25 found
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  1. Decoupling Topological Explanations from Mechanisms.Daniel Kostic & Kareem Khalifa - 2023 - Philosophy of Science 90 (2):245 - 268.
    We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...)
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  2. General Theory of Topological Explanations and Explanatory Asymmetry.Daniel Kostic - 2020 - Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1796):1-8.
    In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; (...)
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  3. Topological Explanations: An Opinionated Appraisal.Daniel Kostić - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge. pp. 96-115.
    This chapter provides a systematic overview of topological explanations in the philosophy of science literature. It does so by presenting an account of topological explanation that I (Kostić and Khalifa 2021; Kostić 2020a; 2020b; 2018) have developed in other publications and then comparing this account to other accounts of topological explanation. Finally, this appraisal is opinionated because it highlights some problems in alternative accounts of topological explanations, and also it outlines responses to some of the main criticisms raised by the (...)
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  4. Integrating Philosophy of Understanding with the Cognitive Sciences.Kareem Khalifa, Farhan Islam, J. P. Gamboa, Daniel Wilkenfeld & Daniel Kostić - 2022 - Frontiers in Systems Neuroscience 16.
    We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.
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  5. The topological realization.Daniel Kostić - 2018 - Synthese (1).
    In this paper, I argue that the newly developed network approach in neuroscience and biology provides a basis for formulating a unique type of realization, which I call topological realization. Some of its features and its relation to one of the dominant paradigms of realization and explanation in sciences, i.e. the mechanistic one, are already being discussed in the literature. But the detailed features of topological realization, its explanatory power and its relation to another prominent view of realization, namely the (...)
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  6. The Directionality of Topological Explanations.Daniel Kostić & Kareem Khalifa - 2021 - Synthese (5-6):14143-14165.
    Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes (...)
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  7. Mechanistic and topological explanations: an introduction.Daniel Kostić - 2018 - Synthese 195 (1).
    In the last 20 years or so, since the publication of a seminal paper by Watts and Strogatz :440–442, 1998), an interest in topological explanations has spread like a wild fire over many areas of science, e.g. ecology, evolutionary biology, medicine, and cognitive neuroscience. The topological approach is still very young by all standards, and even within special sciences it still doesn’t have a single methodological programme that is applicable across all areas of science. That is why this special issue (...)
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  8. On the Role of Erotetic Constraints in Non-causal Explanations.Daniel Kostić - forthcoming - Philosophy of Science.
    In non-causal explanations, some non-causal facts (such as mathematical, modal or metaphysical) are used to explain some physical facts. However, precisely because these explanations abstract away from causal facts, they face two challenges: 1) it is not clear why would one rather than the other non-causal explanantia be relevant for the explanandum; and 2) why would standing in a particular explanatory relation (e.g., “counterfactual dependence”, “constraint”, “entailment”, “constitution”, “grounding”, and so on), and not in some other, be explanatory. I develop (...)
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  9. Minimal structure explanations, scientific understanding and explanatory depth.Daniel Kostić - 2018 - Perspectives on Science (1):48-67.
    In this paper, I outline a heuristic for thinking about the relation between explanation and understanding that can be used to capture various levels of “intimacy”, between them. I argue that the level of complexity in the structure of explanation is inversely proportional to the level of intimacy between explanation and understanding, i.e. the more complexity the less intimacy. I further argue that the level of complexity in the structure of explanation also affects the explanatory depth in a similar way (...)
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  10. Unifying the essential concepts of biological networks: biological insights and philosophical foundations.Daniel Kostic, Claus Hilgetag & Marc Tittgemeyer - 2020 - Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1796):1-8.
    Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...)
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  11. Mapping Explanatory Language in Neuroscience.Daniel Kostić & Willem Halffman - 2023 - Synthese 202 (112):1-27.
    The philosophical literature on scientific explanation in neuroscience has been dominated by the idea of mechanisms. The mechanist philosophers often claim that neuroscience is in the business of finding mechanisms. This view has been challenged in numerous ways by showing that there are other successful and widespread explanatory strategies in neuroscience. However, the empirical evidence for all these claims was hitherto lacking. Empirical evidence about the pervasiveness and uses of various explanatory strategies in neuroscience is particularly needed because examples and (...)
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    Unifying the debates: mathematical and non-causal explanations.Daniel Kostić - 2019 - Perspectives on Science 27 (1):1-6.
    In the last couple of years a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the question what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e. explanations that don’t cite causes in the explanans) sometimes take a form of the question what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue of what (...)
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  13.  97
    The vagueness constraint and the quality space for pain.Daniel Kostic - 2012 - Philosophical Psychology 25 (6):929-939.
    This paper is concerned with a quality space model as an account of the intelligibility of explanation. I argue that descriptions of causal or functional roles (Chalmers Levine, 2001) are not the only basis for intelligible explanations. If we accept that phenomenal concepts refer directly, not via descriptions of causal or functional roles, then it is difficult to find role fillers for the described causal roles. This constitutes a vagueness constraint on the intelligibility of explanation. Thus, I propose to use (...)
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  14. Explanatory Perspectivalism: Limiting the Scope of the Hard Problem of Consciousness.Daniel Kostić - 2017 - Topoi 36 (1):119-125.
    I argue that the hard problem of consciousness occurs only in very limited contexts. My argument is based on the idea of explanatory perspectivalism, according to which what we want to know about a phenomenon determines the type of explanation we use to understand it. To that effect the hard problem arises only in regard to questions such as how is it that concepts of subjective experience can refer to physical properties, but not concerning questions such as what gives rise (...)
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  15.  37
    (1 other version)Unifying the essential concepts of biological networks: biological insights and philosophical foundations.Daniel Kostic, Claus Hilgetag & Marc Tittgemeyer (eds.) - 2020 - Oxford, UK: Royal Society.
    Over the last two decades, network-focused approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While the network approach continues to grow very rapidly, some of its conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. Consequently, the central focus of this theme issue will be on (...)
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  16. Using Network Models in Person-Centered Care in Psychiatry: How Perspectivism Could Help To Draw Boundaries.Nina de Boer, Daniel Kostić, Marcos Ross, Leon de Bruin & Gerrit Glas - 2022 - Frontiers in Psychiatry, Section Psychopathology 13 (925187).
    In this paper, we explore the conceptual problems arising when using network analysis in person- centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that we can make more explicit (...)
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  17. The Explanatory Gap Account and Intelligibility of Explanation.Daniel Kostic - 2011 - Theoria 54 (3):27-42.
    This paper examines the explanatory gap account. The key notions for its proper understanding are analysed. In particular, the analysis is concerned with the role of “thick” and “thin” modes of presentation and “thick” and “thin” concepts which are relevant for the notions of “thick” and “thin” conceivability, and to that effect relevant for the gappy and non-gappy identities. The last section of the paper discusses the issue of the intelligibility of explanations. One of the conclusions is that the explanatory (...)
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  18. The Two-dimensional Argument Against Physicalism and the Conceptual Analysis.Daniel Kostic - 2011 - Belgrade Philosophical Annual 24:05-17.
    This paper is divided into three sections. In the first section I briefly outline the background of the problem, i.e. Kripke’s modal argument (Kripke 1980). In the second section I present Chalmers’ account of two- dimensional semantics and two-dimensional argument against physicalism. In the third section I criticize Chalmers’ approach based on two crucial points, one is about necessity of identities and the other is about microphysi- cal descriptions and a priori derivation.
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  19. Mathematical and Non-causal Explanations: an Introduction.Daniel Kostić - 2019 - Perspectives on Science 1 (27):1-6.
    In the last couple of years, a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the questions what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e., explanations that don’t cite causes in the explanans) sometimes take a form of the question of what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue of (...)
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  20. Objašnjenje, evidencija, teorija (Explanation, Evidence, Theory).Daniel Kostic & Dusko Prelevic - 2014 - Belgrade, Serbia: Treći program.
  21. Uloga topološke reprezentacije mozga za razumevanje njegovih svojstava, funkcija i ponašanja (“The role of topological representation of the brain in understanding its properties, functions and behaviors“).Daniel Kostic - 2016 - In Vasilije Gvozdenović (ed.), Aspekti problema mentalnih reprezentacija (Aspects of the Mental Representation Problems.
  22. Struktura objašnjenja (Structure of Explanations).Daniel Kostic - 2012 - Belgrade, Serbia: Treći program.
  23.  41
    The explanatory gap problem – how neuroscience might contribute to its solution.Daniel Kostic - 2012 - Berlin, Germany: Humboldt University Library.
    This thesis evaluates several powerful arguments that not only deny that brain states and conscious states are one and the same thing, but also claim that such an identity is unintelligible. I argue that these accounts do not undermine physicalism because they don’t provide any direct or independent justification for their tacit assumptions about a link between modes of presentation and explanation. In my view intelligibility of psychophysical identity should not be based exclusively on the analysis of meaning. The main (...)
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  24. Forging Connections: Uniting Neuroscience and Philosophy of Science. [REVIEW]Marcin Miłkowski & Daniel Kostić - 2023 - Levenstein, Daniel, Et Al. Andquot;on the Role of Theory and Modeling in Neuroscience.".
    Levenstein et al. aptly highlight some of the foundational issues in theoretical neuroscience, such as the role of abstraction and idealization in providing scientific explanations and understanding, and distinguishing under which conditions neuroscientific models provide genuine explanations, or mere descriptions, predictions, or control. -/- The authors rightly emphasize that philosophers of science can also gain valuable insights from the vast body of neuroscience literature, by employing methods of digital humanities, such as text mining, in line with the cognitive metascience approach (...)
     
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  25.  41
    The ultimate articulation of the account of explanatory understanding: Khalifa, Kareem: Understanding, explanation, and scientific knowledge, Cambridge University Press, Cambridge, 262 pp, £75 HB. [REVIEW]Daniel Kostic - 2018 - Metascience 28 (1):61-64.
    Kareem Khalifa’s Understanding, Explanation, and Scientific Knowledge is a splendid book, written in a beautiful and accessible style. It provides the ultimate articulation of his account of explanatory understanding that I am sure will be regarded as one of the landmark publications on the topic of scientific understanding. Many of the central questions regarding scientific understanding are treated from different perspectives in the book. Such questions are: Does understanding require explanations? Must it consist of mostly true information? Is it a (...)
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