The directionality of topological explanations

Abstract

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 involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation.

Decoupling Topological Explanations from Mechanisms

“…Consequently, all topological explanations may still track with one of these broader ontic dependency relations. Alternatively, Kostić and Khalifa (2021) argue that nothing ontic is needed to account for topological explanations' directionality. Clarifying the precise nature of the counterfactuals involved in topological explanations helps to circumscribe what a 32 See Hochstein (2016) for a relevant discussion of representation and (non-)mechanistic explanation.…”

“…Recent literature discusses topological or "network" explanations in the life sciences (Bechtel 2020;Craver 2016;Darrason 2018;Green et al 2018;Huneman 2010;Jones 2014;Kostić 2018Kostić , 2019Kostić , 2020Kostić and Khalifa 2021;Levy and Bechtel 2013;Matthiessen 2017;Rathkopf 2018;Ross 2020). Some self-described mechanists have only focused on topological explanations as a species of mechanistic explanation (Bechtel 2020;Craver 2016;DiFrisco and Jaeger 2019;Levy and Bechtel 2013).…”

Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries

“…What criteria should be met before personalized network models are able to provide topological explanations? We already discussed this briefly in a previous section, but here we will explore this in more detail using the account of topological explanations developed by Kostić (54,56,57). Kostić's account provides necessary and sufficient conditions under which a network model provides a genuine topological explanation and does so by explicitly incorporating perspectival criteria.…”

“…Network representations themselves do not provide many constraints on what can be represented. Network models typically capture global and very abstract features of a system, whereas, for instance, mechanistic models capture more finegrained and local features (49)(50)(51)(52)(53)(54)(55)(56)(57). However, nodes and edges can in principle represent anything.…”

“…The first possibility is that these models provide topological explanations, i.e., explanations that are based on the topological properties of a network. We argue that this is the most promising explanatory potential of these models because network models in general are particularly suited to provide such explanations (49,52,(55)(56)(57)(63)(64)(65)(66). What criteria should personalized network models of mental disorders meet in order to provide topological explanations?…”