Minimal Structure Explanations, Scientific Understanding and Explanatory Depth

Kostić, Daniel

doi:10.1162/posc_a_00299

Cited by 11 publications

(17 citation statements)

References 38 publications

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“…Third, owing to their mathematical character, network approaches make it easier to compare and integrate data pertaining to different levels of structural, functional and causal organization in biological systems. This characteristic has been already discussed by a number of philosophers of biology [11,13,14]. However, while previous philosophical analyses highlight how this integration facilitates explanation of important biological phenomena, I emphasize its exploratory potential.…”

Section: (B) Network Models In Exploratory Research (I) Some General Featuresmentioning

confidence: 83%

“…Much of what I have to say about the exploratory functions of network models in bioscientific research, however, is meant to complement rather than challenge previous philosophical analyses (e.g. [11][12][13][14][15][16][17]). But even without doing a one-eighty in ongoing debates, I maintain that differentiating and articulating the exploratory functions of network models affords a better understanding of how researchers use these tools and methods to investigate in greater depth 1 and detail various aspects of biological systems.…”

Section: Exploratory Mathematical Modelsmentioning

confidence: 99%

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Exploring modularity in biological networks

Serban

2020

Phil. Trans. R. Soc. B

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Network theoretical approaches have shaped our understanding of many different kinds of biological modularity. This essay makes the case that to capture these contributions, it is useful to think about the role of network models in exploratory research. The overall point is that it is possible to provide a systematic analysis of the exploratory functions of network models in bioscientific research. Using two examples from molecular and developmental biology, I argue that often the same modelling approach can perform one or more exploratory functions, such as introducing new directions of research, offering a complementary set of concepts, methods and algorithms for individuating important features of natural phenomena, generating proofs of principle demonstrations and potential explanations for phenomena of interest and enlarging the scope of certain research agendas. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

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Section: (B) Network Models In Exploratory Research (I) Some General Featuresmentioning

confidence: 83%

Section: Exploratory Mathematical Modelsmentioning

confidence: 99%

Exploring modularity in biological networks

Serban

2020

Phil. Trans. R. Soc. B

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“…Topological explanations explain the dynamics of complex systems by making use of topological properties, i.e., properties of a complex system that are mathematically quantified using graph theory ( Kostić, 2019 ). To illustrate what topological properties are, a classic example might help.…”

Section: The Topological Explanatory Strategymentioning

confidence: 99%

The Network Theory of Psychiatric Disorders: A Critical Assessment of the Inclusion of Environmental Factors

et al. 2021

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Borsboom and colleagues have recently proposed a “network theory” of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an “extended” network theory provide? The aim of this article is to critically examine what explanatory strategies the network theory that includes both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward’s interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations.

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“…Admittedly, mathematical dependences can be causal or constitutive (Glennan 2017). Nevertheless, those that appear in Kostić's conception of topological explanation are neither (Kostić 2019b). Consequently, on the conception given by Kostić, topological explanation also excludes mechanisms, because mechanisms typically exhibit both causal and constitutive dependences.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a topological explanation is in essence a mathematical entailment and therefore apparently excludes mechanisms. On the other hand, according to Kostić (2019b), "the topological explanation has a structure of counterfactual that describes a mathematical dependency between a set of topological properties and a network representation of a real-world system." Admittedly, mathematical dependences can be causal or constitutive (Glennan 2017).…”

Section: Introductionmentioning

confidence: 99%

Are topological explanations really free of mechanisms?

Zhang

2021

Theory Biosci.

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Topological explanations in biology have been largely assumed to be free of mechanisms. However, by examining two classic topological explanations in the philosophical literature, this article has identified mechanisms in the corrected and complete formulations of both explanations. This constitutes the major work of this article. The minor work of this article is to address a follow-up question: given that these two topological explanations contain mechanisms, would this significantly blur the widely assumed boundary between topological and mechanistic explanations? My answer to this question is negative and the argument I have developed is that although these two topological explanations contain mechanisms, these mechanisms are explanatorily irrelevant to the target properties, which is in stark contrast to the situation in mechanistic explanations.

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Minimal Structure Explanations, Scientific Understanding and Explanatory Depth

Cited by 11 publications

References 38 publications

Exploring modularity in biological networks

Exploring modularity in biological networks

The Network Theory of Psychiatric Disorders: A Critical Assessment of the Inclusion of Environmental Factors

Are topological explanations really free of mechanisms?

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