Reductionism encompasses a set of ontological, epistemological, and methodological claims about the relation of different scientific domains. The basic question of reduction is whether the properties, concepts, explanations, or methods from one scientific domain (typically at higher levels of organization) can be deduced from or explained by the properties, concepts, explanations, or methods from another domain of science (typically one about lower levels of organization). Reduction is germane to a variety of issues in philosophy of science, including the structure of (...) scientific theories, the relations between different scientific disciplines, the nature of explanation, the diversity of methodology, and the very idea of theoretical progress, as well as to numerous topics in metaphysics and philosophy of mind, such as emergence, mereology, and supervenience. (shrink)

The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem, scientists often assess whether the tasks engage the same neural mechanisms. But to determine whether mechanisms are of the same or different kinds, we need to solve the abstraction problem by (...) determining which mechanistic differences are and are not relevant, and also the boundary problem by distinguishing the mechanism from its background conditions. Solving these problems, in turn, requires understanding how cognitive capacities are elicited in tasks. These three problems, which have been noted and discussed elsewhere in the literature, together form a ‘cycle of kinds’ that frames the central problem-space of cognitive ontology. We describe this cycle to clarify the intellectual challenges facing the cognitive ontologist and to reveal the kind of iterative process by which ontological revision in cognitive neuroscience is likely to unfold. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

The past decade has witnessed a growing awareness of conceptual and methodological hurdles within psychology and neuroscience that must be addressed for taxonomic and explanatory progress in understanding psychological functions to be possible. In this paper, I evaluate several recent knowledge-building initiatives aimed at overcoming these obstacles. I argue that while each initiative offers important insights about how to facilitate taxonomic and explanatory progress in psychology and neuroscience, only a “coordinated pluralism” that incorporates positive aspects of each initiative will have (...) the potential for success. (shrink)

Developing tools is a crucial aspect of experimental practice, yet most discussions of scientific change traditionally emphasize theoretical over technological change. To elaborate on the role of tools in scientific change, I offer an account that shows how scientists use tools in exploratory experiments to form novel concepts. I apply this account to two cases in neuroscience and show how tool development and concept formation are often intertwined in episodes of tool-driven change. I support this view by proposing common normative (...) principles that specify when exploratory concept formation and tool development succeed to initiate scientific change. (shrink)

The Morris water maze has been put forward in the philosophy of neuroscience as an example of an experimental arrangement that may be used to delineate the cognitive faculty of spatial memory (e.g., Craver and Darden, Theory and method in the neurosciences, University of Pittsburgh Press, Pittsburgh, 2001; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford, 2007). However, in the experimental and review literature on the water maze throughout the history of its use, (...) we encounter numerous responses to the question of “what” phenomenon it circumscribes ranging from cognitive functions (e.g., “spatial learning”, “spatial navigation”), to representational changes (e.g., “cognitive map formation”) to terms that appear to refer exclusively to observable changes in behavior (e.g., “water maze performance”). To date philosophical analyses of the water maze have not been directed at sorting out what phenomenon the device delineates nor the sources of the different answers to the question of what. I undertake both of these tasks in this paper. I begin with an analysis of Morris’s first published research study using the water maze and demonstrate that he emerged from it with an experimental learning paradigm that at best circumscribed a discrete set of observable changes in behavior. However, it delineated neither a discrete set of representational changes nor a discrete cognitive function. I cite this in combination with a reductionist-oriented research agenda in cellular and molecular neurobiology dating back to the 1980s as two sources of the lack of consistency across the history of the experimental and review literature as to what is under study in the water maze. (shrink)

Recent extensions of mechanistic explanation into psychology suggest that cognitive models are only explanatory insofar as they map neatly onto, and serve as scaffolding for more detailed neural models. Filling in those neural details is what these accounts take the integration of cognitive psychology and neuroscience to mean, and they take this process to be seamless. Critics of this view have given up on cognitive models possibly explaining mechanistically in the course of arguing for cognitive models having explanatory value independent (...) of how well they align with neural mechanisms. We can have things both ways, however. The problem with seamless integration accounts is their seamlessness, not that they take cognitive models to be mechanistic. A non-componential view of mechanisms allows for cognitive and neural models that cross cut one another, and for cognitive models that don’t decompose into parts. I illustrate the inadequacy of seamless accounts of integration by contrasting how “filter” models of attention in psychology and of sodium channels in neuroscience developed; by questioning whether the mappings generated by neuroimaging subtraction studies achieve integration; and by reinterpreting the evidence for cognitive models of memory having been successfully integrated with neural models. I argue that the integrations we can realistically expect are more partial, patchy, and full of loose threads than the mosaic unity Craver describes. (shrink)

In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.

This paper offers a critique of an account of explanatory integration that claims that explanations of cognitive capacities by functional analyses and mechanistic explanations can be seamlessly integrated. It is shown that achieving such explanatory integration requires that the terms designating cognitive capacities in the two forms of explanation are stable but that experimental practice in the mind-brain sciences currently is not directed at achieving such stability. A positive proposal for changing experimental practice so as to promote such stability is (...) put forward and its implications for explanatory integration are briefly considered. (shrink)

This paper asks (a) how new scientific objects of research are onceptualized at a point in time when little is known about them, and (b) how those conceptualizations, in turn, figure in the process of investigating the phenomena in question. Contrasting my approach with existing notions of concepts and situating it in relation to existing discussions about the epistemology of experimentation, I propose to think of concepts as research tools. I elaborate on the conception of a tool that informs my (...) account. Narrowing my focus to phenomena in cognitive neuropsychology, I then illustrate my thesis with the example of the concept of implicit memory. This account is based on an original reconstruction of the nature and function of operationism in psychology. (shrink)

The source of endless speculation and public curiosity, our scientific quest for the origins of human consciousness has expanded along with the technical capabilities of science itself and remains one of the key topics able to fire public as much as academic interest. Yet many problematic issues, identified in this important new book, remain unresolved. Focusing on a series of methodological difficulties swirling around consciousness research, the contributors to this volume suggest that ‘consciousness’ is, in fact, not a wholly viable (...) scientific concept. Supporting this ‘eliminativist‘ stance are assessments of the current theories and methods of consciousness science in their own terms, as well as applications of good scientific practice criteria from the philosophy of science. For example, the work identifies the central problem of the misuse of qualitative difference and dissociation paradigms, often deployed to identify measures of consciousness. It also examines the difficulties that attend the wide range of experimental protocols used to operationalise consciousness—and the implications this has on the findings of integrative approaches across behavioural and neurophysiological research. The work also explores the significant mismatch between the common intuitions about the content of consciousness, that motivate much of the current science, and the actual properties of the neural processes underlying sensory and cognitive phenomena. Even as it makes the negative eliminativist case, the strong empirical grounding in this volume also allows positive characterisations to be made about the products of the current science of consciousness, facilitating a re-identification of target phenomena and valid research questions for the mind sciences.​. (shrink)

To explain their role in discovery and contrast them with theory-driven research, philosophers of science have characterized exploratory experiments in terms of what they lack: namely, that they lack direction from what have been called “local theories” of the target system or object under investigation. I argue that this is incorrect: it’s not whether or not there is direction from a local theory that matters, but instead how such a theory is used to direct an experiment that matters. Appealing to (...) contemporary exploratory experiments that involve the use of experimental techniques—specifically, examples where scientists explore the interaction of neural activity and human behavior by magnetically stimulating brains—I argue that local theories of a target system can inform auxiliary hypotheses in exploratory experiments, which direct these experiments. These examples illustrate how local theories can direct the exploration of target systems where researchers do not aim to evaluate these theories. (shrink)

This paper describes one style of functional analysis commonly used in the neurosciences called task-bound functional analysis. The concept of function invoked by this style of analysis is distinctive in virtue of the dependence relations it bears to transient environmental properties. It is argued that task-bound functional analysis cannot explain the presence of structural properties in nervous systems. An alternative concept of neural function is introduced that draws on the theoretical neuroscience literature, and an argument is given to show that (...) this alternative concept of may help to overcome the explanatory limitations of task-bound functional analysis. (shrink)

New Mechanist philosophical models of "phenomenon reconstitution" understand the process to be driven by explanatory considerations. Here I discuss an episode of phenomenon reconstitution that occurred entirely within an experimental program dedicated to characterizing the phenomenon of kinesin motility. Rather than being driven by explanatory considerations, as standard mechanist views maintain, I argue that the phenomenon of kinesin motility was reconstituted to enhance researchers’ primary experimental tool—the single molecule motility assay.

Questions about phenomenology’s role in non-philosophical disciplines gained renewed attention. While we claim that phenomenology makes indispensable, unique contributions to different domains of scientific practice such as concept formation, experimental design, and data collection, we also contend that when it comes to explanation, phenomenological approaches face a dilemma. Either phenomenological attempts to explain conscious phenomena do not satisfy a central constraint on explanations, i.e. the asymmetry between explanans and explanandum, or they satisfy this explanatory asymmetry only by largely merging with (...) non-phenomenological explanation types. The consequence of this dilemma is that insofar as phenomenological approaches are explanatory, they do not provide an own type of explanation. We substantiate our two claims by offering three case studies of phenomenologically inspired experiments in cognitive science. Each case study points out a specific phenomenological contribution to experimental practice while also illustrating how phenomenological approaches face the explanatory dilemma we outline. (shrink)

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

In this article, I explain why stabilizing constructs is important to the success of the Research Domain Criteria Project and identify one measure for facilitating such stability.

This paper revisits the debate between Harry Collins and Allan Franklin, concerning the experimenters’ regress. Focusing my attention on a case study from recent psychology (regarding experimental evidence for the existence of a Mozart Effect), I argue that Franklin is right to highlight the role of epistemological strategies in scientific practice, but that his account does not sufficiently appreciate Collins’s point about the importance of tacit knowledge in experimental practice. In turn, Collins rightly highlights the epistemic uncertainty (and skepticism) surrounding (...) much experimental research. However, I will argue that his analysis of tacit knowledge fails to elucidate the reasons why scientists often are (and should be) skeptical of other researchers’ experimental results. I will present an analysis of tacit knowledge in experimental research that not only answers to this desideratum, but also shows how such skepticism can in fact be a vital enabling factor for the dynamic processes of experimental knowledge generation. (shrink)

This paper provides an interpretation of Hans-Jörg Rheinberger’s notions of epistemic things and historical epistemology . I argue that Rheinberger’s approach articulates a unique contribution to current debates about integrated HPS, and I propose some modifications and extensions of this contribution. Drawing on examples from memory research, I show that Rheinberger is right to highlight a particular feature of many objects of empirical research (“epistemic things”)—especially in the contexts of exploratory experimentation—namely our lack of knowledge about them. I argue that (...) this analysis needs to be supplemented with an account of what scientists do know, and in particular, how they are able to attribute rudimentary empirical contours to objects of research. These contours are closely connected to paradigmatic research designs, which in turn are tied to basic methodological rules for the exploration of the purported phenomena. I suggest that we engage with such rules in order to develop our own normative (epistemological) categories, and I tie this proposal to the idea of a methodological naturalism in philosophy of science. (shrink)

Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview of (...) some of the key developments in this philosophical literature and identify some interesting issues it raises about the prospects of the so-called “special sciences”, including psychiatry, psychology, and the mind-brain sciences more generally, to discover natural kinds. (shrink)

In 2007, ten world-renowned neuroscientists proposed “A Decade of the Mind Initiative.” The contention was that, despite the successes of the Decade of the Brain, “a fundamental understanding of how the brain gives rise to the mind [was] still lacking” (2007, 1321). The primary aims of the decade of the mind were “to build on the progress of the recent Decade of the Brain (1990-99)” by focusing on “four broad but intertwined areas” of research, including: healing and protecting, understanding, enriching, (...) and modeling the mind. These four aims were to be the result of “transdisciplinary and multiagency” research spanning “across disparate fields, such as cognitive science, medicine, neuroscience, psychology, mathematics, engineering, and computer science.” The proposal for a decade of the mind prompted many questions (See Spitzer 2008). In this chapter, I address three of them: (1) How do proponents of this new decade conceive of the mind? (2) Why should a decade be devoted to understanding it? (3) What should this decade look like? (shrink)

What role does the concept of representation play in the contexts of experimentation and explanation in cognitive neurobiology? In this article, a distinction is drawn between minimal and substantive roles for representation. It is argued by appeal to a case study that representation currently plays a role in cognitive neurobiology somewhere in between minimal and substantive and that this is problematic given the ultimate explanatory goals of cognitive neurobiological research. It is suggested that what is needed is for representation to (...) instead play a more substantive role. (shrink)

Most defenders of the new mechanistic approach accept ontic constraints for successful scientific explanation (Illari 2013; Craver 2014). The minimal claim is that scientific explanations have objective truthmakers, namely mechanisms that exist in the physical world independently of any observer and that cause or constitute the phenomena-to- be-explained. How can this idea be applied to type-level explanations? Many authors at least implicitly assume that in order for mechanisms to be the truthmakers of type-level explanation they need to be regular (Andersen (...) 2012; Sheredos 2015). One problem of this assumption is that most mechanisms are (highly) stochastic in the sense that they “fail more often than they succeed” (Bogen 2005; Andersen 2012). How can a mechanism type whose instances are more likely not to produce an instance of a particular phenomenon type be the truthmaker of the explanation of that particular phenomenon type? In this paper, I will give an answer to this question. I will analyze the notion of regularity and I will discuss Andersen's suggestion for how to cope with stochastic mechanisms. I will argue that her suggestion cannot account for all kinds of stochastic mechanisms and does not provide an answer as to why regularity grounds type-level explanation. According to my analysis, a mechanistic type- level explanation is true if and only if at least one of the following two conditions is satisfied: the mechanism brings about the phenomenon more often than any other phenomenon (comparative regularity) or the phenomenon is more often brought about by the mechanism than by any other mechanism/causal sequence (comparative reverse regularity). (shrink)

Recent trends in the debate about natural kinds tend towards increasingly permissive and practice-oriented views. I argue that while these accounts—which I characterize using Boyd’s ([1991]) term ‘enthusiasm’—offer several helpful insights, they often lack the normative force that they want to have; that is, they cannot provide an account of what makes something a good or bad, better or worse, kind for scientific pursuits. I argue that such accounts can regain a minimal sense of normativity in two ways. The first, (...) which has already been widely embraced by theorists, is to index the appropriateness of a scientific kind to the domain within which it is situated. While this is a good solution, it is not clear how it can be applied in interdisciplinary and cross-domain research pursuits, which are increasingly common. The second way of regaining normativity—which is especially, but not exclusively, effective for such cross-domain pursuits—is to attend to the stage at which scientific research is occurring. (shrink)

Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...) neuroscience with a particular focus on two research areas: cognitive neuroscience and cognitive neurobiology. (shrink)

Accounts of causal explanation are standard in philosophy of science. Less common are accounts of experimentation to investigate causal relations: detailed discussions of the specific kinds of experiments scientists design and run. Silva, Landreth, and Bickle’s account of “connection experiments” derives directly from landmark experiments in “molecular and cellular cognition.” We start with its key components, and then using a detailed case study from recent social neuroscience we emphasize and extend three features of SLB’s account: a division of distinct types (...) of connection experiments, each providing a different type of evidence for a hypothesized causal relationship; the typically downward-looking nature of the experimental search for mediating causes in mainstream neurobiology; and most importantly, the centrality of multiple-experiment research programs, with each experiment designed such that if successful its results can be integrated with the others, toward the goal of confirming multiple-phenomena causal pathways. Our extension of SLB’s account complements existing philosophical work on experimentation in neurobiology. (shrink)

Neurobiologists talk of linking mind to molecular dynamics in and between neurons. Such talk is dismissed by cognitive scientists, including many cognitive neuroscientists, due to the number of “levels” that separate behaviors from these molecular events. In this paper I explain what neurobiologists mean by such claims by describing the kinds of experiment tools that have forged these linkages, directly on lab benches. I here focus on one of these tools, gene targeting techniques, brought into behavioral neuroscience from developmental biology (...) more than a quarter-century ago. Discussion of this tool does more than illuminate these claims by neurobiologists, however. An account of its development shows the doubly dependent role that theory plays in neurobiology. Our best current theories about “how the brain works” depend entirely on the experiment tools neuroscientists have available. And these tools get developed via the solution of engineering problems, not the application of theory. Theory is thus of tertiary importance in neuroscience, not of the primary importance that many cognitive scientists assume it to occupy. (shrink)

The Hard Problem is surrounded by a vast literature, to which it is increasingly hard to contribute to in any meaningful way. Accordingly, the strategy here is not to offer any new metaphysical or ‘in principle’ arguments in favour of the success of materialism, but to assume a Type Q(uinian) approach and look to contemporary consciousness science to see how the concept of consciousness fares there, and what kind of explanations we can hope to offer of it. It is suggested (...) that while they will be materialist explanations, they will not be of the form that many scientists and philosophers would have us believe, but instead prompt a very different set of expectations and research projects. (shrink)

Over the past three decades, philosophy of science has grown increasingly “local.” Concerns have switched from general features of scientific practice to concepts, issues, and puzzles specific to particular disciplines. Philosophy of neuroscience is a natural result. This emerging area was also spurred by remarkable recent growth in the neurosciences. Cognitive and computational neuroscience continues to encroach upon issues traditionally addressed within the humanities, including the nature of consciousness, action, knowledge, and normativity. Empirical discoveries about brain structure and function suggest (...) ways that “naturalistic” programs might develop in detail, beyond the abstract philosophical considerations in their favor. -/- The literature distinguishes “philosophy of neuroscience” and “neurophilosophy.” The former concerns foundational issues within the neurosciences. The latter concerns application of neuroscientific concepts to traditional philosophical questions. Exploring various concepts of representation employed in neuroscientific theories is an example of the former. Examining implications of neurological syndromes for the concept of a unified self is an example of the latter. In this entry, we will assume this distinction and discuss examples of both. (shrink)

Although researchers in psychiatry have been trying for decades to elucidate the pathophysiology underlying mental disorders, relatively little progress has been made. One explanation for this failure is that diagnostic categories in psychiatry are unlikely to track underlying neurological mechanisms. Because of this, the US National Institutes of Mental Health has recently developed a novel ontology to guide research in biological psychiatry: the Research Domain Criteria. In this paper, I argue that while RDoC may lead to better neuroscientific explanations for (...) mental disorders, it is unlikely that this new knowledge will then lead to an improved diagnostic system. I therefore suggest that researchers in psychiatry should work toward the development of two new ontologies: one for research and one for clinical practice. (shrink)

The sceptical positions philosophers have adopted with respect to neuroimaging data are based on detailed evaluations of subtraction, which is one of many data analysis techniques used with neuroimaging data. These positions are undermined when the epistemic implications of the use of a diversity of data analysis techniques are taken into account. I argue that different data analysis techniques reveal different patterns in the data. Through the use of multiple data analysis techniques, researchers can produce results that are locally robust. (...) Thus, the epistemology of neuroimaging must take into consideration the details of the different data analysis techniques that are used to evaluate neuroimaging data, and the specific theoretical aims those techniques are deployed towards. _1_ Introduction _2_ Scepticism about Neuroimaging _3_ Data Analysis and Evidence _4_ Deconvolution and Pattern Classification Analysis _4.1_ Deconvolution analysis _4.2_ Region of interest selection _4.3_ Pattern classification analysis _5_ The Strength of Multiple Analyses _6_ Conclusion. (shrink)

Experiments in cognitive neuroscience build a setup whose set of controlled stimuli and rules elicits a cognitive process in a participant. This setup requires researchers to decide the value of quite a few parameters along several dimensions. We call ‘’contextual factors’’ the parameters often assumed not to change the cognitive process elicited and are free to vary across the experiment’s repetitions. Against this assumption, empirical evidence shows that many of these contextual factors can significantly influence cognitive performance. Nevertheless, it is (...) not entirely clear what it means for a cognitive phenomenon to be context-sensitive and how to identify context-sensitivity experimentally. We claim that a phenomenon can be context-sensitive either because it is only triggered within a specific context or because different contexts change its manifestation conditions. Assessing which of these forms of context-sensitivity is present in a given phenomenon requires a criterion for individuating it across contextual variations. We argue that some inter-level experiments that, within the mechanistic approach to explanation, are required to identify relations of constitutive relevance between a phenomenon and a mechanism, are also necessary for individuating the phenomenon across its contextual variations. We articulate a criterion according to which behavioral variations across contexts indicate different phenomena if and only if the mechanistic activities, components and/or organizational properties recruited in each context are different. We support this approach by showing how it is applied in paradigmatic studies addressing cognitive performance differences resulting from contextual variations of task features, such as stimulus type and response modality. Finally, we address the challenge that a form of context-sensitivity possessed by the so-called ‘multifunctional mechanisms’ is incompatible with our proposal because it entails that the same mechanism can be recruited in different contexts to produce different phenomena. We examine key cases of multifunctionality and argue that they are consistent with our proposal because a single mechanism can have different components, activities and/or organizational properties in different contexts. Thus, these modifications may not affect the identity of a mechanism, and they could explain how it produced different phenomena in those contexts. (shrink)

Crime is a serious social problem, but its causes are not exclusively social. There is growing consensus that explaining and preventing it requires interdisciplinary research efforts. Indeed, the landscape of contemporary criminology includes a variety of theoretical models that incorporate psychological, biological and sociological factors. These multi-disciplinary approaches, however, have yet to radically advance scientific understandings of crime and shed light on how to manage it. In this paper, using conceptual tools on offer in the philosophy of science in combination (...) with theoretical work represented in this special volume of Psychology, Crime and Law, I provide some perspective on why explanatory progress in criminology has remained elusive and evaluate some positive proposals for attaining it. -/- . (shrink)

Changes in synaptic strength are described as a unifying hypothesis for memory formation and storage, leading philosophers to consider the ‘synaptic efficacy hypothesis’ as a paradigmatic explanation in neuroscience. Craver’s mosaic view has been influential in understanding synaptic efficacy by presenting long-term potentiation as a multi-level mechanism nested within a multi-level structure. This paper argues that the mosaic view fails to fully capture the explanatory power of the synaptic efficacy hypothesis due to assumptions about multi-level mechanisms. I present an alternative (...) approach that emphasizes the explanatory function of unification, accounting for the widespread consensus in neuroscience regarding synaptic efficacy by highlighting the stability of synaptic causal variables across different multi-level mechanisms. (shrink)

This paper responds to a recent challenge for the validity of extrapolation of neurobiological knowledge from laboratory animals to humans. According to this challenge, experimental neurobiology, and thus neuroscience, is in a state of crisis because the knowledge produced in different laboratories hardly generalizes from one laboratory to another. Presumably, this is so because neurobiological laboratories use simplified animal models of human conditions that differ across laboratories. By contrast, I argue that maintaining a multiplicity of experimental protocols and simple models (...) is well justified. It fosters rather than precludes the validity of extrapolation of neurobiological knowledge. The discipline is thriving. (shrink)

In recent debates about the replication crisis, two positions have been dominant: one that focuses on methodological reforms and one that focuses on theory building. This paper takes up the suggestion that there might be a deeper difference in play, concerning the ways the very subject matter of psychology is construed by opposing camps, i.e., in terms of stable effects versus in terms of complexity. I argue that each gets something right, but neither is sufficient. My analysis suggests that the (...) context sensitivity of the psychological subject matter needs to be front and center of methodological and theoretical efforts. (shrink)

The study of psychological mechanisms is an interdisciplinary endeavour, requiring insights from many different domains. In this article, I argue that philosophy plays an essential role in this interdisciplinary project, and that effective scientific study of psychological mechanisms requires that working scientists be responsible metaphysicians. This means adopting deliberate metaphysical positions when studying mechanisms that go beyond what is empirically justified regarding the nature of the phenomenon being studied, the conditions of its occurrence, and its boundaries. Such metaphysical commitments are (...) necessary in order to set up experimental protocols, determine which variables to manipulate under experimental conditions, and which conclusions to draw from different scientific models and theories. It is important for scientists to be aware of the metaphysical commitments they adopt, since they can easily be led astray if invoked carelessly. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

The debate between the defenders of explanatory unification and explanatory pluralism has been ongoing from the beginning of cognitive science and is one of the central themes of its philosophy. Does cognitive science need a grand unifying theory? Should explanatory pluralism be embraced instead? Or maybe local integrative efforts are needed? What are the advantages of explanatory unification as compared to the benefits of explanatory pluralism? These questions, among others, are addressed in this Synthese’s special issue. In the introductory paper, (...) we discuss the background of the questions, distinguishing integrative theorizing from building unified theories. On the one hand, integrative efforts involve collaboration between various disciplines, fields, approaches, or theories. These efforts could even be quite temporary, without establishing any long-term institutionalized fields or disciplines, but could also contribute to developing new interfield theories. On the other hand, unification can rely on developing complete theories of mechanisms and representations underlying all cognition, as Newell’s “unified theories of cognition”, or may appeal to grand principles, as predictive coding. Here, we also show that unification in contemporary cognitive science goes beyond reductive unity, and may involve various forms of joint efforts and division of explanatory labor. This conclusion is one of the themes present in the content of contributions constituting the special issue. (shrink)

The claims that “The brain processes information” or “Cognition is information processing” are accepted as truisms in cognitive science. However, it is unclear how to evaluate such claims absent a specification of “information” as it is used by neurocognitive theories. The aim of this article is, thus, to identify the key features of information that information-based neurocognitive theories posit. A systematic identification of these features can reveal the explanatory role that information plays in specific neurocognitive theories, and can, therefore, be (...) both theoretically and practically important. These features can be used, in turn, as desiderata against which candidate theories of information may be evaluated. After discussing some characteristics of explanation in cognitive science and their implications for “information”, three notions are briefly introduced: natural, sensory, and endogenous information. Subsequently, six desiderata are identified and defended based on cognitive scientific practices. The global workspace theory of consciousness is then used as a specific case study that arguably posits either five or six corresponding features of information. (shrink)

The article advances a new way of thinking about classifications in general and the classification of mental disorders in particular. By applying insights from measurement practice to the context of classification, I defend a notion of epistemic accuracy that allows one to evaluate and improve classifications by comparing different classifying methods to each other. Progress in classification arises from the mutual development of classification systems and classifying methods. Based on this notion of accuracy, the article illustrates with an example how (...) psychiatric classifications can be improved via circumscribed comparisons of different perspectives on mental disorders, without relying on complete models of their complex aetiology. When applying this strategy, the traditional opposition between symptom-based and causal approaches is of little consequence for making progress in the epistemic accuracy of psychiatric classification. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation (LTP). I argue that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds.

Research devoted to characterizing phenomena is underappreciated in philosophical accounts of scientific inquiry. This paper develops a diachronic analysis of research over 100 years that led to the recognition of two related electrophysiological phenomena, the membrane potential and the action potential. A diachronic perspective allows for reconciliation of two threads in philosophical discussions of phenomena—Hacking’s treatment of phenomena as manifest in laboratory settings and Bogen and Woodward’s construal of phenomena as regularities in the world. The diachronic analysis also reveals the (...) epistemic tasks that contribute to establishing phenomena, including the development of appropriate investigative techniques and concepts for characterizing them. (shrink)

Cognitive science has been beset for thirty years by foundational disputes about the nature and extension of cognition—e.g. whether cognition is necessarily representational, whether cognitive processes extend outside the brain or body, and whether plants or microbes have them. Whereas previous philosophical work aimed to settle these disputes, I aim to understand what conception of cognition scientists could share given that they disagree so fundamentally. To this end, I develop a number of variations on traditional conceptual explication, and defend a (...) novel explication of cognition called the sensitive management hypothesis. -/- Since expert judgments about the extension of “cognition” vary so much, I argue that there is value in explication that accurately models the variance in judgments rather than taking sides or treating that variance as noise. I say of explications that accomplish this that they are ecumenically extensionally adequate. Thus, rather than adjudicating whether, say, plants can have cognitive processes like humans, an ecumenically adequate explication should classify these cases differently: human cognitive processes as paradigmatically cognitive, and plant processes as controversially cognitive. -/- I achieve ecumenical adequacy by articulating conceptual explications with parameters, or terms that can be assigned a number of distinct interpretations based on the background commitments of participants in a discourse. For example, an explication might require that cognition cause “behavior,” and imply that plant processes are cognitive or not depending on whether anything plants do can be considered “behavior.” Parameterization provides a unified treatment of embattled concepts by isolating topics of disagreement in a small number of parameters. -/- I incorporate these innovations into an account on which cognition is the “sensitive management of organismal behavior.” The sensitive management hypothesis is ecumenically extensionally adequate, accurately classifying a broad variety of cases as paradigmatically or controversially cognitive phenomena. I also describe an extremely permissive version of the sensitive management hypothesis, arguing that it has the potential to explain several features of cognitive scientific discourse, including various facts about the way cognitive scientists ascribe representations to cognitive systems. (shrink)

In this article, I show the role that the philosopher of cognitive science can cur-rently play in cognitive science research. I argue for the important, and not yet considered, role of the philosophy of cognitive science in cognitive science, that is, the importance of cooperation between philosophers of science with cogni-tive scientists in investigating the research methods and theoretical assump-tions of cognitive science. At the beginning of the paper I point out, how the philosopher of science, here, the philosopher of (...) cognitive science, can participate in interdisciplinary research. I am opting of the cooperation in investigating the so-called reflective problems. Then, I discuss four examples of issues important for the cognitive science, in which the competences possessed by the philosopher are useful. At the ending I point out wider landscape of possible cooperation of philosophers with cognitive scientists. (shrink)

The use of neuroscientific evidence in criminal trials has been steadily increasing. Despite progress made in recent decades in understanding the mechanisms of psychological and behavioral functioning, neuroscience is still in an early stage of development and its potential for influencing legal decision-making is highly contentious. Scholars disagree about whether or how neuroscientific evidence might impact prescriptions of criminal culpability, particularly in instances in which evidence of an accused’s history of mental illness or brain abnormality is offered to support a (...) plea of not criminally responsible. In the context of these debates, philosophers and legal scholars have identified numerous problems with admitting neuroscientific evidence in legal contexts. To date, however, less has been said about the challenges of evaluating the evidence upon which integrative mechanistic explanations that bring together evidence from different areas of neuroscience are based. As we explain, current criteria for evaluating such evidence to determine its admissibility in legal contexts are inadequate. Appealing to literature in the philosophy of scientific experimentation and theoretical work in the social, cognitive and behavioral sciences, we lay the groundwork for reforming these criteria and identify some of the implications of modifying them. (shrink)