.
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  8. How to reconcile physicalism and antireductionism about biology.Alex Rosenberg & David Michael Kaplan - 2005 - Philosophy of Science 72 (1):43-68.
    Physicalism and antireductionism are the ruling orthodoxy in the philosophy of biology. But these two theses are difficult to reconcile. Merely embracing an epistemic antireductionism will not suffice, as both reductionists and antireductionists accept that given our cognitive interests and limitations, non-molecular explanations may not be improved, corrected or grounded in molecular ones. Moreover, antireductionists themselves view their claim as a metaphysical or ontological one about the existence of facts molecular biology cannot identify, express, or explain. However, this is tantamount (...)
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  9.  68
    Perception and Cognition: Essays in the Philosophy of Psychology.David Michael Kaplan - 2012 - Philosophical Psychology 25 (3):463-468.
    Philosophical Psychology, Volume 0, Issue 0, Page 1-6, Ahead of Print.
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