Modeling mechanisms

Glennan, Stuart

doi:10.1016/j.shpsc.2005.03.011

Cited by 188 publications

(91 citation statements)

References 16 publications

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“…The same authors who question autonomy seem to underestimate the role that distinctness plays in defenses of autonomy. Sometimes proponents of mechanistic explanation even vaguely hint or assume that functional analysis is the same as mechanistic explanation (e.g., Bechtel 2008, 140;Feest 2003;Glennan 2005), but they don't articulate and defend that thesis. So long as distinctness remains in place, defenders of autonomy have room to resist the mechanist's objections.…”

Section: The Received View: Functional Analysis As Distinct and Autonmentioning

confidence: 99%

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Integrating psychology and neuroscience: functional analyses as mechanism sketches

2011

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Synthese; Synthese is available online at:http://www.springer.com/philosophy/epistemology+and+philosophy+of+science/jou rnal/11229Abstract. We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms, in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated with multilevel mechanistic explanations.1 This paper was refereed in two rounds. John Symons graciously arranged for a round of blind refereeing; thanks are due to him and the anonymous referees. In addition, thanks to those who refereed the paper non-blindly: Ken Aizawa, Robert Cummins, and Dan Weiskopf. Many thanks to audiences at the 2010 APA Pacific Division, Saint Louis University, and University of Missouri -Columbia. This material is based upon work supported by the National Science Foundation under Grant No. SES-0924527 to Gualtiero Piccinini. 2 Integrating Psychology and Neuroscience via Multi-Level Mechanistic ExplanationWhen psychologists explain behavior, the explanations typically make reference to causes that precede the behavior and make a difference to whether and how it occurs.For instance, they explain that Anna ducked because she saw a looming ball. By contrast, when psychologists explain psychological capacities such as stereopsis or working memory, they typically do so by showing that these complex capacities are made up of more basic capacities organized together. In this paper, we focus exclusively on the latter sort of explanation, which is usually referred to as functional analysis. We argue that such decompositional, constitutive explanations gain their explanatory force by describing mechanisms (even approximately and with idealization) and, conversely, that they lack explanatory force to the extent that they fail to describe mechanisms.In arguing for this point, we sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be and in some cases have been integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms, in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated with multilevel mechanistic explanations. 3The conclusion that functional analyses are mechanism sketches leads to a simple argument that psychological explanation is mechanistic. It is generally assumed that psychological explanation is functional-that it proceeds via t...

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Section: The Received View: Functional Analysis As Distinct and Autonmentioning

confidence: 99%

“…Descriptions of mechanisms-mechanism schemas (Machamer, Darden, and Craver 2000) or models (Glennan 2005, Craver 2006)-can be more or less complete.…”

Section: Mechanistic Explanationmentioning

confidence: 99%

Integrating psychology and neuroscience: functional analyses as mechanism sketches

2011

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“…The model-based view has continued its evolution throughout the twenty-first century with a focus on mechanisms and models of mechanisms (Machamer et al 2000;Bechtel and Abrahamsen 2005;Glennan 2005;Craver 2006;Woodward 2002). The former term is normally used to refer to something in the real world, while the latter is employed to denote the representation tool.…”

Section: Related Workmentioning

confidence: 99%

“…Matthewson and Calcott (2011, p. 738) agree in that "it is sometimes difficult to see where the analysis of mechanisms in the world finishes and where (or if) a discussion of their representations begins". Glennan (2005) and more recently other authors such as Matthewson andCalcott (2011) andSchaffner (2007) have elaborated on one of the model-based views of theories: constructive realism (Giere 1988). This philosophical programme regards a scientific theory as an heterogeneous structure consisting, on the one hand, of a family of (nonlinguistic) models at different levels of abstraction; on the other hand, a set of (linguistic) hypotheses claiming the similarity of models with something in the real world (a system or a class of systems).…”

Section: Related Workmentioning

confidence: 99%

Mechanistic modelling of cancer: some reflections from software engineering and philosophy of science

Cañete-Valdeón

Wieringa

Smallbone

2012

Naturwissenschaften

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There is a growing interest in mathematical mechanistic modelling as a promising strategy for understanding tumour progression. This approach is accompanied by a methodological change of making research, in which models help to actively generate hypotheses instead of waiting for general principles to become apparent once sufficient data are accumulated. This paper applies recent research from philosophy of science to uncover three important problems of mechanistic modelling which may compromise its mainstream application, namely: the dilemma of formal and informal descriptions, the need to express degrees of confidence and the need of an argumentation framework. We report experience and research on similar problems from software engineering and provide evidence that the solutions adopted there can be transferred to the biological domain. We hope this paper can provoke new opportunities for further and profitable interdisciplinary research in the field.

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“…The sorts of models we use to provide explanations often depends on the sorts of questions that we are interested in answering, and the scientific domain in which we are working. When trying to provide explanations in scientific disciplines pertaining to the mind -disciplines such as neuroscience, cognitive science and cognitive psychologythe type of model typically considered ideal for explanations is a mechanistic model (Machamer, Darden, and Craver 2000;Bechtel 2005Bechtel , 2008Glennan 2005;Craver 2006;Wimsatt 2007;Thagard 2009Thagard , 2012Eliasmith 2010). Mechanistic models provide explanations by demonstrating how objects within a system interact so as to produce some phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Minds, models and mechanisms: a new perspective on intentional psychology

Hochstein

2012

Journal of Experimental & Theoretical Artificial Intelligen

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Abstract:In this article, I argue that intentional psychology (i.e. the interpretation of human behaviour in terms of intentional states and propositional attitudes) plays an essential role in the sciences of the mind. However, this role is not one of identifying scientifically respectable states of the world. Rather, I argue that intentional psychology acts as a type of phenomenological model, as opposed to a mechanistic one. I demonstrate that, like other phenomenological models in science, intentional psychology is a methodological tool with its own benefits and insights that complements our mechanistic understanding of systems. As a result, intentional psychology's distinctive scientific benefit is its ability to model systems in unique, non-mechanistic, ways. This allows us to generate predictions that we cannot otherwise generate using the mechanistic models of neuroscience and cognitive psychology necessary for various scientific tasks.

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Modeling mechanisms

Cited by 188 publications

References 16 publications

Integrating psychology and neuroscience: functional analyses as mechanism sketches

Integrating psychology and neuroscience: functional analyses as mechanism sketches

Mechanistic modelling of cancer: some reflections from software engineering and philosophy of science

Minds, models and mechanisms: a new perspective on intentional psychology

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