Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defences, objections, and replies into a convincing defence of the core of his theory, which is that we can analyse causation by appeal to the notion of manipulation.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.

The question has long confounded philosophers and scientists, and it is this so-called explanatory gap between biological life and consciousness that Evan ...

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences (Kaplan and Bechtel; Kaplan and Craver). We argue that mechanistic explanation is defined by localization and decomposition. We argue further that systems neuroscience contains explanations that violate both localization and decomposition. We conclude that the mechanistic model of explanation needs to either stretch to now include explanations wherein localization or decomposition fail or acknowledge that there are counterexamples to mechanistic explanation (...) in the biological sciences. (shrink)

In this article, I present two conceptual problems for Craver's mutual manipulability account of constitutive relevance in mechanisms. First, constitutive relevance threatens to imply causal relevance despite Craver (and Bechtel)'s claim that they are strictly distinct. Second, if (as is intuitively appealing) parthood is defined in terms of spatio-temporal inclusion, then the mutual manipulability account is prone to counterexamples, as I show by a case of endosymbiosis. I also present a methodological problem (a case of experimental underdetermination) and formulate two (...) partial, but fallible solutions based on the notions of parthood and synchronicity. (shrink)

Resistance to the idea that phenomenology can be relevant to cognitive scientific explanation has faced two objections advanced, respectively, from both sides of the issue: from the scientific perspective it has been suggested that phenomenology, understood as an account of first-person experience, is ultimately reducible to cognitive neuroscientific explanation; and from a phenomenological perspective it has been argued that phenomenology cannot be naturalized. In this context it makes sense to consider that the notion of scientific reduction is linked to a (...) classic scientific conception of nature. I argue that if properly understood, the proposal to rethink the concept of nature itself, in enactivist phenomenological approaches, undermines the reductionist program and redefines what it means for phenomenology to be naturalized. (shrink)

Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences. This claim is meant to hold both in principle and in practice. The basic claim is that any explanation of a particular feature of a biological system, including dynamical explanations, must ultimately be grounded in mechanistic explanation. There are several variations on this theme, some stronger and some weaker. In order to avoid equivocation and miscommunication, in section 1 we will (...) argue that mechanistic explanation is defined by localization and decomposition. In section 2 we will argue that systems neuroscience contains explanations that violate both localization and decomposition on any non-trivial construal of these concepts. Therefore, in section 3 we conclude the mechanistic model of explanation either needs to stretch to now include explanations wherein localization or decomposition fail, or acknowledge that there are counter-examples to mechanistic explanation in the biological sciences. We will also consider consequences and possible replies on the part of the mechanist in section 3. (shrink)