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  1. Extended Control Systems: A Theory and its Implications.Hunter R. Gentry - 2021 - Philosophical Psychology 34 (3):345-373.
    Philosophers and cognitive scientists alike have recently been interested in whether cognition extends beyond the boundaries of skin and skull and into the environment. However, the extended cognition hypothesis has suffered many objections over the past few decades. In this paper, I explore the option of control extending beyond the human boundary. My aim is to convince the reader of three things: (i) that control can be implemented in artifacts, (ii) that humans and artifacts can form extended control systems, and (...)
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  • Computational Modelling for Alcohol Use Disorder.Matteo Colombo - forthcoming - Erkenntnis:1-21.
    In this paper, I examine Reinforcement Learning modelling practice in psychiatry, in the context of alcohol use disorders. I argue that the epistemic roles RL currently plays in the development of psychiatric classification and search for explanations of clinically relevant phenomena are best appreciated in terms of Chang’s account of epistemic iteration, and by distinguishing mechanistic and aetiological modes of computational explanation.
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  • Psychology and Neuroscience: The Distinctness Question.Brice Bantegnie - 2022 - Erkenntnis 87 (4):1753-1772.
    In a recent paper, Gualtiero Piccinini and Carl Craver have argued that psychology is not distinct from neuroscience. Many have argued that Piccinini and Craver’s argument is unsuccessful. However, none of these authors have questioned the appropriateness of Piccinini and Craver’s argument for their key premise—that functional analyses are mechanism sketches. My first and main goal in this paper is to show that Piccinini and Craver offer normative considerations in support of what is a descriptive premise and to provide some (...)
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  • Auditory Perception – Its Functions and Disorders. Towards a Mechanistic Analyses of Auditory Hybrid Systems.Robert Poczobut - 2020 - Studies in Logic, Grammar and Rhetoric 62 (1):207-227.
    The aim of the paper is to present and analyze problems associated with the mechanisms of auditory perception, their specific disorders and functions. I discuss research on speech perception in the broader theoretical context of the mechanistic model of scientific explanation and the perspective of cognitive implantology that explores the possibilities for building hybrid auditory systems.
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  • Explicating Agency: The Case of Visual Attention.Denis Buehler - forthcoming - Philosophical Quarterly.
    How do individuals guide their activities towards some goal? Harry Frankfurt once identified the task of explaining guidance as the central problem in action theory. An explanation has proved to be elusive, however. In this paper, I show how we can marshal empirical research to make explanatory progress. I contend that human agents have a primitive capacity to guide visual attention, and that this capacity is actually constituted by a sub-individual psychological control-system: the executive system. I thus illustrate how we (...)
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  • What Levels of Explanation in the Behavioural Sciences?Giuseppe Boccignone & Roberto Cordeschi (eds.) - 2015 - Frontiers Media SA.
    Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...)
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  • The Methodological Role of Mechanistic-Computational Models in Cognitive Science.Jens Harbecke - 2020 - Synthese 199 (Suppl 1):19-41.
    This paper discusses the relevance of models for cognitive science that integrate mechanistic and computational aspects. Its main hypothesis is that a model of a cognitive system is satisfactory and explanatory to the extent that it bridges phenomena at multiple mechanistic levels, such that at least several of these mechanistic levels are shown to implement computational processes. The relevant parts of the computation must be mapped onto distinguishable entities and activities of the mechanism. The ideal is contrasted with two other (...)
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  • Mechanisms in Cognitive Science.Carlos Zednik - 2017 - In Phyllis McKay Illari & Stuart Glennan (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. London: Routledge. pp. 389-400.
    This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...)
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  • Can Predictive Processing Explain Self-Deception?Marko Jurjako - 2022 - Synthese 200 (4):1-20.
    The prediction error minimization framework denotes a family of views that aim at providing a unified theory of perception, cognition, and action. In this paper, I discuss some of the theoretical limitations of PEM. It appears that PEM cannot provide a satisfactory explanation of motivated reasoning, as instantiated in phenomena such as self-deception, because its cognitive ontology does not have a separate category for motivational states such as desires. However, it might be thought that this objection confuses levels of explanation. (...)
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  • Coordinated Pluralism as a Means to Facilitate Integrative Taxonomies of Cognition.Jacqueline Anne Sullivan - 2017 - Philosophical Explorations 20 (2):129-145.
    The past decade has witnessed a growing awareness of conceptual and methodological hurdles within psychology and neuroscience that must be addressed for taxonomic and explanatory progress in understanding psychological functions to be possible. In this paper, I evaluate several recent knowledge-building initiatives aimed at overcoming these obstacles. I argue that while each initiative offers important insights about how to facilitate taxonomic and explanatory progress in psychology and neuroscience, only a “coordinated pluralism” that incorporates positive aspects of each initiative will have (...)
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  • Unification Strategies in Cognitive Science.Marcin Miłkowski - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):13–33.
    Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are (...)
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  • The Philosophy of Computer Science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
  • The Philosophy of Neuroscience.Bickle John, Mandik Peter & Anthony Landreth - 2007 - In Thaddeus Metz (ed.), Stanford Encyclopedia of Philosophy.
  • The Philosophy of Neuroscience.John Bickle, Pete Mandik & Anthony Landreth - 2006 - Stanford Encyclopedia of Philosophy.
    Over the past three decades, philosophy of science has grown increasingly “local.” Concerns have switched from general features of scientific practice to concepts, issues, and puzzles specific to particular disciplines. Philosophy of neuroscience is a natural result. This emerging area was also spurred by remarkable recent growth in the neurosciences. Cognitive and computational neuroscience continues to encroach upon issues traditionally addressed within the humanities, including the nature of consciousness, action, knowledge, and normativity. Empirical discoveries about brain structure and function suggest (...)
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  • A Defense of Algorithmic Homuncularism.Spencer Kinsey - unknown
    In this thesis, I defend the explanatory force of algorithmic information processing models in cognitive neuroscience. I describe the algorithmic approach to cognitive explanation, its relation to Shea’s theory of cognitive representation, and challenges stemming from neuronal population analysis and dimensionality reduction. I then consider competing interpretations of some neuroscientific data that have been central to the debate. I argue in favor of a sequenced computational explanation of the phenomenon, contra Burnston. Finally, I argue that insights from theoretical neuroscience allow (...)
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  • Rumos da Epistemologia V. 11.Luiz Dutra & Alexandre Meyer Luz (eds.) - 2011 - Núcleo de Epistemologia e Lógica.
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  • Reconciling New Mechanism and Psychological Explanation: A Pragmatic Approach.Michael De Vivo - unknown
    Recently, Gualtiero Piccinini and Carl Craver have argued that functional analyses in psychology lack explanatory autonomy from explanations in neuroscience. In this thesis I argue against this claim by motivating and defending a pragmatic-epistemic conception of autonomous psychological explanation. I argue that this conception of autonomy need not require that functional analyses be distinct in kind from neural-mechanistic explanations. I use the framework of Bas van Fraassen’s Pragmatic Theory of Explanation to show that explanations in psychology and neuroscience can be (...)
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  • Functional Individuation, Mechanistic Implementation: The Proper Way of Seeing the Mechanistic View of Concrete Computation.Dimitri Coelho Mollo - 2017 - Synthese 195 (8):3477-3497.
    I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...)
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  • Cajal’s Law of Dynamic Polarization: Mechanism and Design.Sergio Daniel Barberis - 2018 - Philosophies 3 (2):11-0.
    Santiago Ramón y Cajal, the primary architect of the neuron doctrine and the law of dynamic polarization, is considered to be the founder of modern neuroscience. At the same time, many philosophers, historians, and neuroscientists agree that modern neuroscience embodies a mechanistic perspective on the explanation of the nervous system. In this paper, I review the extant mechanistic interpretation of Cajal’s contribution to modern neuroscience. Then, I argue that the extant mechanistic interpretation fails to capture the explanatory import of Cajal’s (...)
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  • The Content of Marr’s Information-Processing Framework.J. Brendan Ritchie - 2019 - Philosophical Psychology 32 (7):1078-1099.
    ABSTRACTThe seminal work of David Marr, popularized in his classic work Vision, continues to exert a major influence on both cognitive science and philosophy. The interpretation of his work also co...
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  • Freedom in Uncertainty.Filippos Stamatiou - 2022 - Dissertation, University of Copenhagen
    This work develops a philosophically credible and psychologically realisable account of control that is necessary for moral responsibility. We live, think, and act in an environment of subjective uncertainty and limited information. As a result, our decisions and actions are influenced by factors beyond our control. Our ability to act freely is restricted by uncertainty, ignorance, and luck. Through three articles, I develop a naturalistic theory of control for action as a process of error minimisation that extends over time. Thus (...)
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  • Mental Kinematics: Dynamics and Mechanics of Neurocognitive Systems.David L. Barack - 2020 - Synthese 199 (1-2):1091-1123.
    Dynamical systems play a central role in explanations in cognitive neuroscience. The grounds for these explanations are hotly debated and generally fall under two approaches: non-mechanistic and mechanistic. In this paper, I first outline a neurodynamical explanatory schema that highlights the role of dynamical systems in cognitive phenomena. I next explore the mechanistic status of such neurodynamical explanations. I argue that these explanations satisfy only some of the constraints on mechanistic explanation and should be considered pseudomechanistic explanations. I defend this (...)
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  • 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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  • Are More Details Better? On the Norms of Completeness for Mechanistic Explanations.Carl F. Craver & David M. Kaplan - 2020 - British Journal for the Philosophy of Science 71 (1):287-319.
    Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...)
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  • Functional Analysis and Mechanistic Explanation.David Barrett - 2014 - Synthese 191 (12):2695-2714.
    Piccinini and Craver (Synthese 183:283–311, 2011) argue for the surprising view that psychological explanation, properly understood, is a species of mechanistic explanation. This contrasts with the ‘received view’ (due, primarily, to Cummins and Fodor) which maintains a sharp distinction between psychological explanation and mechanistic explanation. The former is typically construed as functional analysis, the analysis of some psychological capacity into an organized series of subcapacities without specifying any of the structural features that underlie the explanandum capacity. The latter idea, of (...)
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  • Against Neuroclassicism: On the Perils of Armchair Neuroscience.Alex Morgan - 2022 - Mind and Language 37 (3):329-355.
    Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...)
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  • Psychoneural Reduction: A Perspective From Neural Circuits.David Parker - 2019 - Biology and Philosophy 34 (4):44.
    Psychoneural reduction has been debated extensively in the philosophy of neuroscience. In this article I will evaluate metascientific approaches that claim direct molecular and cellular explanations of cognitive functions. I will initially consider the issues involved in linking cellular properties to behaviour from the general perspective of neural circuits. These circuits that integrate the molecular and cellular components underlying cognition and behaviour, making consideration of circuit properties relevant to reductionist debates. I will then apply this general perspective to specific systems (...)
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  • 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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  • Get the Latest Upgrade: Functionalism 6.3.1.Corey Maley & Gualtiero Piccinini - 2013 - Philosophia Scientae 17 (2):135-149.
    Functionalism is a popular solution to the mind–body problem. It has a number of versions. We outline some of the major releases of functionalism, listing some of their important features as well as some of the bugs that plagued these releases. We outline how different versions are related. Many have been pessimistic about functionalism’s prospects, but most criticisms have missed the latest upgrades. We end by suggesting a version of functionalism that provides a complete account of the mind.
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  • Pain Begins.Aviv Spector Shirtz - forthcoming - Theoria.
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  • Specific Phobia Is an Ideal Psychiatric Kind.Alexander Pereira - 2020 - Philosophy, Psychiatry, and Psychology 27 (3):299-315.
    The causes and underlying natures of common mental disorders are, for the most part, quite mysterious. Our best taxonomies acknowledge this poverty of causal knowledge about minds, brains, society, and whatever else, to instead classify psychopathology based on clusters of detectable signs and symptoms: what it is to be, say, depressed, is simply to exhibit the minimum number of typical features for the right amount of time. Nothing in this approach references what causes and maintains a characteristic set of symptoms, (...)
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  • Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective.Marcin Miłkowski - 2016 - Synthese 193 (5):1457-1478.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  • Neural Computation and the Computational Theory of Cognition.Gualtiero Piccinini & Sonya Bahar - 2013 - Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...)
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  • Exclusion, Subset Realization, and Part‐Whole Relations.Wenjun Zhang - 2022 - Ratio 35 (1):5-15.
    The subset realization view proposes to solve the causal exclusion problem of non‐reductive mental instances by taking the mental instance as a part of its physical realizer. Many philosophers have argued that such a part‐whole relation will undermine physicalist realization because parts are ontologically prior to their wholes and the subset view is thus flawed. I argue that the relation that the subset view should propose is different from the ordinary part‐whole relation. What they should propose is another kind of (...)
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  • Metacognitive Control in Single- Vs. Dual-Process Theory.Caleb Dewey - forthcoming - Thinking and Reasoning:1-36.
    Recent work in cognitive modelling has found that most of the data that has been cited as evidence for the dual-process theory (DPT) of reasoning is best explained by non-linear, “monotonic” one-process models (Stephens et al., 2018, 2019). In this paper, I consider an important caveat of this research: it uses models that are committed to unrealistic assumptions about how effectively task conditions can isolate Type-1 and Type-2 reasoning. To avoid this caveat, I develop a coordinated theoretical, experimental, and modelling (...)
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  • Dynamical Systems Implementation of Intrinsic Sentence Meaning.Hermann Moisl - forthcoming - Minds and Machines:1-27.
    This paper proposes a model for implementation of intrinsic natural language sentence meaning in a physical language understanding system, where 'intrinsic' is understood as 'independent of meaning ascription by system-external observers'. The proposal is that intrinsic meaning can be implemented as a point attractor in the state space of a nonlinear dynamical system with feedback which is generated by temporally sequenced inputs. It is motivated by John Searle's well known critique of the then-standard and currently still influential computational theory of (...)
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  • Validating Function-Based Design Methods: An Explanationist Perspective.Dingmar van Eck - 2015 - Philosophy and Technology 28 (4):511-531.
    Analysis of the adequacy of engineering design methods, as well as analysis of the utility of concepts of function often invoked in these methods, is a neglected topic in both philosophy of technology and in engineering proper. In this paper, I present an approach—dubbed an explanationist perspective—for assessing the adequacy of function-based design methods. Engineering design is often intertwined with explanation, for instance, in reverse engineering and subsequent redesign, knowledge base-assisted designing, and diagnostic reasoning. I argue that the presented approach (...)
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  • Realization Relation and the Autonomy of Special Sciences性質間の実現関係と特殊科学の自律性.Takeshi Akiba - 2022 - Journal of the Japan Association for Philosophy of Science 49 (2):87-109.
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  • The Relationship Between Psychological Capacities and Neurobiological Activities.Gregory Johnson - 2012 - European Journal for Philosophy of Science 2 (3):453-480.
    This paper addresses the relationship between psychological capacities, as they are understood within cognitive psychology, and neurobiological activities. First, Lycan’s (1987) account of this relationship is examined and certain problems with his account are explained. According to Lycan, psychological capacities occupy a higher level than neurobiological activities in a hierarchy of levels of nature, and psychological entities can be decomposed into neurobiological entities. After discussing some problems with Lycan’s account, a similar, more recent account built around levels of mechanisms is (...)
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  • The Explanatory Role of Computation in Cognitive Science.Nir Fresco - 2012 - Minds and Machines 22 (4):353-380.
    Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...)
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  • Function Ascription and Explanation: Elaborating an Explanatory Utility Desideratum for Ascriptions of Technical Functions.Dingmar van Eck & Erik Weber - 2014 - Erkenntnis 79 (6):1367-1389.
    Current philosophical theorizing about technical functions is mainly focused on specifying conditions under which agents are justified in ascribing functions to technical artifacts. Yet, assessing the precise explanatory relevance of such function ascriptions is, by and large, a neglected topic in the philosophy of technical artifacts and technical functions. We assess the explanatory utility of ascriptions of technical functions in the following three explanation-seeking contexts: why was artifact x produced?, why does artifact x not have the expected capacity to ϕ?, (...)
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  • Minimal Models and Canonical Neural Computations: The Distinctness of Computational Explanation in Neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  • Review of Physical Computation: A Mechanistic Account by Gualtiero Piccinini - Gualtiero Piccinini, Physical Computation: A Mechanistic Account. Oxford: Oxford University Press (2015), 313 Pp., $65.00 (Cloth). [REVIEW]Oron Shagrir - 2017 - Philosophy of Science 84 (3):604-612.
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  • Mechanistic Abstraction.Worth Boone & Gualtiero Piccinini - 2016 - Philosophy of Science 83 (5):686-697.
    We provide an explicit taxonomy of legitimate kinds of abstraction within constitutive explanation. We argue that abstraction is an inherent aspect of adequate mechanistic explanation. Mechanistic explanations—even ideally complete ones—typically involve many kinds of abstraction and therefore do not require maximal detail. Some kinds of abstraction play the ontic role of identifying the specific complex components, subsets of causal powers, and organizational relations that produce a suitably general phenomenon. Therefore, abstract constitutive explanations are both legitimate and mechanistic.
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  • Construct Stabilization and the Unity of the Mind-Brain Sciences.Jacqueline Anne Sullivan - 2016 - Philosophy of Science 83 (5):662-673.
    This paper offers a critique of an account of explanatory integration that claims that explanations of cognitive capacities by functional analyses and mechanistic explanations can be seamlessly integrated. It is shown that achieving such explanatory integration requires that the terms designating cognitive capacities in the two forms of explanation are stable but that experimental practice in the mind-brain sciences currently is not directed at achieving such stability. A positive proposal for changing experimental practice so as to promote such stability is (...)
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  • Understanding Non-Modular Functionality – Lessons From Genetic Algorithms.Jaakko Kuorikoski & Samuli Pöyhönen - 2013 - Philosophy of Science 80 (5):637-649.
    Evolution is often characterized as a tinkerer that creates efficient but messy solutions to problems. We analyze the nature of the problems that arise when we try to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem – solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational problems, we show that the reason for why evolutionary (...)
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  • The Functional Sense of Mechanism.Justin Garson - 2013 - Philosophy of Science 80 (3):317-333.
    This article presents a distinct sense of ‘mechanism’, which I call the functional sense of mechanism. According to this sense, mechanisms serve functions, and this fact places substantive restrictions on the kinds of system activities ‘for which’ there can be a mechanism. On this view, there are no mechanisms for pathology; pathologies result from disrupting mechanisms for functions. Second, on this sense, natural selection is probably not a mechanism for evolution because it does not serve a function. After distinguishing this (...)
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  • Localization and Intrinsic Function.Charles A. Rathkopf - 2013 - Philosophy of Science 80 (1):1-21.
    This paper describes one style of functional analysis commonly used in the neurosciences called task-bound functional analysis. The concept of function invoked by this style of analysis is distinctive in virtue of the dependence relations it bears to transient environmental properties. It is argued that task-bound functional analysis cannot explain the presence of structural properties in nervous systems. An alternative concept of neural function is introduced that draws on the theoretical neuroscience literature, and an argument is given to show that (...)
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  • Editors’ Review and Introduction: Levels of Explanation in Cognitive Science: From Molecules to Culture.Matteo Colombo & Markus Knauff - 2020 - Topics in Cognitive Science 12 (4):1224-1240.
    Cognitive science began as a multidisciplinary endeavor to understand how the mind works. Since the beginning, cognitive scientists have been asking questions about the right methodologies and levels of explanation to pursue this goal, and make cognitive science a coherent science of the mind. Key questions include: Is there a privileged level of explanation in cognitive science? How do different levels of explanation fit together, or relate to one another? How should explanations at one level inform or constrain explanations at (...)
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  • The Non-­‐Redundant Contributions of Marr’s Three Levels of Analysis for Explaining Information Processing Mechanisms.William Bechtel & Oron Shagrir - 2015 - Topics in Cognitive Science 7 (2):312-322.
    Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform. The representation and algorithmic perspective offers an understanding of how information about the environment is (...)
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