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Daniel C. Burnston [5]Daniel Burnston [4]
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Daniel Burnston
Tulane University
  1.  92
    Perceptual Learning, Categorical Perception, and Cognitive Permeation.Daniel Burnston - forthcoming - Dialectica.
    Proponents of cognitive penetration often argue for the thesis on the basis of combined intuitions about categorical perception and perceptual learning. The claim is that beliefs penetrate perceptions in the course of learning to perceive categories. I argue that this “diachronic” penetration thesis is false. In order to substantiate a robust notion of penetration, the beliefs that enable learning must describe the particular ability that subjects learn. However, they cannot do so, since in order to help with learning they must (...)
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  2. Why We May Not Find Intentions in the Brain.Sebo Uithol, Daniel C. Burnston & Pim Haselager - 2014 - Neuropsychologia 56 (5):129-139.
    Intentions are commonly conceived of as discrete mental states that are the direct cause of actions. In the last several decades, neuroscientists have taken up the project of finding the neural implementation of intentions, and a number of areas have been posited as implementing these states. We argue, however, that the processes underlying action initiation and control are considerably more dynamic and context sensitive than the concept of intention can allow for. Therefore, adopting the notion of ‘intention’ in neuroscientific explanations (...)
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  3.  67
    Getting Over Atomism: Functional Decomposition in Complex Neural Systems.Daniel C. Burnston - 2021 - British Journal for the Philosophy of Science 72 (3):743-772.
    Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of decomposition, (...)
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  4. Perceptual Integration, Modularity, and Cognitive Penetration.Daniel C. Burnston & Jonathan Cohen - 2015 - In A. Raftopoulos & J. Zeimbekis (eds.), Cognitive Influences on Perception: Implications for Philosophy of Mind, Epistemology, and Philosophy of Action. Oxford University Press.
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  5.  94
    Evolving Concepts of 'Hierarchy' in Systems Neuroscience.Philipp Haueis & Daniel Burnston - 2021 - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience.
    The notion of “hierarchy” is one of the most commonly posited organizational principles in systems neuroscience. To this date, however, it has received little philosophical analysis. This is unfortunate, because the general concept of hierarchy ranges over two approaches with distinct empirical commitments, and whose conceptual relations remain unclear. We call the first approach the “representational hierarchy” view, which posits that an anatomical hierarchy of feed-forward, feed-back, and lateral connections underlies a signal processing hierarchy of input-output relations. Because the representational (...)
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  6. Bayes, Predictive Processing, and the Cognitive Architecture of Motor Control.Daniel C. Burnston - 2021 - Consciousness and Cognition 96:103218.
    Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels (...)
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  7.  67
    Cognitive Ontologies, Task Ontologies, and Explanation in Cognitive Neuroscience.Daniel Burnston - forthcoming - In John Bickle, Carl F. Craver & Ann Sophie Barwich (eds.), Neuroscience Experiment: Philosophical and Scientific Perspectives.
    The traditional approach to explanation in cognitive neuroscience is realist about psychological constructs, and treats them as explanatory. On the “standard framework,” cognitive neuroscientists explain behavior as the result of the instantiation of psychological functions in brain activity. This strategy is questioned by results suggesting the distribution of function in the brain, the multifunctionality of individual parts of the brain, and the overlap in neural realization of purportedly distinct psychological constructs. One response to this in the field has been to (...)
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  8.  71
    Pluralistic Attitude-Explanation and the Mechanisms of Intentional Action.Daniel Burnston - 2021 - In David Shoemaker (ed.), Oxford Studies in Agency and Responsibility, Vol 7. Oxford, UK: pp. 130-153.
    According to the Causal Theory of Action (CTA), genuine actions are individuated by their causal history. Actions are bodily movements that are causally explained by citing the agent’s reasons. Reasons are then explained as some combination of propositional attitudes – beliefs, desires, and/or intentions. The CTA is thus committed to realism about the attitudes. This paper explores current models of decision-making from the mind sciences, and argues that it is far from obvious how to locate the propositional attitudes in the (...)
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  9. Contents, Vehicles, and Complex Data Analysis in Neuroscience.Daniel C. Burnston - 2020 - Synthese 199 (1-2):1617-1639.
    The notion of representation in neuroscience has largely been predicated on localizing the components of computational processes that explain cognitive function. On this view, which I call “algorithmic homuncularism,” individual, spatially and temporally distinct parts of the brain serve as vehicles for distinct contents, and the causal relationships between them implement the transformations specified by an algorithm. This view has a widespread influence in philosophy and cognitive neuroscience, and has recently been ably articulated and defended by Shea. Still, I am (...)
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