Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...) the functional properties of the system, which may not coincide with its mechanistic organization. I describe these techniques and show that despite being non-mechanistic, these cognitive models can satisfy the normative constraints on good explanations. (shrink)

Reductionism is often understood to include two theses: (1) every singular occurrence that the special sciences can explain also can be explained by physics; (2) every law in a higher-level science can be explained by physics. These claims are widely supposed to have been refuted by the multiple realizability argument, formulated by Putnam (1967, 1975) and Fodor (1968, 1975). The present paper criticizes the argument and identifies a reductionistic thesis that follows from one of the argument's premises.

Jaegwon Kim’s causal exclusion argument has rarely been evaluated from an empirical perspective. This is puzzling because its conclusion seems to be making a testable claim about the world: supervenient properties are causally inefficacious. An empirical perspective, however, reveals Kim’s argument to rest on a mistaken conception about how to test whether a property is causally efficacious. Moreover, the empirical perspective makes visible a metaphysical bias that Kim brings to his argument that involves a principle of non-inclusion.

Jaegwon Kim’s causal exclusion argument has rarely been evaluated from an empirical perspective. This is puzzling because its conclusion seems to be making a testable claim about the world: supervenient properties are causally inefficacious. An empirical perspective, however, reveals Kim’s argument to rest on a mistaken conception about how to test whether a property is causally efficacious. Moreover, the empirical perspective makes visible a metaphysical bias that Kim brings to his argument that involves a principle of non‐inclusion.

When conceived as an empirical claim, it is natural to wonder how one might test the hypothesis of multiple realization. I consider general issues of testability, show how they apply specifically to the hypothesis of multiple realization, and propose an auxiliary assumption that, I argue, must be conjoined to the hypothesis of multiple realization to ensure its testability. I argue further that Bechtel and Mundale go astray because they fail to appreciate the need for this auxiliary assumption. †To contact the (...) author, please write to: Department of Philosophy, University of Wisconsin–Madison, 5185 Helen C. White Hall, 600 North Park Street, Madison, WI 53706; e‐mail: [email protected]. (shrink)

Consider what the brain-state theorist has to do to make good his claims. He has to specify a physical–chemical state such that any organism (not just a mammal) is in pain if and only if (a) it possesses a brain of suitable physical–chemical structure; and (b) its brain is in that physical–chemical state. This means that the physical–chemical state in question must be a possible state of a mammalian brain, a reptilian brain, a mollusc’s brain (octopuses are mollusca, and certainly (...) feel pain), etc. At the same time, it must not be a possible (physically possible) state of the brain of any physically possible creature that cannot feel pain. Even if such a state can be found, it must be nomologically certain that it will also be a state of the brain of any extraterrestrial life that may be found that will be capable of feeling pain before we can even entertain the supposition that it may be pain. It is not altogether impossible that such a state will be found... . But this is certainly an ambitious hypothesis. (Putnam 1967/1975, p. 436) The belief that mental states are multiply realized is now nearly universal among philosophers, as is the belief that this fact decisively refutes the identity theory. I argue that the empirical support for multiple realization does not justify the confidence that has been placed in it. In order for multiple realization of mental states to be an objection to the identity theory, the neurological differences among pains, for example, must be such as to guarantee that they are of distinct neurological kinds. But the phenomena traditionally cited do not provide evidence of that sort of variation. In particular, examples of neural plasticity do not provide such evidence. (shrink)

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. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

Piccinini and Craver (Synthese 183:283–311, 2011) argue for the surprising view that psychological explanation, properly understood, is a species of mechanistic explanation. This contrasts with the ‘received view’ (due, primarily, to Cummins and Fodor) which maintains a sharp distinction between psychological explanation and mechanistic explanation. The former is typically construed as functional analysis, the analysis of some psychological capacity into an organized series of subcapacities without specifying any of the structural features that underlie the explanandum capacity. The latter idea, of (...) course, sees explanation as a matter of describing structures that maintain (or produce) the explanandum capacity. In this paper, I defend the received view by criticizing Piccinini and Craver’s argument for the claim that psychological explanation is not distinct from mechanistic explanation, and by showing how psychological explanations can possess explanatory force even when nothing is known about the underlying neurological details. I conclude with a few brief criticisms about the enterprise of mechanistic explanation in general. (shrink)