The following books have been received and many of them are available for review. Interested reviewers please contact the reviews editor: [email protected]. Adams, F. and Aizawa, K., The Bounds of C...

Plausibly, agents act freely iff their actions are responses to reasons. But what sort of relationship between reason and action is required for the action to count as a response? The overwhelmingly dominant answer to this question is modalist. It holds that responses are actions that share a modally robust or secure relationship with the relevant reasons. This thesis offers a new alternative answer. It argues that responses are actions that can be explained by reasons in the right way. This (...) explanationist answer comes apart from the modalist answer. For it holds that actions are responses to reasons if they are explained by those reasons even if they don’t share a modally robust relationship. Explanationism thus offers a novel way of vindicating the intuition that alternative possibilities don’t matter to responding to reasons and (consequently) free agency. The key dialectical position the thesis develops is that both modalism and explanationism constitute attempts to capture he core type of relationship encoded by the notion of a response. Responses to reasons, at core, involve a non-accidental relationship between reason and action. We can either understand non-accidentality as a modal phenomenon – as a modally robust tracking between two facts. Or we can understand non-accidentality as an explanatory phenomenon – as a special explanatory relationship between two facts. According to my rival explanationist proposal, two facts share a non-accidental relationship iff we can give a unified explanation of why both obtain. Unified explanations are explanations of why [p&q] that cannot be decomposed into two (or more) separate independent explanations of p and of q. Consequently, according to explanationism about responding to reasons, actions are responses to reasons iff those reasons offer a rational explanation of the action that cannot be decomposed into separate independent components. (shrink)

After Wesley Salmon’s causal-mechanical stance on explanation in the 1980s, the ontic-epistemic debate of scientific explanations appeared to be resolved in the philosophy of science. However, since the twenty-first century, this debate has been rekindled among philosophers who focus on mechanistic explanations. Nevertheless, its issues have evolved, necessitating scrutiny of the new trends in this debate and a comparison with the original controversy between Carl Hempel and Salmon. The primary objective of this paper is to elucidate three categorical dimensions in (...) the ontic-epistemic debates, spanning from the original to the recent controversies. Subsequently, it will explore why the conception of explanation is linked to representations, what conditions are necessary for linguistic expressions to be explanatory, and what roles norms play in explanation. Consequently, contrary to the common stereotype, it will be argued that mechanistic explanations are more likely to be epistemic rather than ontic. (shrink)

The paper introduces a special issue of the journal Philosophical Problems in Science (ZFN) on the topic of the nature and norms of scientific explanation.

The nature of the product to be discovered guides the reasoning to discover it. Biologists and medical researchers often search for mechanisms. The "new mechanistic philosophy of science" provides resources about the nature of biological mechanisms that aid the discovery of mechanisms. Here, we apply these resources to the discovery of mechanisms in medicine. A new diagrammatic representation of a disease mechanism chain indicates both what is known and, most significantly, what is not known at a given time, thereby guiding (...) the researcher and collaborators in discovery. Mechanisms of genetic diseases provide the examples. (shrink)

It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...) face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

In recent years, scientific understanding has become a focus of attention in philosophy of science. Since understanding is typically associated with the pragmatic and psychological dimensions of explanation, shifting the focus from explanation to understanding may induce a shift from accounts that embody normative ideals to accounts that provide accurate descriptions of scientific practice. Not surprisingly, many ‘friends of understanding’ sympathize with a naturalistic approach to the philosophy of science. However, this raises the question of whether the proposed theories of (...) understanding can still have normative power. In this paper I address this question by examining two theories of scientific understanding: Jan Faye’s pragmatic-rhetorical theory and my own contextual theory of scientific understanding. I argue that both theories leave room for normativity, despite their naturalistic tendencies. The normative power of my contextual theory is illustrated with a case study of the chemical revolution. (shrink)

This article, the second of a two-part essay, outlines a solution to certain tensions in Thomist philosophical anthropology concerning the interaction of the human person’s immaterial intellectual or noetic operations with the psychosomatic sensory operations that are constituted from the formal organization of the nervous system. Continuing with where the first part left off, I argue that Thomists should not be tempted by strong emergentist accounts of mental operations that act directly on the brain, but should maintain, with Aquinas, that (...) noetic operations directly interact with psychosomatic operations. I develop a Thomist account of noetic–psychosomatic interactions that expands upon the first part’s rapprochement between the new mechanist philosophy of neuroscience and psychology and hylomorphic animalism. I argue that noetic–psychosomatic interactions are best understood as analogous to the way diverse higher and lower order psychosomatic powers interact by actualizing, coordinating, and directing the operations of other psychosomatic powers. I draw on James Ross’s arguments for the immateriality of intellectual operations as realizing definite pure functions in order to elucidate the way noetic operations uniquely actualize, coordinate, and direct the psychosomatic operations they interact with. I conclude with a conjectural sketch of how this presentation of Thomist philosophical anthropology understands the noetic and psychosomatic deficits brought about by damage to the nervous system. (shrink)

This article, the first of a two-part essay, presents an account of Aristotelian hylomorphic animalism that engages with recent work on neuroscience and philosophy of mind. I show that Aristotelian hylomorphic animalism is compatible with the new mechanist approach to neuroscience and psychology, but that it is incompatible with strong emergentism in the philosophy of mind. I begin with the basic claims of Aristotelian hylomorphic animalism and focus on its understanding of psychological powers embodied in the nervous system. Next, I (...) introduce the new mechanist approach to neuroscience and psychology and illustrate how it can enrich the more abstract ontological framework of Aristotelian hylomorphic animalism. In the third section of this article I establish in detail the many ways Aristotelian hylomorphic animalism is incompatible with strong emergentism in the philosophy of mind. Based on these fundamental differences I show why a criticism leveled against emergentism by the new mechanist philosophy does not hamper my proposed rapprochement between hylomorphism and the new mechanist philosophy. This conclusion, however, leaves untouched the problem I address in the second article, namely, is the new mechanist philosophy compatible with Aristotelian philosophical anthropology’s contention that intellectual operations are immaterial and interact with the psychosomatic operations of the rational animal? (shrink)

Borsboom and colleagues have recently proposed a “network theory” of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an “extended” network theory provide? The aim of this article is to critically examine what explanatory strategies the network theory that includes (...) both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward’s interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations. (shrink)

During the first half of the twentieth century, many philosophers of memory opposed the postulation of memory traces based on the claim that a satisfactory account of remembering need not include references to causal processes involved in recollection. However, in 1966, an influential paper by Martin and Deutscher showed that causal claims are indeed necessary for a proper account of remembering. This, however, did not settle the issue, as in 1977 Malcolm argued that even if one were to buy Martin (...) and Deutscher’s argument for causal claims, we still don’t need to postulate the existence of memory traces. This paper reconstructs the dialectic between realists and anti-realists about memory traces, suggesting that ultimately realists’ arguments amount to inferences to the best explanation. I then argue that Malcolm’s anti-realist strategy consists in the suggestion that causal explanations that do not invoke memory traces are at least as good as those that do. But then, Malcolm, I argue that there are a large number of memory phenomena for which explanations that do not postulate the existence of memory traces are definitively worse than explanations that do postulate them. Next, I offer a causal model based on an interventionist framework to illustrate when memory traces can help to explain memory phenomena and proceed to substantiate the model with details coming from extant findings in the neuroscience of memory. (shrink)

Bionic systems, connecting biological tissues with computer or robotic devices through brain–machine interfaces, can be used in various ways to discover biological mechanisms. In this article I outline and discuss a “stimulation-connection” bionics-supported methodology for the study of the brain, and compare it with other epistemic uses of bionic systems described in the literature. This methododology differs from the “synthetic”, simulative method often followed in theoretically driven Artificial Intelligence and cognitive science, even though it involves machine models of biological systems. (...) I also bring the previous analysis to bear on some claims on the epistemic value of bionic technologies made in the recent philosophical literature. I believe that the methodological reflections proposed here may contribute to the piecewise understanding of the many ways bionic technologies can be deployed not only to restore lost sensory-motor functions, but also to discover brain mechanisms. (shrink)

Bionic technologies connecting biological nervous systems to computer or robotic devices for therapeutic purposes have been recently claimed to provide novel experimental tools for the investigation of biological mechanisms. This claim is examined here by means of a methodological analysis of bionics-supported experimental inquiries on adaptive sensory-motor behaviours. Two broad classes of bionic systems (regarded here as hybrid simulations of the target biological system) are identified, which differ from each other according to whether a component of the biological target system (...) is replaced by an artificial component, or else a component of an artificial system is replaced by a biological component. The role of these hybrid systems in the modelling of adaptive sensory-motor biological behaviours is discussed with reference to bionics-supported experiments on the mechanisms of body stabilization in lampreys. Methodological problems emerging from these case studies often arise in computer-based and biorobotic simulations of biological behaviours too. Accordingly, the present analysis contributes to identifying a more general regulative methodological framework for the machine-based modelling of biological systems. (shrink)

Geologists, Paleontologists and other historical scientists are frequently concerned with narrative explanations targeting single cases. I show that two distinct explanatory strategies are employed in narratives, simple and complex. A simple narrative has minimal causal detail and is embedded in a regularity, whereas a complex narrative is more detailed and not embedded. The distinction is illustrated through two case studies: the ‘snowball earth’ explanation of Neoproterozoic glaciation and recent attempts to explain gigantism in Sauropods. This distinction is revelatory of historical (...) science. I argue that at least sometimes which strategy is appropriate is not a pragmatic issue, but turns on the nature of the target. Moreover, the distinction reveals a counterintuitive pattern of progress in some historical explanation: shifting from simple to complex. Sometimes, historical scientists rightly abandon simple, unified explanations in favour of disunified, complex narratives. Finally I compare narrative and mechanistic explanation, arguing that mechanistic approaches are inappropriate for complex narrative explanations. (shrink)

The scientific investigation of music requires contributions from a diverse array of disciplines. Given the diverse methodologies, interests and research targets of the disciplines involved, we argue that there is a plurality of legitimate research questions about music, necessitating a focus on integration. In light of this we recommend a pluralistic conception of music—that there is no unitary definition divorced from some discipline, research question or context. This has important implications for how the scientific study of music ought to proceed: (...) we show that some definitions are complementary, that is, they reflect different research interests and ought to be retained and, where possible, integrated, while others are antagonistic, they represent real empirical disagreement about music’s nature and how to account for it. We illustrate this in discussion of two related issues: questions about the evolutionary function of music, and questions of the innateness of music. These debates have been, in light of pluralism, misconceived. We suggest that, in both cases, scientists ought to proceed by constructing integrated models which take into account the dynamic interaction between different aspects of music. (shrink)

Double dissociations between perceivable colors and physical properties of colored objects have led many philosophers to endorse relationalist accounts of color. I argue that there are analogous double dissociations between attitudes of belief—the beliefs that people attribute to each other in everyday life—and intrinsic cognitive states of belief—the beliefs that some cognitive scientists posit as cogs in cognitive systems—pitched at every level of psychological explanation. These dissociations provide good reason to refrain from conflating attitudes of belief with intrinsic cognitive states (...) of belief. I suggest that interpretivism provides an attractive account of the former. Like colors, attitudes of belief evolved to be ecological signifiers, not cogs in cognitive systems. (shrink)

Our epistemic access to the past is infamously patchy: historical information degrades and disappears and bygone eras are often beyond the reach of repeatable experiments. However, historical scientists have been remarkably successful at uncovering and explaining the past. I argue that part of this success is explained by the exploitation of dependencies between historical events, entities, and processes. For instance, if sauropod dinosaurs were hot blooded, they must have been gluttons; the high-energy demands of endothermy restrict sauropod grazing strategies. Understanding (...) such dependencies extends our reach into the past in spite of incomplete data. In addition, this serves as a counterexample to two accounts of method in the historical sciences. By one, historical science proceeds by identifying ‘smoking guns’: traces that discriminate between live hypotheses. By the other, historical hypotheses are supported by consilience: the convergence of independent lines of evidence. However, testing for ‘coherency’ between past hypotheses also plays a critical role in historical confirmation. Just as historical scientists exploit dependencies between past entities and present entities to infer what the past was like, they also exploit dependencies between past entities themselves. I do not suggest that archetypical historical science proceeds in this manner. Rather, the lesson I draw is that historical methodology cannot be characterized as archetypically relying on one method or another. Historical science is at base opportunistic, and is resistant to unitary analyses. 1 Introduction2 Snowballs and Explosions: The Basic Idea3 Were Sauropods Endothermic?4 Dependent Entities and Interdependent Explanations5 Smoking Guns and Consilience. (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)

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)

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 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)

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)

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)

This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.

The most expressive account of explanations in neuroscience is currently the causal-mechanistic model formulated by Carl Craver. According to him, explanations in neuroscience describe mechanisms, in other words, it points out how parts organize themselves and interact to engender the phenomenon. Furthermore, neuroscience is unified as scientists from different areas that compose it work together to develop mechanisms. This model was extensively discussed in the last years and several criticisms were raised towards it. Still, it remains as the soundest model (...) for explanations in neuroscience nowadays. This paper is presented as a review of this model, as well as the critiques worked out against it and finishes with a brief consideration of the problem of explanation in neuroscience. (shrink)

In this paper, I investigate how researchers evaluate their characterizations of scientific phenomena. Characterizing phenomena is an important – albeit often overlooked – aspect of scientific research, as phenomena are targets of explanation and theorization. As a result, there is a lacuna in the literature regarding how researchers determine whether their characterization of a target phenomenon is appropriate for their aims. This issue has become apparent for accounts of scientific explanation that take phenomena to be explananda. In particular, philosophers who (...) endorse mechanistic explanation suggest that the discovery of the mechanisms that explain a phenomenon can lead to its recharacterization. However, they fail to make clear how these explanations provide warrant for recharacterizing their explananda phenomena. Drawing from cases of neurobiological research on potentiation phenomena, I argue that attempting to explain a phenomenon may provide reason to suspend judgment about its characterization, but this cannot provide warrant to recharacterize it if researchers cannot infer a phenomenon’s characteristics from this explanation. To explicate this, I go beyond explanation – mechanistic or otherwise – to analyze why and how researchers change their epistemic commitments in light of new evidence. (shrink)

Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...) explanation? In this article, we propose an alternative antirealist account that also fits explanatory practice in the life sciences. We pay special attention to mechanistic models, i.e. scientific models that involve a mechanism, and to the role of coherence considerations in building such models. To illustrate our points, we consider the mechanism for the action potential. 1 Introduction2 Some Core Features of Mechanistic Explanation3 Scientific Realism and Mechanistic Explanation4 Antirealist Mechanistic Explanation: The Case of the Action Potential5 Some Outstanding Issues for the Antirealist Mechanist6 Two Problems for the Realist Mechanist7 Conclusions. (shrink)

There continues to be significant confusion about the goals, scope, and nature of modelling practice in neuroeconomics. This article aims to dispel some such confusion by using one of the most recent critiques of neuroeconomic modelling as a foil. The article argues for two claims. First, currently, for at least some economic model of choice behaviour, the benefits derivable from neurally informing an economic model do not involve special tractability costs. Second, modelling in neuroeconomics is best understood within Marr’s three-level (...) of analysis framework and in light of a co-evolutionary research ideology. The first claim is established by elucidating the relationship between the tractability of a model, its descriptive accuracy, and its number of variables. The second claim relies on an explanation of what it can take to neurally inform an economic model of choice behaviour. 1 Introduction2 Neurally Informed Models of Choice: A Case Study2.1 A case study on risk-sensitive choice2.1.1 Target and modelling framework2.1.2 Research question and hypotheses2.1.3 Competitive models of risk-sensitive behaviour2.1.4 Model-based fMRI: from economics to brains and back2.2 Neurally informed modelling3 Tractability: When Does Size Matter?4 Neural Integration and the Co-evolutionary Research Ideology5 Conclusion. (shrink)

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of the distinction (...) between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help to address it. (shrink)

Can facts about subpersonal states and events be constitutively relevant to personal-level phenomena? And can knowledge of these facts inform explanations of personal-level phenomena? Some philosophers, like Jennifer Hornsby and John McDowell, argue for two negative answers whereby questions about persons and their behavior cannot be answered by using information from subpersonal psychology. Knowledge of subpersonal states and events cannot inform personal-level explanation such that they cast light on what constitutes persons? behaviors. In this paper I argue against this position. (...) After having distinguished between enabling and constitutive relevance, I defend the claim that at least some facts about subpersonal states and events are constitutively relevant to some personal-level phenomenon, and therefore can, and sometimes should, inform personal-level explanations. I draw some of the possible consequences of my claim for our understanding of personal-level behavior by focusing on the phenomenon of addiction. (shrink)

In this paper, I examine Reinforcement Learning modelling practice in psychiatry, in the context of alcohol use disorders. I argue that the epistemic roles RL currently plays in the development of psychiatric classification and search for explanations of clinically relevant phenomena are best appreciated in terms of Chang’s account of epistemic iteration, and by distinguishing mechanistic and aetiological modes of computational explanation.

Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical (...) nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way. (shrink)

Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (shrink)

In this article, I begin by giving a brief history of melanoma causation. I then discuss the current manner in which malignant melanoma is classified. In general, these systems of classification do not take account of the manner of tumour causation. Instead, they are based on phenomenological features of the tumour, such as size, spread, and morphology. I go on to suggest that misclassification of melanoma is a major problem in clinical practice. I therefore outline an alternative means of classifying (...) these tumours based on causal factors. By analogy with similar systems that have recently emerged for other cancers, I suggest that this causal classification is likely to be both workable and helpful, even in the absence of a full causal-mechanistic understanding of the aetiology of the tumour. (shrink)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

This paper addresses concerns raised recently by Datteri (Biol Philos 24:301–324, 2009) and Craver (Philos Sci 77(5):840–851, 2010) about the use of brain-extending prosthetics in experimental neuroscience. Since the operation of the implant induces plastic changes in neural circuits, it is reasonable to worry that operational knowledge of the hybrid system will not be an accurate basis for generalisation when modelling the unextended brain. I argue, however, that Datteri’s no-plasticity constraint unwittingly rules out numerous experimental paradigms in behavioural and systems (...) neuroscience which also elicit neural plasticity. Furthermore, I propose that Datteri and Craver’s arguments concerning the limitations of prosthetic modelling in basic neuroscience, as opposed to neuroengineering, rests on too narrow a view of the ways models in neuroscience should be evaluated, and that a more pluralist approach is needed. I distinguish organisational validity of models from mechanistic validity. I argue that while prosthetic models may be deficient in the latter of these explanatory virtues because of neuroplasticity, they excel in the former since organisational validity tracks the extent to which a model captures coding principles that are invariant with plasticity. Changing the brain, I conclude, is one viable route towards explaining the brain. (shrink)

It is commonly assumed that the concept of mechanism is a keytool for the scientific understanding of observable phenomena. However, there is no single definition of mechanism in the current philosophy of science. In fact, philosophers have developed several characterizations of what seemed to be a clear intuitive concept for scientists. In this paper, I will analyze these philosophical conceptions of mechanism, highlighting their problematic aspects and proposing a new mechanistic approach based on the idea that the pertinent levels of (...) organization for a mechanistic explanation can be identified with intervals of quasi-decompositionality. I argue that this approach allows us to consider that activities are directly derived from the entities’ structure. Consequently, a mechanistic explanation implies an arbitrary but not capricious choice of an organizational level. According to this approach, inter-level causation is merely apparent and there is no place for emergent properties. (shrink)

New mechanical philosophy posits that explanations in the life sciences involve the decomposition of a system into its entities and their respective activities and organization that are responsible for the explanandum phenomenon. This mechanistic account of explanation has proven problematic in its application to mathematical models, leading the mechanists to suggest different ways of aligning abstract models with the mechanist program. Initially, the discussion centered on whether the Hodgkin-Huxley model is explanatory. Network models provided another complication, as they apply to (...) a wide number of materially diverse systems. In this article, we examine the various attempts to integrate abstract models within the mechanist program, also presenting a further challenge: the Heimburg-Jackson model, which was introduced as an alternative to the Hodgkin-Huxley model. We argue that although the notion of abstraction as the omission of irrelevant mechanistic details appears to give a mechanistic solution for accommodating abstract models, this notion does not suit models whose epistemic strategy is not decompositional. As a result, the mechanist has to choose whether to dilute the mechanistic approach nearly beyond recognition or to claim that many, if not most, abstract theoretical models do not deliver mechanistic explanations, or qualify as explanatory at all. (shrink)

This article focuses on the assessment of mechanistic relations with specific attention to medicine, where mechanistic models are widely employed. I first survey recent contributions in the philosophical literature on mechanistic causation, and then take issue with Federica Russo and Jon Williamson’s thesis that two types of evidence, probabilistic and mechanistic, are at stake in the health sciences. I argue instead that a distinction should be drawn between previously acquired knowledge of mechanisms and yet-to-be-discovered knowledge of mechanisms and that both (...) probabilistic evidence and manipulation are essential with respect to newly discovered mechanisms. (shrink)

This contribution claims that the two fundamental notions of causation at work in the health sciences are manipulative and mechanistic, and investigates what kinds of evidence matter for the assessment of causal relations. This article is a development of our 2007 article, ‘Plurality of Causality’, where we argue for a pluralistic account of causation with an eye to econometrics and a single medical example. The present contribution has a wider focus, and considers the notion of evidence within a whole range (...) of disciplines belonging to the health sciences. Section 1 addresses the relations between kinds of evidence and causal accounts, and it is shown how different notions of causation can be employed in various medical cases. Section 2 calls attention to issues crucial for any adequate epistemological theory of causation, such as the distinctions between types and tokens, observational and experimental regimes, explanation and prediction. Lastly, the notion of context is articulated, highlighted in its role in the assessment of causal links. All these issues are tackled in the framework of what we label a ‘bottom–up’ epistemology. (shrink)

The terms “perspectivism” and “perspectivalism” have been the focus of an intense philosophical discussion with important repercussions for the debate about the role of mechanisms in scientific explanations. However, leading exponents of the new mechanistic philosophy have conceded more than was necessary to the radically subjectivistic perspectivalism, and fell into the opposite error, by retaining not negligible residues of objectivistic views about mechanisms. In order to remove this vacillation between the subjective-cultural and the objective-natural sides of mechanisms, we shall raise (...) the question about theory-ladenness over again and interpret it in its connection with the technical–experimental nature of scientific knowledge, as affirming the perspectival character of scientific knowledge: It is because of the character at once theory-laden and practice-laden, i.e. technique-laden, of our putting questions to nature that empirical reality must be investigated from particular perspectives: nature can be known scientifically only from a potentially infinite number of perspectives or theoretical points of view, concretely exemplified by mechanisms or experimental ‘machines’ that allow specific access to specific aspects of sensible reality. (shrink)

To introduce the issue of the tracking and identification of human agents, I examine the ability of an agent to track a human person and distinguish this target from other individuals: The ability to perform person identification. First, I discuss influential mechanistic models of the perceptual recognition of human faces and people. Such models propose detailed hypotheses about the parts and activities of the mental mechanisms that control the perceptual recognition of persons. However, models based on perceptual recognition are incomplete (...) theories of person identification because they do not explain several identification behaviors that are fundamental to human social interactions. Furthermore, recognition-based models tend to appeal to the controversial concept of the “identity” of a person without explaining what determines personal identity and persistence. To overcome these limitations, I propose to integrate the face-recognition program into a broader causal-historical theory of identification. The causal-historical theory of identification complements models focused on perceptual recognition because it can account for the types of non-perceptual identification overlooked by the face-recognition program. Moreover, it can decompose the identification behaviors into tracking processes that succeed or fail to be sensitive to causal characteristics of a target. I illustrate these advantages with a discussion of the difference between the tracking of a person understood as either a causally continuous biological organism or a psychologically continuous mind. Finally, I argue that the causal-historical theory provides a theoretical framework for investigating the tracking of relations between a target and its contextual and historical attributes, such as a target's possessions. (shrink)

To explain agent-identification behaviours, universalist theories in the biological and cognitive sciences have posited mental mechanisms thought to be universal to all humans, such as agent detection and face recognition mechanisms. These universalist theories have paid little attention to how particular sociocultural or historical contexts interact with the psychobiological processes of agent-identification. In contrast to universalist theories, contextualist theories appeal to particular historical and sociocultural contexts for explaining agent-identification. Contextualist theories tend to adopt idiographic methods aimed at recording the heterogeneity (...) of human behaviours across history, space, and cultures. Defenders of the universalist approach tend to criticise idiographic methods because such methods can lead to relativism or may lack generality. To overcome explanatory limitations of proposals that adopt either universalist or contextualist approaches in isolation, I propose a philosophical model that integrates contributions from both traditions: the psycho-historical theory of agent-identification. This theory investigates how the tracking processes that humans use for identifying agents interact with the unique socio-historical contexts that support agent-identification practices. In integrating hypotheses about the history of agents with psychological and epistemological principles regarding agent-identification, the theory can generate novel hypotheses regarding the distinction between recognition-based, heuristic-based, and explanation-based agent-identification. (shrink)

Executive functioning has been said to bear on a range of traditional philosophical topics, such as consciousness, thought, and action. Surprisingly, philosophers have not much engaged with the scientific literature on executive functioning. This lack of engagement may be due to several influential criticisms of that literature by Daniel Dennett, Alan Allport, and others. In this paper I argue that more recent research on executive functioning shows that these criticisms are no longer valid. The paper clears the way to a (...) more fruitful philosophical engagement with findings on the central executive system. (shrink)

In paradigm exercises of agency, individuals guide their activities toward some goal. A central challenge for action theory is to explain how individuals guide. This challenge is an instance of the more general problem of how to accommodate individuals and their actions in the natural world, as explained by natural science. Two dominant traditions–primitivism and the causal theory–fail to address the challenge in a satisfying way. Causal theorists appeal to causation by an intention, through a feedback mechanism, in explaining guidance. (...) Primitivists postulate primitive agential capacities in their explanations. The latter neglect to explain how primitive capacities integrate with findings from natural science. The former do not explain why some feedback mechanism’s activity amounts to the agent’s guidance. In this paper I argue that both traditions should acknowledge a capacity to guide, as actually constituted by the executive system. I argue that appeals to this empirically discovered psychological system explain how individuals guide in a way that integrates with explanations from cognitive science. Individuals’ capacity to guide is embedded in the natural world through the activity of its constituent (mechanistic) components. (shrink)

The functionalist approach to kinds has suffered recently due to its association with law-based approaches to induction and explanation. Philosophers of science increasingly view nomological approaches as inappropriate for the special sciences like psychology and biology, which has led to a surge of interest in approaches to natural kinds that are more obviously compatible with mechanistic and model-based methods, especially homeostatic property cluster theory. But can the functionalist approach to kinds be weaned off its dependency on laws? Dan Weiskopf has (...) recently offered a reboot of the functionalist program by replacing its nomological commitments with a model-based approach more closely derived from practice in psychology. Roughly, Weiskopf holds that the natural kinds of psychology will be the functional properties that feature in many empirically successful cognitive models, and that those properties need not be localized to parts of an underlying mechanism. I here skeptically examine the three modeling practices that Weiskopf thinks introduce such non-localizable properties: fictionalization, reification, and functional abstraction. In each case, I argue that recognizing functional properties introduced by these practices as autonomous kinds comes at clear cost to those explanations’ counterfactual explanatory power. At each step, a tempting functionalist response is parochialism: to hold that the false or omitted counterfactuals fall outside the modeler’s explanatory aims, and so should not be counted against functional kinds. I conclude by noting the dangers this attitude poses to scientific disagreement, inviting functionalists to better articulate how the individuation conditions for functional kinds might outstrip the perspective of a single modeler. (shrink)

Despite the ubiquity of “levels of organization” in the scientific literature, a nascent “levels skepticism” now claims that the concept of levels is an inherently flawed, misleading, or otherwise inadequate notion for understanding how life scientists produce knowledge about the natural world. However, levels skeptics rely on the maligned “layer-cake” account of levels stemming from Oppenheim and Putnam’s defense of the unity of science for their critical commentary. Recourse to layer-cake levels is understandable, as it is arguably the default conception (...) of levels in philosophy. However, relying on this conception of levels undermines the initial plausibility of general dismissals of the concept, because the problems skeptics identify within the “basic idea” of the concept “levels” are merely ones already widely acknowledged in this conception. I illustrate this “guilt by association” by looking at the embedded role of “levels” in articulating intertheoretical reductionism during the latter part of the 20th century. I conclude by suggesting a methodological framework focusing on local usage patterns as a promising means for future analysis of the levels concept. (shrink)