Scientists aim to remediate artifacts in their experimental datasets. However, the remediation of one artifact can result in another. Why might this happen, and what does this consequence tell us about how we should account for artifacts and their control? In this paper, I explore a case in functional neuroimaging where remediation appears to have caused this problem. I argue that remediation amounts to a change to an experimental arrangement. These changes need not be surgical, and the arrangement need not (...) satisfy the criterion of causal modularity. Thus, remediation can affect more than just the factor responsible for the artifact. However, if researchers can determine the consequences of their remediation, they can make adjustments that control for the present artifact as well as for previously controlled ones. Current philosophical accounts of artifacts and the factors responsible for them cannot adequately address this issue, as they do not account for what is needed for artifact remediation (and specifically correction). I support my argument by paralleling it with ongoing concerns regarding the transparency of complex computational systems, as near future remediation across the experimental life sciences will likely make greater use of AI tools to correct for artifacts. (shrink)

This paper accounts for broad definitions of memory, which extend to paradigmatic memory phenomena, like episodic memory in humans, and phenomena in worms and sea snails. These definitions may seem too broad, suggesting that they extend to phenomena that don’t count as memory or illustrate that memory is not a natural kind. However, these responses fail to consider a definition as a hypothesis. As opposed to construing definitions as expressing memory’s properties, a definition as a hypothesis is the basis to (...) test inferences about phenomena. A definition as a hypothesis is valuable when the “kinding” of phenomena is ongoing. (shrink)

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

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)

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)

Scientists often respond to failures to replicate by citing differences between the experimental components of an original study and those of its attempted replication. In this paper, we investigate these purported mismatch explanations. We assess a body of failures to replicate in neuroscience studies on spinal cord injury. We argue that a defensible mismatch explanation is one where a mismatch of components is a difference maker for a mismatch of outcomes, and the components are relevantly different in the follow-up study, (...) given the scope of the original study. With this account, we argue that not all differences between studies are meaningful, even if they are difference makers. As our examples show, focusing only on these differences results in disregarding the representativeness of the original experiment’s components and the scope of its outcomes, undercutting other epistemic aims, such as translation, in the process. (shrink)

I focus on the concept of the receptive field of a sensory neuron, taking it as a prominent case to address conceptual change in the history of neuroscience. I argue for an interpretation of its ro...

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)

A number of biologists and philosophers have noted the diversity of interpretations of evolvability in contemporary evolutionary research. Different clusters of research defined by co-citation patterns or shared methodological orientation sometimes concentrate on distinct conceptions of evolvability. We examine five different activities where the notion of evolvability plays conceptual roles in evolutionary biological investigation: setting a research agenda, characterization, explanation, prediction, and control. Our analysis of representative examples demonstrates how different conceptual roles of evolvability are quasi-independent and yet exhibit important (...) relationships across scientific activities. It also provides us with the resources to detail two distinct strategies for how evolvability can help to synthesize disparate areas of research and thereby potentially serve as a unifying concept in evolutionary biology. (shrink)