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)

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.

Driven by an appreciation of the field’s early stage of development, I apply the concept of exploratory experimentation, originally put forward in the late 90s philosophy of biology, to current research in cognitive neuroscience. I concentrate on functional magnetic resonance imaging and how this wide-spread technique is used, from experimental design to data analysis. I claim that, although subject to certain significant modifications with respect to the concept’s original rendering, the exploratory character of neuroimaging experiments can be appreciated considering their (...) goals, centered on the stabilization of experimental systems for phenomenological description, and the relevance of their methodological facet. Although I do not claim that there is a specific kind of experiment that one can single out as definitely exploratory, exploration can be seen as a general trait imbuing fMRI-based experimentation. (shrink)

The discovery of RNA interference in 1998 has made a lasting impact on biological research. Identifying the regulatory role of small RNAs changed the modes of molecular biological inquiry as well as biologists' understanding of genetic regulation. This article examines the early years of small RNA biology's success story. I query which factors had to come together so that small RNA research came into life in the blink of an eye. I primarily look at scientific repertoires as facilitators of rapid (...) scientific change. I show that for a short period of time, between the years 1998 and 2002, different model organism communities, investigative strategies, technological innovations, and research interests could be successfully aligned to take small RNA research off the ground. I discuss how the keystone discoveries were situated in specific experimental traditions and what strategies were employed to establish these discoveries as more general phenomena. Providing thus a practice-based approach of rapid scientific change, I ask how to relate the change in propositional bits of scientific knowledge with changes in scientific practice. (shrink)

One important strategy for dealing with error in our methods is triangulation, or the use multiple methods to investigate the same object. Current accounts of triangulation assume that its primary function is to provide a confirmatory boost to hypotheses beyond what confirmation of each method alone could produce. Yet, researchers often use multiple methods to examine new constructs about which they are uncertain. For example, social psychologists use multiple indirect measures to provide convergent evidence about implicit attitudes, but how to (...) characterize implicit attitudes is an open question. To make sense of triangulation under uncertainty about constructs, I suggest two changes: first, triangulation can serve multiple epistemic functions, including some that are non-confirmatory, and second, researchers should assess the epistemic risk in claims about evidence and the acceptance/rejection of hypotheses. (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)

In recent years, the use of historical cases in philosophy of science has become a proper topic of reflection. In this article I will contribute to this research by means of a discussion of one very famous example of case-based philosophy of science, namely the debate on the London & London model of superconductivity between Cartwright, Suárez and Shomar on the one hand, and French, Ladyman, Bueno and Da Costa on the other. This debate has been going on for years, (...) without any satisfactory resolution. I will argue here that this is because both sides impose on the historical case a particular philosophical conception of scientific representation that does not do justice to the historical facts. Both sides assume, more specifically, that the case concerns the discovery of a representational connection between a given experimental insight – the Meissner effect – and the diamagnetic meaning of London and London’s new equations of superconductivity. I will show, however, that at the time of the Londons’ publication, neither the experimental insight nor the meaning of the new equations was established: both were open for discussion and they were stabilized only later. On the basis of this historical discussion, I will then propose an alternative approach to the case study: the case should not be seen as a site of confrontation between pre-existing philosophical accounts, but rather as a way to historically elaborate and develop philosophical concepts. I will then show how approaching the historical episode in this way suggests an alternative approach to the philosophical study of representation, according to which it involves the establishment, over time, of a stable connection between constellations of different elements that, through discussion and engagement with alternative views and approaches, come to constitute phenomenon and meaning. (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)

Observation and experiment as categories for analysing scientific practice have a long pedigree in writings on science. There has, however, been little attempt to delineate observation and experiment with respect to analysing scientific practice; in particular, scientific experimentation, in a systematic manner. Someone who has presented a systematic account of observation and experiment as categories for analysing scientific experimentation is Ian Hacking. In this paper, I present a detailed analysis of Hacking’s observation versus experiment account. Using a range of cases (...) from various fields of scientific enquiry, I argue that the observation versus experiment account is not an adequate framework for delineating scientific experimentation in a systematic manner. (shrink)

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (shrink)

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (shrink)

This article considers the temporal dimension of data processing and use and the ways in which it affects the production and interpretation of knowledge claims. I start by distinguishing the time at which data collection, dissemination, and analysis occur from the time in which the phenomena for which data serve as evidence operate. Building on the analysis of two examples of data reuse from modeling and experimental practices in biology, I then argue that Dt affects how researchers select and interpret (...) data as evidence and identify and understand phenomena. (shrink)

Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models—acknowledging their status as living beings and as epistemological tools—necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper (...) presents an account of how disease-specific animal models are established by drawing on the example of transgenic mice models for Alzheimer’s disease. We will introduce an account of validation that involves a three-fold process including from human being to experimental organism; from experimental organism to animal model; and from animal model to human patient. This process draws upon clinical relevance as much as scientific practices and results in disease-specific, yet incomplete, animal models. The second part of this paper argues that the incompleteness of models can be described in terms of multi-level abstractions. We qualify this notion by pointing to different experimental techniques and targets of modelling, which give rise to a plurality of models for a specific disease. (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)

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)

It is commonly held that research efforts in the cognitive and behavioral sciences are mainly directed toward providing explanations and that phenomena figure into scientific practice qua explananda. I contend that these assumptions convey a skewed picture of the research practices in question and of the role played by phenomena. I argue that experimental research often aims at exploring and describing “objects of research” and that phenomena can figure as components of, and as evidence for, such objects. I situate my (...) analysis within the existing literature and illustrate it with examples from memory research. (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)

Background Professional communities such as the medical community are acutely concerned with negligence: the category of misconduct where a professional does not live up to the standards expected of a professional of similar qualifications. Since science is currently strengthening its structures of self-regulation in parallel to the professions, this raises the question to what extent the scientific community is concerned with negligence, and if not, whether it should be. By means of comparative analysis of medical and scientific codes of conduct, (...) we aim to highlight the role of negligence provisions in codes of conduct for scientists, and to discuss the normative consequences for future codes of conduct. -/- Methods We collected scientific and medical codes of conduct in a selection of OECD countries, and submitted each code of conduct to comparative textual analysis. -/- Results Negligence is invariably listed as an infraction of the norms of integrity in medical codes of conduct, but only rarely so in the scientific codes. When the latter list negligence, they typically do not provide any detail on the meaning of ‘negligence’. -/- Discussion Unlike codes of conduct for professionals, current codes of conduct for scientists are largely silent on the issue of negligence, or explicitly exclude negligence as a type of misconduct. In the few cases where negligence is stipulated to constitute misconduct, no responsibilities are identified that would help prevent negligence. While we caution against unreasonable negligence provisions as well as disproportionate sanctioning systems, we do argue that negligence provisions are crucial for justified trust in the scientific community, and hence that there is a very strong rationale for including negligence provisions in codes of conduct. (shrink)

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)

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.

The neuron doctrine, according to which nerves consist of discontinuous neurons, presented investigators with the challenge of determining what activities occurred between them or between them and muscles. One group of researchers, dubbed the sparks, viewed the electrical current in one neuron as inducing a current in the next neuron or in muscles. For them there was no gap between the activities of neurons or neurons and muscles that required filling with a new type of activity. A competing group, the (...) soups, came to argue for chemicals, subsequently referred to neurotransmitters, as carrying out the activities between neurons or between neurons and muscles. But even for them the conclusion that chemicals performed this activity was only arrived over time. I examine the prolonged period in which proponents of chemical transmission developed their account and challenged the sparks. My goal is to illuminate the epistemic processes that led to the discovery of a new scientific phenomenon—chemical transmission between neurons. (shrink)

The Galilean explanatory style is characterized by the search for the underlying structure of phenomena, the positing of "deep" explanatory principles, and a view of the relation between theory and data, on which the search for "crucial data" is of primary importance. In this paper, I trace the dynamics of adopting the Galilean style, focusing on the science of episodic memory. I argue that memory systems, such as episodic and semantic memory, were posited as underlying competences producing the observable phenomena (...) of memory. Considered in idealized isolation from other systems, episodic memory was taken to underlay the ability of individuals to remember events from their personal past. Yet, in reality, memory systems regularly interact, standing in many-to-many relations to actual memory tasks and experiences. Upon this backdrop, I explore a puzzle about the increasing prominence of the notion of autonoetic consciousness in Tulving's theory of episodic memory. I argue that, contrary to widespread belief, the prominence is not best explained by the purported essential link between autonoetic consciousness and episodic memory. Rather, it is explained by the fact that autonoetic consciousness, hypothesized to uniquely accompany episodic retrieval, was considered a source of crucial data, predictable only from theories positing a functionally distinct episodic memory system. However, with the emergence of a new generation of theories, positing wider memory systems for remembering and imagination, the question of the relation between episodic memory and autonoetic consciousness has been reopened. This creates a pressing need for de-idealization, triggering a new search for crucial data. (shrink)

Philosophers of science have recently begun to pay more attention to scientific practice, moving away from the discipline’s focus on theories. The creation of the Society for Philosophy of Science in Practice in 2006, as well as the emergence of scholarship on experimental practice (e.g. Sullivan 2009; 2010; 2016) as well as on the tools scientists use to construct explanations and theories (e.g. Feest 2011) all point to a disciplinary shift towards a more practice-conscious philosophy of science. In addition, scholars (...) are realizing the potential social relevance of philosophy of science and identifying the obstacles that stand in the way of realizing said potential (e.g. Douglas 2010). The aim of this dissertation is to propose a novel descriptive framework for philosophy of science, one that rests on the idea that scientific practice should be described as accurately as possible so that philosophical discussions of science rest on a solid descriptive base and can more easily be of use in engaging users and practitioners of science. The dissertation is organized along the stages of developing what I call the dynamic-iterative model of scientific practice. In chapter 1, I clarify the project’s philosophical background and outline six conditions of adequacy on a descriptive model of science. These conditions allow me to evaluate the three descriptive models reviewed in chapter 2. Chapter 3 combines Nickles’ problem-solving view of science (1981) with core insights from the heuristics and biases literature into a workable version of the dynamic-iterative model. I then apply the model to the case of place cell research in chapter 4 as a test of the model’s usefulness and applicability. In chapter 5 I evaluate the model with respect to my six conditions and assess its strengths and weaknesses. The dynamic-iterative model is a flexible descriptive framework that not only allows for more complete philosophical analyses of cases than other current models, but also supports important practical applications. (shrink)

This paper argues that many of the conceptual controversies in evolutionary biology are due to the use of different operational definitions. Since the set of operations is not consistent, then there are many ways to understand, in practice, how concepts should be investigated. In this paper we introduce a formal analysis to study the scope of operationalism and we conclude that the controversial concepts are in fact umbrella variables, that is, a single term can be referring to different processes, phenomena (...) or entities linked by a large ontological commitment driving operationalism. If this is correct, then many of the controversies in evolutionary biology are due, in part, to the operationalization of the objects of study. (shrink)

in a nervous system of a given species. This chapter provides a critical perspective on the role of connectomes in neuroscientific practice and asks how the connectomic approach fits into a larger context in which network thinking permeates technology, infrastructure, social life, and the economy. In the first part of this chapter, we argue that, seen from the perspective of ongoing research, the notion of connectomes as “complete descriptions” is misguided. Our argument combines Rachel Ankeny’s analysis of neuroanatomical wiring diagrams (...) as “descriptive models” with Hans-Joerg Rheinberger’s notion of “epistemic objects,” i.e., targets of research that are still partially unknown. Combining these aspects we conclude that connectomes are constitutively epistemic objects: there just is no way to turn them into permanent and complete technical standards because the possibilities to map connection properties under different modeling assumptions are potentially inexhaustible. In the second part of the chapter, we use this understanding of connectomes as constitutively epistemic objects in order to critically assess the historical and political dimensions of current neuroscientific research. We argue that connectomics shows how the notion of the “brain as a network” has become the dominant metaphor of contemporary brain research. We further point out that this metaphor shares (potentially problematic) affinities to the form of contemporary “network societies.” We close by pointing out how the relation between connectomes and networks in society could be used in a more fruitful manner. (shrink)

In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...) relevant to robustness analysis. I close by briefly outlining a promising alternative approach inspired by Horwich’s (1982) eliminative account of evidential diversity. (shrink)

In the face of causal complexity, scientists reconstitute phenomena in order to arrive at a more simplified and partial picture that ignores most of the 'bigger picture.' This paper will distinguish between two modes of reconstituting phenomena: one moving down to a level of greater decomposition (toward organizational parts of the original phenomenon), and one moving up to a level of greater abstraction (toward different differences regarding the phenomenon). The first aim of the paper is to illustrate that phenomena are (...) moving targets, i.e., they are not fixed once and for all, but are adapted, if necessary, on the basis of the preferred perspective adopted for pragmatic reasons. The second aim is to analyze in detail the second mode of reconstituting phenomena. This includes an exposition of the kind of pragmatic-pluralistic picture resulting from the fact that phenomena are reconstituted by a move up to a level of greater abstraction. (shrink)

Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...) in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)

At the beginning of the 20th century, Gestalt psychologists put forward the concept of psychoneural isomorphism, which was meant to replace Fechner’s obscure notion of psychophysical parallelism and provide a heuristics that may facilitate the search for the neural correlates of the mind. However, the concept has generated much confusion in the debate, and today its role is still unclear. In this contribution, I will attempt a little conceptual spadework in clarifying the concept of psychoneural isomorphism, focusing exclusively on conscious (...) visual perceptual experience and its neural correlates. Firstly, I will outline the history of our concept, and its alleged metaphysical and epistemic roles. Then, I will clarify the nature of isomorphism and rule out its metaphysical role. Finally, I will review some epistemic roles of our concept, zooming in on the work of Jean Petitot, and suggest that it does not play a relevant heuristic role. I conclude suggesting that psychoneural isomorphism might be an indicator of robustness for certain mathematical descriptions of perceptual content. (shrink)

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation. But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim that, in experimentation, no less than (...) in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)