Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.

With In Search of Mechanisms, Carl F. Craver and Lindley Darden offer both a descriptive and an instructional account of how biologists discover mechanisms. Drawing on examples from across the life sciences and through the centuries, Craver and Darden compile an impressive toolbox of strategies that biologists have used and will use again to reveal the mechanisms that produce, underlie, or maintain the phenomena characteristic of living things. They discuss the questions that figure in the search for mechanisms, characterizing (...) the experimental, observational, and conceptual considerations used to answer them, all the while providing examples from the history of biology to highlight the kinds of evidence and reasoning strategies employed to assess mechanisms. At a deeper level, Craver and Darden pose a systematic view of what biology is, of how biology makes progress, of how biological discoveries are and might be made, and of why knowledge of biological mechanisms is important for the future of the human species. (shrink)

A core, constitutive norm of science is to remove or remedy the artefacts in one’s data. Here, we consider examples of artefacts from many fields of science (for example, astronomy, economics, electrophysiology, psychology, and systems neuroscience) and discuss their contribution to a more general evidential selection problem at the heart of the epistemology of evidence. Synthesizing and building on previously disparate discussions in many areas of the philosophy of science, we provide a novel, causal–pragmatic account that fits the examples and (...) clarifies the practices by which artefacts are discovered and remedied. (shrink)

The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. These experimental strategies include activation strategies, interference strategies, and additive strategies. These strategies are mutually reinforcing, (...) providing a kind of interlevel and intratheoretic robustness that has not previously been recognized. (shrink)

Hodgkin and Huxley’s model of the action potential is an apparent dream case of covering‐law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to explain it or that Hodgkin and Huxley were wrong. I defend Hodgkin (...) and Huxley against Weber’s heteronomy thesis and argue that explanations are descriptions of mechanisms. †To contact the author, please write to: Department of Philosophy, Philosophy‐Neuroscience‐Psychology Program, Washington University in St. Louis, One Brookings Drive, Wilson Hall, St. Louis, MO 63130; e‐mail: [email protected]. (shrink)

We address Turkheimer’s argument that genome-wide association studies of behaviors and psychiatric traits will fail to produce coherent explanations. We distinguish two major sources of potential i...

Long-Term Potentiation (LTP) is a kind of synaptic plasticity that many contemporary neuroscientists believe is a component in mechanisms of memory. This essay describes the discovery of LTP and the development of the LTP research program. The story begins in the 1950's with the discovery of synaptic plasticity in the hippocampus (a medial temporal lobe structure now associated with memory), and it ends in 1973 with the publication of three papers sketching the future course of the LTP research program. The (...) making of LTP was a protracted affair. Hippocampal synaptic plasticity was initially encountered as an experimental tool, then reported as a curiosity, and finally included in the ontic store of the neurosciences. Early researchers were not investigating the hippocampus in search of a memory mechanism; rather, they saw the hippocampus as a useful experimental model or as a structure implicated in the etiology of epilepsy. The link between hippocampal synaptic plasticity and learning or memory was a separate conceptual achievement. That link was formulated in at least three different ways at different times: reductively (claiming that plasticity is identical to learning), analogically (claiming that plasticity is an example or model of learning), and mechanistically (claiming that plasticity is a component in learning or memory mechanisms). The hypothesized link with learning or memory, coupled with developments in experimental techniques and preparations, shaped how researchers understood LTP itself. By 1973, the mechanistic formulation of the link between LTP and memory provided an abstract framework around which findings from multiple perspectives could be integrated into a multifield research program. (shrink)

In this book, Carl Cranor utilizes material from ethics, philosophy of law, epidemiology, tort law, regulatory law, and risk assessment to argue that the evidentiary standards for science used in the law to control toxics ought to be ...

What are the relative epistemic merits of building prosthetic models versus building nonprosthetic models and simulations? I argue that prosthetic models provide a sufficient test of affordance validity, that is, of whether the target system affords mechanisms that can be commandeered by a prosthesis. In other respects, prosthetic models are epistemically on par with nonprosthetic models. I focus on prosthetics in neuroscience, but the results are general. The goal of understanding how brain mechanisms work under ecologically and physiologically relevant conditions (...) is narrow compared to the search for maker's knowledge about how the brain can be made to work for us. (shrink)

It is common to defend the Homeostatic Property Cluster ( HPC ) view as a third way between conventionalism and essentialism about natural kinds ( Boyd , 1989, 1991, 1997, 1999; Griffiths , 1997, 1999; Keil , 2003; Kornblith , 1993; Wilson , 1999, 2005; Wilson , Barker , & Brigandt , forthcoming ). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a similarity generating ( (...) or homeostatic ) mechanism . I argue that conventional elements are involved partly but ineliminably in deciding which mechanisms define kinds , for deciding when two mechanisms are mechanisms of the same type, and for deciding where one particular mechanism ends and another begins. This intrusion of conventional perspective into the idea of a mechanism raises doubts as to whether the HPC view is sufficiently free of conventional elements to serve as an objective arbiter in scientific disputes about what the kinds of the special sciences should be. (shrink)

In a recent issue of The Monist, Alisa Bokulich argues that those who embrace an ontic conception of scientific explanation are committed to rejecting an explanatory role for idealized, i.e., deliberately false, models. Her argument is based on an inaccurate characterization of the ontic view. Indeed, her positive view of idealization embraces rather than opposes the ontic conception. Because Bokulich is not alone in this misunderstanding, an effort to diagnose and correct it might prevent scholars from talking past one another (...) and, hopefully, nudge future discussions down more inviting paths. (shrink)

We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...) behaviour. We discuss some ways that the search for mechanisms can bring about such top-down and bottom-up revision, and we consider some examples from the recent neuroeconomics literature of how varieties of progress of this sort might be achieved. (shrink)

It is a common assumption in contemporary cognitive neuroscience that discovering a putative realized kind to be dissociably realized (i.e., to be realized in each instance by two or more distinct realizers) mandates splitting that kind. Here I explore some limits on this inference using two deceptively similar examples: the dissociation of declarative and procedural memory and Ramachandran's argument that the self is an illusion.

The construct “remembering” is equivocal between an epistemic sense, denoting a distinctive ground for knowledge, and empirical sense, denoting the typical behavior of a neurocognitive mechanism. Because the same kind of equivocation arises for other psychologistic terms (such as believe, decide, know, judge, decide, infer and reason), the effort to spot and remedy the confusion in the case of remembering might prove generally instructive. The failure to allow these two senses of remembering equal play in their respective domains leads, I (...) argue, to unnecessary confusion about memory externalism, the possibility of episodic memory in non-human species, and the thesis of memory continuism. By distinguishing these equivocal senses of remembering, we thus gain leverage on understanding how the distinctive epistemic norms that define many of our psychologic terms are more plausibly related to the capacities studied by empirical science, given that neither identity nor elimination are possible. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

Environmentalists have advocated the Precautionary Principle (PP) to help guide public and private decisions about the environment. By contrast, industry and its spokesmen have opposed this. There is not one principle, but many that have been recommended for this purpose. Despite the attractiveness of a core idea in all versions of the principle—that decision-makers should take some precautionary steps to ensure that threats of serious and irreversible damage to the environment and public health do not materialize into harm—even one of (...) the most widely endorsed principles needs considerable specification and refinement before it can be used. Moreover, the PP is an approach or guide to utilizing scientific evidence in social or legal decision-making contexts. In this it does not differ in kind from other approaches to using factual information such as in the law. The law provides some models for different strategies to guide decision-making under uncertainty when factual issues cannot be resolved with certainty. These in turn can help guide the formulation of different versions of PP and help clarify some presuppositions of the principle. Once some plausible versions of PP are articulated, I suggest some applications to existing environmental problems. (shrink)

Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...) articulate norms of completeness for mechanistic explanations that have no such unwanted implications. _1_ Introduction _2_ A Balancing Act: When Do Details Matter? _3_ The Norms of Causal Explanation _4_ The Norms of Constitutive Explanation _5_ Salmon-Completeness _6_ From More Details to More Relevant Details _7_ Non-explanatory Virtues of Abstraction _8_ From Explanatory Models to Explanatory Knowledge _9_ Mechanistic Completeness Reconsidered _10_ Conclusion. (shrink)

A world awash in little understood chemicals tragically harms adults and children alike. Laws keep health agencies in the dark about toxicants, slow, well motivated research hampers protections, and strenuous vested opposition exacerbates the harm. How science is used in the tort law can facilitate or frustrate redress of harm. This book recommends better approaches.

Today a failure of the physical sciences accompanies a failure of the social sciences; and the failure of both consists in part in this: in the lack of a fully-developed and implemented sense of social responsibility. Both have denied guilt for their shortcomings in this respect: advancing rationalizations to the effect that social reform is not the task of science; that objectivity suffers if such motivations are allowed to become involved; and that science makes its most valuable contributions to social (...) welfare rather by maintaining a strict laboratory manner of impartiality. Implied often, as well, is the conclusion that not science itself but the misuse of science; not the patience and care of science itself but the impatience and carelessness of non-scientists is responsible for the miscarriage of its contributions. (shrink)

We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...) causes can be translated into mechanistically mediated effects, the posited relationship is intelligible and should raise no special philosophical objections. When they cannot, they are suspect. (shrink)

In “What Makes a Scientific Explanation Distinctively Mathematical?” (2013b), Lange uses several compelling examples to argue that certain explanations for natural phenomena appeal primarily to mathematical, rather than natural, facts. In such explanations, the core explanatory facts are modally stronger than facts about causation, regularity, and other natural relations. We show that Lange's account of distinctively mathematical explanation is flawed in that it fails to account for the implicit directionality in each of his examples. This inadequacy is remediable in each (...) case by appeal to ontic facts that account for why the explanation is acceptable in one direction and unacceptable in the other direction. The mathematics involved in these examples cannot play this crucial normative role. While Lange's examples fail to demonstrate the existence of distinctively mathematical explanations, they help to emphasize that many superficially natural scientific explanations rely for their explanatory force on relations of stronger-than-natural necessity. These are not opposing kinds of scientific explanations; they are different aspects of scientific explanation. (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)

An adequate understanding of the ubiquitous practice of mechanistic explanation requires an account of what Craver termed “constitutive relevance.” Entities or activities are constitutively relevant to a phenomenon when they are parts of the mechanism responsible for that phenomenon. Craver’s mutual manipulability account extended Woodward’s account of manipulationist counterfactuals to analyze how interlevel experiments establish constitutive relevance. Critics of MM argue that applying Woodward’s account to this philosophical problem conflates causation and constitution, thus rendering the account incoherent. These criticisms, we (...) argue, arise from failing to distinguish the semantic, epistemic, and metaphysical aspects of the problem of constitutive relevance. In distinguishing these aspects of the problem and responding to these critics accordingly, we amend MM into a refined epistemic criterion, the “matched interlevel experiments” account. Further, we explain how this epistemological thesis is grounded in the plausible metaphysical thesis that constitutive relevance is causal betweenness. (shrink)

Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions-according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system-captures one important sense of "function" in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explanation. The synthesis produces an analysis of specifically mechanistic role functions, one that uses the characteristic (...) active, spatial, temporal, and hierarchical organization of mechanisms to add precision and content to Cummins' original suggestion. This synthesis also shows why the discovery of role functions is a scientific achievement. Discovering a role function (i) contributes to the interlevel integration of multilevel mechanisms, and (ii) provides a unique, contextual variety of causal/mechanical explanation. (shrink)

To model potential interactions, memory must not only mesh prior patterns of action, as Glenberg proposes, but also their internal consequences. This is necessary both to discriminate sensorimotor information by its relevance and to explain how go als about the world develop. In the absence of internal feedback, Glenberg is forced to reintroduce a grounding problem into his otherwise sound model by presupposing interactive goals.

The relationship between science, law and justice has become a pressing issue with US Supreme Court decisions beginning with Daubert v. Merrell-Dow Pharmaceutical. How courts review scientific testimony and its foundation before trial can substantially affect the possibility of justice for persons wrongfully injured by exposure to toxic substances. If courts do not review scientific testimony, they will deny one of the parties the possibility of justice. Even if courts review evidence well, the fact and perception of greater judicial scrutiny (...) increases litigation costs and attorney screening of clients. Mistaken review of scientific evidence can decrease citizen access to the law, increase unfortunate incentives for firms not to test their products, lower deterrence for wrongful conduct and harmful products, and decrease the possibility of justice for citizens injured by toxic substances. This book introduces these issues, reveals the relationships that pose problems, and shows how justice can be denied. (shrink)

This chapter contains sections titled: Introduction The Once Received View (ORV) Criticisms of the ORV The “Model Model” of Scientific Theories Mechanisms: Investigating Nonformal Patterns in Scientific Theories Conclusion.

Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as explanatory.

The idea of a precautionary principle (or precautionary principles) is beginning to come to the wider attention of the environmental community, governmental agencies, regulatory agencies, and the regulated community. Different precautionary principles have not been specified in detail, and, of course, this is difficult to do. Yet some specification must be done in order to understand it better and, if it is to be used for specific action-guidance, to implement it. Moreover, it is important to understand more about the principle, (...) its background assumptions and its comparison with other principles to which we might subscribe. This paper explores aspects of the PP and its background assumptions and presuppositions, comparing them with those for risk assessment and other statements of the PP. It also briefly indicates how it resembles legal principles in addressing problems of uncertainty. Finally, it recapitulates two possible versions of the PP and suggests an application of it for an emerging threat to the environment and public health. This review suggests the PP has plausible applications and is not the radical principle some have suggested. (shrink)

Government agencies and private risk assessors use (quasi) scientific risk assessment procedures to try to estimate or predict risk to human health or the environment that might result from exposure to toxic substances in order to take steps to prevent such risks from arising or to eliminate the risks if they already exist. In this paper I discuss several ways in which the "science" of carcinogen risk assessment differs from ordinary scientific enterprises. I also consider several ways in which normative (...) policy considerations infect this regulatory science. Scientists, philosophers of science, moral philosophers and policy makers should address these issues forthrightly in order to serve better the aims of science and regulation. (shrink)

Many environmental harms are produced by the consequences of too many people doing acts which taken together have collective bad consequences, e.g. overuse of an underground aquifer or acid rain 'killing' a lake. If such acts are wrong, what should a conscientious moral agent do in such circumstances? Examples of such harms have the general feature that they are produced by individual acts, which taken by themselves may be innocent and morally permissible, but which have disastrous consequences when too many (...) people perform them. Philosophers once thought that the generalisation argument, "If the consequences of everyone's doing acts of kind a are undesirable, then no one ought to do a," was the appropriate principle to guide a conscientious moral agent in such circumstances. However, there has been considerable literature discussing the shortcomings of this principle. Nevertheless, a proper understanding of the GA suggests that whole groups of people have collective duties to prevent such harms, which duties then provide clues to individual duties to protect the environment. In this paper I consider some major deficiencies of the generalisation argument, the collective duty which follows from the salvageable part of the argument, and the distribution of individual duties a conscientious moral agent has with regard to such environmental harms as a consequence. These duties turn out to be peculiarly political in nature with the result that conscientious moral agents may have a number of political duties to protect the environment heretofore unrealised. (shrink)