Numerous articles in top IS journals note as a limitation and lack of generalizability that their findings are specific to a certain type of technology, culture, and so on. We argue that this generalizability concern is about limited scope. The IS literature notes this preference for generalizability as a characteristic of good science and it is sometimes confused with statistical generalizability. We argue that such generalizability can be in conflict with explanation or prediction accuracy. An increase in scope can decrease (...) explanation or prediction accuracy. Thus, in sciences such as cancer research, where explanation and prediction accuracy are highly valued, the cancer accounts have become increasingly narrower. IS thinking has not yet benefitted from these considerations. Whether generalizability is valued should be linked with the research aims. If the aim is practical applicability through explanation or prediction accuracy, then “limited” generalizability could be a strength rather than a weakness. (shrink)

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)

Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...) find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up —situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. (shrink)

This paper aims to clarify the nature of understanding in medicine. The first part describes in more detail what it means to understand something and links a type of understanding (i.e., objectual understanding) to explanations. The second part proceeds to investigate what objectual understanding of a disease (i.e., biomedical understanding) requires by considering the case of scurvy from the history of medicine. The main hypothesis is that grasping a mechanistic explanation of a condition is necessary for a biomedical understanding of (...) that condition. The third part of the paper argues that biomedical understanding is necessary, but not sufficient for understanding in a clinical context (i.e., clinical understanding). The hypothesis is that clinical understanding combines biomedical understanding of a _disease_ or pathological condition with understanding _illness,_ which involves some degree of personal understanding of the patient. It is argued that, in many cases, clinical understanding necessitates adopting a particular second-personal stance and using cognitive resources _in addition_ to those involved in biomedical understanding. (shrink)

Analysis of the adequacy of engineering design methods, as well as analysis of the utility of concepts of function often invoked in these methods, is a neglected topic in both philosophy of technology and in engineering proper. In this paper, I present an approach—dubbed an explanationist perspective—for assessing the adequacy of function-based design methods. Engineering design is often intertwined with explanation, for instance, in reverse engineering and subsequent redesign, knowledge base-assisted designing, and diagnostic reasoning. I argue that the presented approach (...) is useful for validating function-based design methods with respect to their explanatory elements and that it supports assessment of the explanatory and design utility of “function”, and the different conceptualizations thereof, as used in such engineering design methods. I deploy two key desiderata from the explanation literature to assess the viability of function-based design methods: explanatorily relevant difference-making factors and counterfactual understanding defined in terms of what-if-things-had-been-different questions. I explicate the approach and its merits in terms of two case studies drawn from the engineering functional modeling literature: reverse engineering and redesign and malfunction analysis. I close the paper by discussing ramifications of the presented approach for the philosophy of design and the philosophy of explanation. (shrink)

In this paper I address the current debate on ontic versus epistemic conceptualizations of mechanistic explanation in the mechanisms literature. Illari recently argued that good explanations are subject to both ontic and epistemic constraints: they must describe mechanisms in the world in such fashion that they provide understanding of their workings. Elaborating upon Illari’s ‘integration’ account, I argue that causal role function discovery of mechanisms and their components is an epistemic prerequisite for achieving these two aims. This analysis extends Illari’s (...) account in important ways, putting more pressure on ontic readings of mechanistic explanation and providing an answer to the question how ontic and epistemic constraints on mechanistic explanation are related. I argue these point in terms of cases on memory research drawn from neuroscience and research on extinct neurogenetic mechanisms from early nervous systems biology. (shrink)

In this paper I apply the mechanistic account of explanation to engineering science. I discuss two ways in which this extension offers further development of the mechanistic view. First, functional individuation of mechanisms in engineering science proceeds by means of two distinct sub types of role function, behavior function and effect function, rather than role function simpliciter. Second, it offers refined assessment of the explanatory power of mechanistic explanations. It is argued that in the context of malfunction explanations of technical (...) systems, two key desiderata for mechanistic explanations, ‘completeness and specificity’ and ‘abstraction’, pull in opposite directions. I elaborate a novel explanatory desideratum to accommodate this explanatory context, dubbed ‘local specificity and global abstraction’, and further argue that it also holds for mechanistic explanations of malfunctions in the biological domain. The overall result is empirically-informed understanding of mechanistic explanation in engineering science, thus contributing to the ongoing project of understanding mechanistic explanation in novel or relatively unexplored domains. I illustrate these claims in terms of reverse engineering and malfunction explanations in engineering science. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

In this paper we consider mechanistic explanations for biologic malfunctions. Drawing on Lipton’s work on difference making, we offer three reasons why one should distinguish i) mechanistic features that only make a difference to the malfunction one aims to explain, from ii) features that make a difference to both the malfunction and normal functioning. Recognition of the distinction is important for a) repair purposes, b) mechanism discovery, and c) understanding. This analysis extends current mechanistic thinking, which fails to appreciate the (...) distinction. We illustrate our contribution with a case on sleeping disorders as arising from disruptions of circadian rhythms. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make a difference. This (...) analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

This paper examines Ian Hacking's analysis of the looping effects of psychiatric classifications, focusing on his recent account of interactive and indifferent kinds. After explicating Hacking's distinction between 'interactive kinds' (human kinds) and 'indifferent kinds' (natural kinds), I argue that Hacking cannot claim that there are 'interactive and indifferent kinds,' given the way that he introduces the interactive-indifferent distinction. Hacking is also ambiguous on whether his notion of interactive and indifferent kinds is supposed to offer an account of classifications or (...) objects of classification. I argue that these conceptual difficulties show that Hacking's account of interactive and indifferent kinds cannot be based on - and should be clearly separated from - his distinction between interactive kinds and indifferent kinds. In clarifying Hacking's account, I argue that interactive and indifferent kinds should be regarded as objects of classification (i.e., kinds of people) that can be identified with reference to a law-like biological regularity and are aware of how they are classified. Schizophrenia and depression are discussed as examples. I subsequently offer reasons for resisting Hacking's claim that the objects of classification in the human sciences - as a result of looping effects - are 'moving targets'. (shrink)

In psychiatry, pharmacological drugs play an important experimental role in attempts to identify the neurobiological causes of mental disorders. Besides being developed in applied contexts as potential treatments for patients with mental disorders, pharmacological drugs play a crucial role in research contexts as experimental instruments that facilitate the formulation and revision of neurobiological theories of psychopathology. This paper examines the various epistemic functions that pharmacological drugs serve in the discovery, refinement, testing, and elaboration of neurobiological theories of mental disorders. I (...) articulate this thesis with reference to the history of antipsychotic drugs and the evolution of the dopamine hypothesis of schizophrenia in the second half of the twentieth century. I argue that interventions with psychiatric patients through the medium of antipsychotic drugs provide researchers with information and evidence about the neurobiological causes of schizophrenia. This analysis highlights the importance of pharmacological drugs as research tools in the generation of psychiatric knowledge and the dynamic relationship between practical and theoretical contexts in psychiatry. (shrink)

We investigate the context of discovery of two significant achievements of twentieth century biochemistry: the chemiosmotic mechanism of oxidative phosphorylation and the dark reaction of photosynthesis. The pursuit of these problems involved discovery strategies such as the transfer, recombination and reversal of previous causal and mechanistic knowledge in biochemistry. We study the operation and scope of these strategies by careful historical analysis, reaching a number of systematic conclusions: even basic strategies can illuminate “hard cases” of scientific discovery that go far (...) beyond simple extrapolation or analogy; the causal–mechanistic approach to discovery permits a middle course between the extremes of a completely substrate-neutral and a completely domain-specific view of scientific discovery; the existing literature on mechanism discovery underemphasizes the role of combinatorial approaches in defining and exploring search spaces of possible problem solutions; there is a subtle interplay between a fine-grained mechanistic and a more coarse-grained causal level of analysis, and both are needed to make discovery processes intelligible. (shrink)

We investigate the context of discovery of two significant achievements of twentieth century biochemistry: the chemiosmotic mechanism of oxidative phosphorylation and the dark reaction of photosynthesis. The pursuit of these problems involved discovery strategies such as the transfer, recombination and reversal of previous causal and mechanistic knowledge in biochemistry. We study the operation and scope of these strategies by careful historical analysis, reaching a number of systematic conclusions: even basic strategies can illuminate “hard cases” of scientific discovery that go far (...) beyond simple extrapolation or analogy; the causal–mechanistic approach to discovery permits a middle course between the extremes of a completely substrate-neutral and a completely domain-specific view of scientific discovery; the existing literature on mechanism discovery underemphasizes the role of combinatorial approaches in defining and exploring search spaces of possible problem solutions; there is a subtle interplay between a fine-grained mechanistic and a more coarse-grained causal level of analysis, and both are needed to make discovery processes intelligible. (shrink)

According to mainstream philosophical views causal explanation in biology and neuroscience is mechanistic. As the term ‘mechanism’ gets regular use in these fields it is unsurprising that philosophers consider it important to scientific explanation. What is surprising is that they consider it the only causal term of importance. This paper provides an analysis of a new causal concept—it examines the cascade concept in science and the causal structure it refers to. I argue that this concept is importantly different from the (...) notion of mechanism and that this difference matters for our understanding of causation and explanation in science. (shrink)

In the last two decades few topics in philosophy of science have received as much attention as mechanistic explanation. A significant motivation for these accounts is that scientists frequently use the term “mechanism” in their explanations of biological phenomena. While scientists appeal to a variety of causal concepts in their explanations, many philosophers argue or assume that all of these concepts are well understood with the single notion of mechanism. This reveals a significant problem with mainstream mechanistic accounts– although philosophers (...) use the term “mechanism” interchangeably with other causal concepts, this is not something that scientists always do. This paper analyses two causal concepts in biology–the notions of “mechanism” and “pathway”–and how they figure in biological explanation. I argue that these concepts have unique features, that they are associated with distinct strategies of causal investigation, and that they figure in importantly different types of explanation. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it (...) is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

Peter Lipton has argued that understanding can exist in the absence of explanation. We argue that this does not denigrate explanation's importance to understanding. Specifically, we show that all of Lipton's examples are consistent with the idea that explanation is the ideal of understanding, i.e. other modes of understanding ought to be assessed by how well they replicate the understanding provided by a good and correct explanation. We defend this idea by showing that for all of Lipton's examples of non-explanatory (...) understanding of why p , there exists a correct and reasonably good explanation that would provide greater understanding of p. (shrink)

While mechanistic explanation and, to a lesser extent, nomological explanation are well-explored topics in the philosophy of biology, topological explanation is not. Nor is the role of diagrams in topological explanations. These explanations do not appeal to the operation of mechanisms or laws, and extant accounts of the role of diagrams in biological science explain neither why scientists might prefer diagrammatic representations of topological information to sentential equivalents nor how such representations might facilitate important processes of explanatory reasoning unavailable to (...) scientists who restrict themselves to sentential representations. Accordingly, relying upon a case study about immune system vulnerability to attacks on CD4+ T-cells, I argue that diagrams group together information in a way that avoids repetition in representing topological structure, facilitate identification of specific topological properties of those structures, and make available to controlled processing explanatorily salient counterfactual information about topological structures, all in ways that sentential counterparts of diagrams do not. (shrink)

In the debate on causal explanation in biology, in the past two decades largely influenced by the new mechanist approach, the concept of a pathway has recently reemerged as a promising research agenda, 551-572, 2018; The British Journal for the Philosophy of Science, 72, 131-158, 2021). Ross’ account of biological explanation differentiates several autonomous types of causal structures that play explanatory and other roles across the life sciences. NM, however, prioritizes mechanisms as vehicles of biological explanations. According to this program, (...) the causal architecture of biological pathways and other causal structures, such as cascades and processes, can be interpreted with at least one of the NM’s mechanism concepts. In other words, these alternative causal structures are not sufficiently distinctive to merit the explanatory autonomy with regard to the NM corresponding concepts. We examine the explanatory practice of molecular biology and concur with Ross that there are indeed distinct types of causal structures, not all falling under the concept of a mechanism. Nonetheless, we show that the concept of mechanism is referring to a privileged causal structure, at the center of explanatory efforts in molecular biology. Pathways and other causal concepts, while somewhat distinct from mechanisms themselves, are explanatorily relevant to the degree in which they exhibit mechanistic features, are parts of a mechanistic architecture, or may lead to a mechanistic arrangement. What emerges in that manner is a hierarchy of causal structures with mechanisms at the explanatory top, and lower levels differing in the degree in which they contribute to mechanistic arrangements. (shrink)

Research on computational models of scientific discovery investigates both the induction of descriptive laws and the construction of explanatory models. Although the work in law discovery centers on knowledge‐lean approaches to searching a problem space, research on deeper modeling tasks emphasizes the pivotal role of domain knowledge. As an example, our own research on inductive process modeling uses information about candidate processes to explain why variables change over time. However, our experience with IPM, an artificial intelligence system that implements this (...) approach, suggests that process knowledge is insufficient to avoid consideration of implausible models. To this end, the discovery system needs additional knowledge that constrains the model structures. We report on an extended system, SC‐IPM, that uses such information to reduce its search through the space of candidates and to produce models that human scientists find more plausible. We also argue that although people carry out less extensive search than SC‐IPM, they rely on the same forms of knowledge—processes and constraints—when constructing explanatory models. (shrink)

This work addresses biological explanations and aims to provide a philosophical account which brings together logical-procedural and historical-processual aspects when considering molecular pathways. It is argued that, having molecular features as explananda, a particular non-classical logical language – Zsyntax – can be used to formally represent, in terms of logical theorems, types of molecular processes, and to grasp how we get from one molecular interaction to another, hence explaining why a given outcome occurs. Expressing types of molecular biology processes in (...) terms of the Zsyntax language allows us to represent causal interactions by taking into account their context-sensitivity, and amounts to partly reviving the spirit of the so-called received view of explanation – which aimed to capture scientific explanatory accounts in terms of their logical structure and their appealing to nomological relations. Such a partial revival is pursued by invoking here non-classical deductions and empirical generalisations, which are called to provide the epistemic norms to explain the behavior of molecular pathways. (shrink)

Much of the recent philosophical debate on causation and causal explanation in the biological and biomedical sciences has focused on the notion of mechanism. Mechanisms, their nature and epistemic roles have been tackled by a range of so-called neo-mechanistic theories, and widely discussed. Without denying the merits of this approach, our paper aims to show how lately it has failed to give proper credit to processes, which are central to the field, especially of contemporary molecular biology. Processes can be summed (...) up in the notion of ‘pathway’, which is far from being just equivalent to that of ‘mechanism’ and has a profound epistemological and explanatory relevance. It is argued that an adequate consideration of pathways impels some rethinking of scientific explanation in molecular biology, namely its functional and contextual features. A number of examples are given to suggest that the focus of philosophical attention in this disciplinary field should shift from the notion of mechanism to the notion of pathway. (shrink)

La plupart des projets d’architectures cognitives dans les sciences cognitives et des explications des processus cérébraux dans les neurosciences interprètent l’esprit/cerveau comme réactif : le processus est déclenché par un stimulus et se termine par une réponse. Mais il y a de plus en plus de données laissant penser que le cerveau est endogéniquement actif : des oscillations de l’activité électrochimique à de multiples fréquences ont lieu dans le cerveau même en l’absence de stimuli et ceux-ci servent plutôt à moduler (...) ces oscillations qu’à déclencher l’activité. De plus, des données montrent que cette activité endogène est utilisée dans diverses activités de traitement de l’information. Je m’appuie sur les données issues des enregistrements cellulaires unitaires, de l’EEG et de l’IRMf en situation passive, afin de soutenir la thèse d’un comportement oscillatoire continu dans le cerveau et d’identifier plusieurs manières dont ce comportement peut contribuer à la cognition. Si les sciences cognitives ont pour but de comprendre comment nous effectuons des tâches cognitives, elles ont besoin de développer des architectures cognitives qui intègrent le type d’activité endogène dynamique présentée par le cerveau. (shrink)

La plupart des projets d’architectures cognitives dans les sciences cognitives et des explications des processus cérébraux dans les neurosciences interprètent l’esprit/cerveau comme réactif : le processus est déclenché par un stimulus et se termine par une réponse. Mais il y a de plus en plus de données laissant penser que le cerveau est endogéniquement actif : des oscillations de l’activité électrochimique à de multiples fréquences ont lieu dans le cerveau même en l’absence de stimuli et ceux-ci servent plutôt à moduler (...) ces oscillations qu’à déclencher l’activité. De plus, des données montrent que cette activité endogène est utilisée dans diverses activités de traitement de l’information. Je m’appuie sur les données issues des enregistrements cellulaires unitaires, de l’EEG et de l’IRMf en situation passive, afin de soutenir la thèse d’un comportement oscillatoire continu dans le cerveau et d’identifier plusieurs manières dont ce comportement peut contribuer à la cognition. Si les sciences cognitives ont pour but de comprendre comment nous effectuons des tâches cognitives, elles ont besoin de développer des architectures cognitives qui intègrent le type d’activité endogène dynamique présentée par le cerveau. (shrink)

Explaining the complex dynamics exhibited in many biological mechanisms requires extending the recent philosophical treatment of mechanisms that emphasizes sequences of operations. To understand how nonsequentially organized mechanisms will behave, scientists often advance what we call dynamic mechanistic explanations. These begin with a decomposition of the mechanism into component parts and operations, using a variety of laboratory-based strategies. Crucially, the mechanism is then recomposed by means of computational models in which variables or terms in differential equations correspond to properties of (...) its parts and operations. We provide two illustrations drawn from research on circadian rhythms. Once biologists identified some of the components of the molecular mechanism thought to be responsible for circadian rhythms, computational models were used to determine whether the proposed mechanisms could generate sustained oscillations. Modeling has become even more important as researchers have recognized that the oscillations generated in individual neurons are synchronized within networks; we describe models being employed to assess how different possible network architectures could produce the observed synchronized activity. (shrink)

This article argues that the basic account of mechanism and mechanistic explanation, involving sequential execution of qualitatively characterized operations, is itself insufficient to explain biological phenomena such as the capacity of living organisms to maintain themselves as systems distinct from their environment. This capacity depends on cyclic organization, including positive and negative feedback loops, which can generate complex dynamics. Understanding cyclically organized mechanisms with complex dynamics requires coordinating research directed at decomposing mechanisms into parts and operations with research using computational (...) models to recompose mechanisms and determine their dynamic behavior. This coordinated endeavor yields dynamic mechanistic explanations. (shrink)

This paper discusses the important paper by Paul Thagard on the pathway version of mechanistic explanation that is currently used in chemical explanation. The author claims that this method of explanation has a respectable pedigree and can be traced back to the Chemical Revolution in the arguments used by the Lavoisier School in their theoretical duels with Richard Kirwan, the proponent of a revised phlogistonian theory. Kirwan believed that complex chemical reactions could be explained by recourse to affinity tables that (...) catalogued the attraction that various simple bodies possessed towards each other. To explain was in effect to make a delayed prediction, it is not enough just to show how a phenomenon fits into the discernible patterns of the world. Lavoisier, Fourcroy and their colleagues used pathway reasoning, although disguising this fact by suggesting that affinities varied when subjected to n-body situations. (shrink)

This paper aims to clarify the nature of understanding in medicine. The first part describes in more detail what it means to understand something and links a type of understanding (i.e., objectual understanding) to explanations. The second part proceeds to investigate what objectual understanding of a disease (i.e., biomedical understanding) requires by considering the case of scurvy from the history of medi- cine. The main hypothesis is that grasping a mechanistic explanation of a condi- tion is necessary for a biomedical (...) understanding of that condition. The third part of the paper argues that biomedical understanding is necessary, but not sufficient for understanding in a clinical context (i.e., clinical understanding). The hypothe- sis is that clinical understanding combines biomedical understanding of a disease or pathological condition with understanding illness, which involves some degree of personal understanding of the patient. It is argued that, in many cases, clinical understanding necessitates adopting a particular second-personal stance and using cognitive resources in addition to those involved in biomedical understanding. (shrink)

We contrast reactive and endogenously active perspectives on brain activity. Both have been pursued continuously in neurophysiology laboratories since the early 20thcentury, but the endogenous perspective has received relatively little attention until recently. One of the many successes of the reactive perspective was the identification, in the second half of the 20th century, of the distinctive contributions of different brain regions involved in visual processing. The recent prominence of the endogenous perspective is due to new findings of ongoing oscillatory activity (...) in the brain at a wide range of time scales, exploiting such techniques as single-cell recording, EEG, and fMRI. We recount some of the evidence pointing to ways in which this endogenous activity is relevant to cognition and behavior. Our major objective is to consider certain implications of the contrast between the reactive and endogenous perspectives. In particular, we relate these perspectives to two different characterizations of explanation in the new mechanistic philosophy of science. In a basic mechanistic explanation, the operations of a mechanism are characterized qualitatively and as functioning sequentially until a terminating condition is realized. In contrast, a dynamic mechanistic explanation allows for non-sequential organization and emphasizes quantitative modeling of the mechanisms's behavior. For example, with appropriate parameter values a set of differential equations can be used to demonstrate ongoing oscillations in a system organized with feedback loops. We conclude that the basic conception of mechanistic explanation is adequate for reactive accounts of brain activity, but dynamical accounts are required to explain sustained, endogenous activity. (shrink)

Biology is the study of life, psychology is the study of mind, and medicine is the investigation of the causes and treatments of disease. This chapter describes how the central concepts of life, mind, and disease have undergone fundamental changes in the past 150 years or so. There has been a progression from theological, to qualitative, to mechanistic explanations of the nature of life, mind and disease. This progression has involved both theoretical change, as new theories with greater explanatory power (...) replaced older ones, and emotional change as the new theories brought reorientation of attitudes toward the nature of life, mind, and disease. After a brief comparison of theological, qualitative, and mechanistic explanations, I will describe how shifts from one kind of explanation to another have carried with them dramatic kinds of conceptual change in the key concepts in the life sciences. Three generalizations follow about the nature of conceptual change in the history of science: there has been a shift from conceptualizations in terms of simple properties to ones in terms of complex relations; conceptual change is theory change; and conceptual change is often emotional as well as cognitive. The contention that historical development proceeds in three stages originated with the nineteenth-century French philosophers, Auguste Comte, who claimed that November 9, 2006 human intellectual development progresses from a theological to a “metaphysical” stage to a “positive” (scientific) stage (Comte, 1988). The stages I have in mind are different from Comte’s, so let me say what they involve. By the theological stage I mean systems of thought in which the primary explanatory entities are supernatural ones beyond the reach of science, such as gods, devils, angels, spirits, and souls. For example, the concept of fire was initially theological, as in the Greek myth of Prometheus receiving fire from the gods.. (shrink)

Modern medicine has produced many successful theories concerning the causes of diseases. For example, we know that tuberculosis is caused by the bacterium Mycobacterium tuberculosis, and that scurvy is caused by a deficiency of vitamin C. This chapter discusses the nature of medical theories from the perspective of the philosophy, history, and psychology of science. I will review prominent philosophical accounts of what constitutes a scientific theory, and develop a new account of medical theories as representations of mechanisms that explain (...) disease. An account of the nature of medical theories should illuminate many aspects of the development and application of medical knowledge. Most importantly, it should contribute to understanding of medical explanation, both at the general level of causes of diseases and at the individual level of diagnosis of particular cases of a disease. Medical researchers seek to explain the causes of diseases such as tuberculosis, while physicians seek to identify diseases that explain symptoms such as fever. A medical theory such as the bacterial theory of tuberculosis provides good explanations at both the general and individual levels. The primary aim of this chapter is to show how these explanations work. A secondary aim is to show how an account of medical theories can shed light on other aspects of medical research and practice, including the nature of medical discovery, the process of evaluation of competing medical theories, and the ways in which effective treatments of disease depend on the development of good mechanistic theories about diseases. (shrink)

Here are some of the most important discoveries in the history of medicine: blood circulation (1620s), vaccination, (1790s), anesthesia (1840s), germ theory (1860s), X- rays (1895), vitamins (early 1900s), antibiotics (1920s-1930s), insulin (1920s), and oncogenes (1970s). This list is highly varied, as it includes basic medical knowledge such has Harvey’s account of how the heart pumps blood, hypotheses about the causes of disease such as the germ theory, ideas about the treatments of diseases such as antibiotics, and medical instruments such (...) as X-ray machines. The philosophy of medicine should be able to contribute to understanding of the nature of discoveries such as these. The great originators of the field of philosophy of science were all concerned with the nature of scientific discovery, including Francis Bacon (1960), William Whewell (1967), John Stuart Mill (1974), and Charles Peirce (1931-1958). The rise of logical positivism in the 1930s pushed discovery off the philosophical agenda, but the topic was revived through the work of philosophers such as Norwood Russell Hanson (1958), Thomas Nickles (1980), Lindley Darden (1991, 2006), and Nancy Nersessian (1984). Scientific discovery has also become an object of investigations for researchers in the fields of cognitive psychology and artificial intelligence, as seen in the work of Herbert Simon, Pat Langley, and others (Langley et al., 1987; Klahr, 2000). Today, scientific September 14, 2009 discovery is an interdisciplinary topic at the intersection of the philosophy, history, and psychology of science. The aim of this chapter is to identify patterns of discovery that illuminate some of the most important developments in the history of medicine. I have used a variety of sources to identify forty great medical discoveries (Adler, 2004; Friedman and Friedland, 1998; Science Channel, 2006; Strauss and Strauss, 2006).. (shrink)

Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.

Craver’s (2007) account of explanation in neurobiology offers one of the most sophisticated explications of the mechanism concept. This paper argues that despite groundbreaking advances in understanding mechanistic explanation, serious challenges remain. The first goal of this paper is to address the notorious problem of explanatory relevance concerning mechanistic explanation. I argue that Craver underestimates the importance of pragmatic constraints on the individuation of mechanisms, and that his suggestion for a solution of the explanatory relevance problem is therefore insufficient on (...) several counts. My second goal is to develop an alternative that explicitly incorporates both pragmatic and ontic aspects of mechanism individuation. (shrink)

Scientists, philosophers, and even the lay public commonly accept that schizophrenia stems from a biological or internal ‘dysfunction.’ However, this assessment is typically accompanied neither by well-defined criteria for determining that something is dysfunctional nor empirical evidence that schizophrenia satisfies those criteria. In the following, a concept of biological function is developed and applied to a neurobiological model of schizophrenia. It concludes that current evidence does not warrant the claim that schizophrenia stems from a biological dysfunction, and, in fact, that (...) unusual neural structures associated with schizophrenia may have functional or adaptive significance. The fact that current evidence is ambivalent between these two possibilities (dysfunction versus adaptive function) implies that schizophrenia researchers should be much more cautious in using the ‘dysfunction’ label than they currently are. This has implications for both psychiatric treatment as well as public perception of mental disorders. (shrink)

As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather than (...) reduce them, as well as the different ways in which mechanisms are discovered. Finally, we offer a more detailed example of an important psychological phenomenon for which mechanistic explanation has provided the main source of scientific understanding. (shrink)

Causal selection has to do with the distinction we make between background conditions and “the” true cause or causes of some outcome of interest. A longstanding consensus in philosophy views causal selection as lacking any objective rationale and as guided, instead, by arbitrary, pragmatic, and non-scientific considerations. I argue against this position in the context of causal selection for disease traits. In this domain, causes are selected on the basis of the type of causal control they exhibit over a disease (...) of interest. My analysis clarifies the principled rationale that guides this selection and how it involves both pragmatic and objective considerations, which have been overlooked in the extant literature. (shrink)

Causal selection has to do with a distinction between mere background conditions and the "true" causes of some outcome of interest. Mainstream philosophical views claim that causal selection is "groundless" in the sense that it lacks any type of principled rationale. I argue against this position in the context of biochemistry where causal factors are selected in explanations of metabolic processes. These factors are selected on the basis of a principled rationale, which is best understood in terms of the causal (...) control that they provide over an outcome of interest. (shrink)