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  1. Epistemic Irrationality in the Bayesian Brain.Daniel Williams - forthcoming - British Journal for the Philosophy of Science:000-000.
    A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to model information processing within the brain. Many theorists have noted that this research seems to be in tension with a large body of experimental results purportedly documenting systematic deviations from Bayesian updating in human belief formation. In response, proponents of the Bayesian brain hypothesis contend that Bayesian models can accommodate such results by making suitable assumptions about model parameters. To make progress in this debate, I (...)
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  • Delusional Predictions and Explanations.Matthew Parrott - forthcoming - British Journal for the Philosophy of Science:axz003.
    In both cognitive science and philosophy, many theorists have recently appealed to a predictive processing framework to offer explanations of why certain individuals form delusional beliefs. One aim of this essay will be to illustrate how one could plausibly develop a predictive processing account in different ways to account for the onset of different kinds of delusions. However, the second aim of this essay will be to discuss two significant limitations of the predictive processing framework. First, I shall draw on (...)
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  • Being Realist About Bayes, and the Predictive Processing Theory of Mind.Matteo Colombo, Lee Elkin & Stephan Hartmann - forthcoming - British Journal for the Philosophy of Science:000-000.
    Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...)
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  • Bayesian Cognitive Science, Monopoly, and Neglected Frameworks.Matteo Colombo & Stephan Hartmann - 2015 - British Journal for the Philosophy of Science 68 (2):451–484.
    A widely shared view in the cognitive sciences is that discovering and assessing explanations of cognitive phenomena whose production involves uncertainty should be done in a Bayesian framework. One assumption supporting this modelling choice is that Bayes provides the best approach for representing uncertainty. However, it is unclear that Bayes possesses special epistemic virtues over alternative modelling frameworks, since a systematic comparison has yet to be attempted. Currently, it is then premature to assert that cognitive phenomena involving uncertainty are best (...)
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  • Bayesian Cognitive Science, Unification, and Explanation.Stephan Hartmann & Matteo Colombo - 2017 - British Journal for the Philosophy of Science 68 (2).
    It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be (...)
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  • Two Kinds of Information Processing in Cognition.Mark Sprevak - 2020 - Review of Philosophy and Psychology 11 (3):591-611.
    What is the relationship between information and representation? Dating back at least to Dretske, an influential answer has been that information is a rung on a ladder that gets one to representation. Representation is information, or representation is information plus some other ingredient. In this paper, I argue that this approach oversimplifies the relationship between information and representation. If one takes current probabilistic models of cognition seriously, information is connected to representation in a new way. It enters as a property (...)
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  • Meeting in the Dark Room: Bayesian Rational Analysis and Hierarchical Predictive Coding,.Sascha Benjamin Fink & Carlos Zednik - 2017 - Philosophy and Predictive Processing.
    At least two distinct modeling frameworks contribute to the view that mind and brain are Bayesian: Bayesian Rational Analysis (BRA) and Hierarchical Predictive Coding (HPC). What is the relative contribution of each, and how exactly do they relate? In order to answer this question, we compare the way in which these two modeling frameworks address different levels of analysis within Marr’s tripartite conception of explanation in cognitive science. Whereas BRA answers questions at the computational level only, many HPC-theorists answer questions (...)
     
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  • Shannon + Friston = Content: Intentionality in Predictive Signaling Systems.Carrie Figdor - forthcoming - Synthese:1-24.
    What is the content of a mental state? This question poses the problem of intentionality: to explain how mental states can be about other things, where being about them is understood as representing them. A framework that integrates predictive coding and signaling systems theories of cognitive processing offers a new perspective on intentionality. On this view, at least some mental states are evaluations, which differ in function, operation, and normativity from representations. A complete naturalistic theory of intentionality must account for (...)
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  • A Predictive Coding Perspective on Autism Spectrum Disorders.Jeroen J. A. van Boxtel & Hongjing Lu - 2013 - Frontiers in Psychology 4.
  • Direct Perception and the Predictive Mind.Zoe Drayson - 2018 - Philosophical Studies 175 (12):3145-3164.
    Predictive approaches to the mind claim that perception, cognition, and action can be understood in terms of a single framework: a hierarchy of Bayesian models employing the computational strategy of predictive coding. Proponents of this view disagree, however, over the extent to which perception is direct on the predictive approach. I argue that we can resolve these disagreements by identifying three distinct notions of perceptual directness: psychological, metaphysical, and epistemological. I propose that perception is plausibly construed as psychologically indirect on (...)
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  • Rational Relations Between Perception and Belief: The Case of Color.Peter Brössel - 2017 - Review of Philosophy and Psychology 8 (4):721-741.
    The present paper investigates the first step of rational belief acquisition. It, thus, focuses on justificatory relations between perceptual experiences and perceptual beliefs, and between their contents, respectively. In particular, the paper aims at outlining how it is possible to reason from the content of perceptual experiences to the content of perceptual beliefs. The paper thereby approaches this aim by combining a formal epistemology perspective with an eye towards recent advances in philosophy of cognition. Furthermore the paper restricts its focus, (...)
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  • Predictive Processing and the Representation Wars.Daniel Williams - 2018 - Minds and Machines 28 (1):141-172.
    Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the “representation wars” of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing’s account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based (...)
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  • Bayesian Cognitive Science, Predictive Brains, and the Nativism Debate.Matteo Colombo - 2018 - Synthese 195 (11):4817-4838.
    The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empiricists into more productive forms—or so have claimed several philosophers and cognitive scientists. The present paper explicates this claim, distinguishing different ways of understanding it. After clarifying what is at stake in the controversy between nativists and empiricists, and what is involved in current Bayesian cognitive science, the paper argues that Bayesianism offers not a vindication of either nativism or empiricism, but one way to talk (...)
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  • A Deflationary Account of Mental Representation.Frances Egan - forthcoming - In Joulia Smortchkova, Krzysztof Dolega & Tobias Schlicht (eds.), Mental Representations. New York, USA: Oxford University Press.
    Among the cognitive capacities of evolved creatures is the capacity to represent. Theories in cognitive neuroscience typically explain our manifest representational capacities by positing internal representations, but there is little agreement about how these representations function, especially with the relatively recent proliferation of connectionist, dynamical, embodied, and enactive approaches to cognition. In this talk I sketch an account of the nature and function of representation in cognitive neuroscience that couples a realist construal of representational vehicles with a pragmatic account of (...)
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  • Philosophie der Neurowissenschaften.Holger Lyre - 2017 - In Simon Lohse & Thomas A. C. Reydon (eds.), Grundriss Wissenschaftsphilosophie: Die Philosophien der Einzelwissenschaften. Meiner.
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  • First Principles in the Life Sciences: The Free-Energy Principle, Organicism, and Mechanism.Matteo Colombo & Cory Wright - forthcoming - Synthese:1-26.
    The free-energy principle claims that biological systems behave adaptively maintaining their physical integrity only if they minimize the free energy of their sensory states. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, and function of the brain, and has been called a “postulate,” a “mandatory principle,” and an “imperative.” While it might afford a theoretical foundation for understanding the complex relationship between physical environment, life, and mind, its epistemic (...)
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  • Bayesian Reverse-Engineering Considered as a Research Strategy for Cognitive Science.Carlos Zednik & Frank Jäkel - 2016 - Synthese 193 (12):3951-3985.
    Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and (...)
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  • If Perception is Probabilistic, Why Doesn't It Seem Probabilistic?Ned Block - 2018 - Philosophical Transactions of the Royal Society B 373 (1755).
    The success of the Bayesian approach to perception suggests probabilistic perceptual representations. But if perceptual representation is probabilistic, why doesn't normal conscious perception reflect the full probability distributions that the probabilistic point of view endorses? For example, neurons in MT/V5 that respond to the direction of motion are broadly tuned: a patch of cortex that is tuned to vertical motion also responds to horizontal motion, but when we see vertical motion, foveally, in good conditions, it does not look at all (...)
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  • Sculpting the Space of Actions. Explaining Human Action by Integrating Intentions and Mechanisms.Machiel Keestra - 2014 - Dissertation, University of Amsterdam
    How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...)
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  • Husserl’s Hyletic Data and Phenomenal Consciousness.Kenneth Williford - 2013 - Phenomenology and the Cognitive Sciences 12 (3):501-519.
    In the Logical Investigations, Ideas I and many other texts, Husserl maintains that perceptual consciousness involves the intentional “animation” or interpretation of sensory data or hyle, e.g., “color-data,” “tone-data,” and algedonic data. These data are not intrinsically representational nor are they normally themselves objects of representation, though we can attend to them in reflection. These data are “immanent” in consciousness; they survive the phenomenological reduction. They partly ground the intuitive or “in-the-flesh” aspect of perception, and they have a determinacy of (...)
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  • Explaining Social Norm Compliance. A Plea for Neural Representations.Matteo Colombo - 2014 - Phenomenology and the Cognitive Sciences 13 (2):217-238.
    How should we understand the claim that people comply with social norms because they possess the right kinds of beliefs and preferences? I answer this question by considering two approaches to what it is to believe (and prefer), namely: representationalism and dispositionalism. I argue for a variety of representationalism, viz. neural representationalism. Neural representationalism is the conjunction of two claims. First, what it is essential to have beliefs and preferences is to have certain neural representations. Second, neural representations are often (...)
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  • Learning What to Expect.Peggy Seriès & Aaron R. Seitz - 2013 - Frontiers in Human Neuroscience 7.
  • Bayesian Sensorimotor Psychology.Michael Rescorla - 2016 - Mind and Language 31 (1):3-36.
    Sensorimotor psychology studies the mental processes that control goal-directed bodily motion. Recently, sensorimotor psychologists have provided empirically successful Bayesian models of motor control. These models describe how the motor system uses sensory input to select motor commands that promote goals set by high-level cognition. I highlight the impressive explanatory benefits offered by Bayesian models of motor control. I argue that our current best models assign explanatory centrality to a robust notion of mental representation. I deploy my analysis to defend intentional (...)
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