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  1. Neural representations unobserved—or: a dilemma for the cognitive neuroscience revolution.Marco Facchin - 2023 - Synthese 203 (1):1-42.
    Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal scale of observation. (...)
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  • Evolving Concepts of Functional Localization.Joseph B. McCaffrey - 2023 - Philosophy Compass 18 (5):e12914.
    Functional localization is a central aim of cognitive neuroscience. But the nature and extent of functional localization in the human brain have been subjects of fierce theoretical debate since the 19th Century. In this essay, I first examine how concepts of functional localization have changed over time. I then analyze contemporary challenges to functional localization drawing from research on neural reuse, neural degeneracy, and the context-dependence of neural functions. I explore the consequences of these challenges for topics in philosophy of (...)
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  • Beyond the Platonic Brain: facing the challenge of individual differences in function-structure mapping.Marco Viola - 2020 - Synthese 199 (1-2):2129-2155.
    In their attempt to connect the workings of the human mind with their neural realizers, cognitive neuroscientists often bracket out individual differences to build a single, abstract model that purportedly represents (almost) every human being’s brain. In this paper I first examine the rationale behind this model, which I call ‘Platonic Brain Model’. Then I argue that it is to be surpassed in favor of multiple models allowing for patterned inter-individual differences. I introduce the debate on legitimate (and illegitimate) ways (...)
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  • The death of the cortical column? Patchwork structure and conceptual retirement in neuroscientific practice.Philipp Haueis - 2021 - Studies in History and Philosophy of Science Part A 85:101-113.
    In 1981, David Hubel and Torsten Wiesel received the Nobel Prize for their research on cortical columns—vertical bands of neurons with similar functional properties. This success led to the view that “cortical column” refers to the basic building block of the mammalian neocortex. Since the 1990s, however, critics questioned this building block picture of “cortical column” and debated whether this concept is useless and should be replaced with successor concepts. This paper inquires which experimental results after 1981 challenged the building (...)
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  • 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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  • Data Mining the Brain to Decode the Mind.Daniel Weiskopf - 2020 - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue that (...)
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  • Beyond cognitive myopia: a patchwork approach to the concept of neural function.Philipp Haueis - 2018 - Synthese 195 (12):5373-5402.
    In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...)
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  • The search of “canonical” explanations for the cerebral cortex.Alessio Plebe - 2018 - History and Philosophy of the Life Sciences 40 (3):40.
    This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...)
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  • Polychrony and the Process View of Computation.Colin Klein - 2020 - Philosophy of Science 87 (5):1140-1149.
    Some realistic models of neural spiking take into account spike timing, yet the practical relevance of spike timing is often unclear. In Eugene Izhikevich’s model, timing plays a crucial role by al...
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  • 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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  • Context-Sensitive Ontologies for a Non-reductionist Cognitive Neuroscience.Joe Dewhurst - 2018 - Australasian Philosophical Review 2 (2):224-228.
    The target article criticises reductionist programs in cognitive science for failing to take into account important explanatory features of the organism's physical embodiment and task environment. My aim in this commentary is to show how such features are increasingly being taken seriously by (some) researchers in cognitive neuroscience, who describe the functional activity of neural structures in terms that are context-sensitive rather than intrinsic. This approach can allow us to take seriously the concerns presented in Gallagher’s [2019] target article without (...)
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  • Against the “System” Module.John Zerilli - 2017 - Philosophical Psychology 30 (3):231-246.
    Modularity is a fundamental doctrine in the cognitive sciences. It holds a preeminent position in cognitive psychology and generative linguistics, as well as a long history in neurophysiology, with roots going all the way back to the early nineteenth century. But a mature field of neuroscience is a comparatively recent phenomenon and has challenged orthodox conceptions of the modular mind. One way of accommodating modularity within the new framework suggested by these developments is to go for increasingly soft versions of (...)
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  • Brain regions as difference-makers.Colin Klein - 2017 - Philosophical Psychology 30 (1-2):1-20.
    Contrastive neuroimaging is often taken to provide evidence about the localization of cognitive functions. After canvassing some problems with this approach, I offer an alternative: neuroimaging gives evidence about regions of the brain that bear difference-making relationships to psychological processes of interest. I distinguish between the specificity and what I call the systematicity of a difference-making relationship, and I show how at least some neuroimaging experiments can give evidence for systematic difference-making.
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  • Neural Reuse and the Modularity of Mind: Where to Next for Modularity?John Zerilli - 2019 - Biological Theory 14 (1):1-20.
    The leading hypothesis concerning the “reuse” or “recycling” of neural circuits builds on the assumption that evolution might prefer the redeployment of established circuits over the development of new ones. What conception of cognitive architecture can survive the evidence for this hypothesis? In particular, what sorts of “modules” are compatible with this evidence? I argue that the only likely candidates will, in effect, be the columns which Vernon Mountcastle originally hypothesized some 60 years ago, and which form part of the (...)
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  • Neural Representations Observed.Eric Thomson & Gualtiero Piccinini - 2018 - Minds and Machines 28 (1):191-235.
    The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.
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  • The Future of Cognitive Neuroscience? Reverse Inference in Focus.Marco J. Nathan & Guillermo Del Pinal - 2017 - Philosophy Compass 12 (7):e12427.
    This article presents and discusses one of the most prominent inferential strategies currently employed in cognitive neuropsychology, namely, reverse inference. Simply put, this is the practice of inferring, in the context of experimental tasks, the engagement of cognitive processes from locations or patterns of neural activation. This technique is notoriously controversial because, critics argue, it presupposes the problematic assumption that neural areas are functionally selective. We proceed as follows. We begin by introducing the basic structure of traditional “location-based” reverse inference (...)
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  • Computational neuroscience and localized neural function.Daniel C. Burnston - 2016 - Synthese 193 (12):3741-3762.
    In this paper I criticize a view of functional localization in neuroscience, which I call “computational absolutism”. “Absolutism” in general is the view that each part of the brain should be given a single, univocal function ascription. Traditional varieties of absolutism posit that each part of the brain processes a particular type of information and/or performs a specific task. These function attributions are currently beset by physiological evidence which seems to suggest that brain areas are multifunctional—that they process distinct information (...)
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  • The notorious neurophilosophy of pain: A family resemblance approach to idiosyncrasy and generalizability.Sabrina Coninx - 2021 - Mind and Language 38 (1):178-197.
    Pain continues to be one of the most controversial subjects in neurophilosophy. One focus of current debates is the apparent absence of an ideal brain‐based biomarker that could function as a coherent and distinct indicator for pain. One prominent reaction to this in the philosophical literature is scientific pain eliminativism. In this article, I argue for a non‐eliminative alternative that builds on family resemblances and provides a useful heuristic in the tradeoff between the idiosyncrasy of the neural processes corresponding to (...)
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  • The standard ontological framework of cognitive neuroscience: Some lessons from Broca’s area.Marco Viola & Elia Zanin - 2017 - Philosophical Psychology 30 (7):945-969.
    Since cognitive neuroscience aims at giving an integrated account of mind and brain, its ontology should include both neural and cognitive entities and specify their relations. According to what we call the standard ontological framework of cognitive neuroscience, the aim of cognitive neuroscience should be to establish one-to-one mappings between neural and cognitive entities. Where such entities do not yet closely align, this can be achieved by reforming the cognitive ontology, the neural ontology, or both. In order to assess the (...)
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  • Network Modularity as a Foundation for Neural Reuse.Matthew L. Stanley, Bryce Gessell & Felipe De Brigard - 2019 - Philosophy of Science 86 (1):23-46.
    The neural reuse framework developed primarily by Michael Anderson proposes that brain regions are involved in multiple and diverse cognitive tasks and that brain regions flexibly and dynamically interact in different combinations to carry out cognitive functioning. We argue that the evidence cited by Anderson and others falls short of supporting the fundamental principles of neural reuse. We map out this problem and provide solutions by drawing on recent advances in network neuroscience, and we argue that methods employed in network (...)
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  • Mechanistic inquiry and scientific pursuit: The case of visual processing.Philipp Haueis & Lena Kästner - 2022 - Studies in History and Philosophy of Science Part A 93 (C):123-135.
    Why is it rational for scientists to pursue multiple models of a phenomenon at the same time? The literatures on mechanistic inquiry and scientific pursuit each develop answers to a version of this question which is rarely discussed by the other. The mechanistic literature suggests that scientists pursue different complementary models because each model provides detailed insights into different aspects of the phenomenon under investigation. The pursuit literature suggests that scientists pursue competing models because alternative models promise to solve outstanding (...)
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  • Causation and cognition: an epistemic approach.Samuel D. Taylor - 2021 - Synthese 199 (3-4):9133-9160.
    Kaplan and Craver :601–627, 2011) and Piccinini and Craver :283–311, 2011) argue that only mechanistic explanations of cognition are genuine causal explanations, because only evidence of mechanisms reveals the causal structure of cognition. I first argue that this claim is grounded in a commitment to the mechanistic account of causality, which cannot be endorsed by a defender of causal-nonmechanistic explanations. Then, I defend the epistemic theory of causality, which holds that causal explanations are not genuine to the extent that they (...)
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  • Inference to the best neuroscientific explanation.Davide Coraci, Igor Douven & Gustavo Cevolani - 2024 - Studies in History and Philosophy of Science Part A 107 (C):33-42.
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  • Conceptual Change in Visual Neuroscience: The Receptive Field Concept.A. Nicolás Venturelli - 2021 - International Studies in the Philosophy of Science 34 (1):41-57.
    I focus on the concept of the receptive field of a sensory neuron, taking it as a prominent case to address conceptual change in the history of neuroscience. I argue for an interpretation of its ro...
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