Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models (...) are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...) that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms. (shrink)

In this paper, an account of theoretical integration in cognitive (neuro)science from the mechanistic perspective is defended. It is argued that mechanistic patterns of integration can be better understood in terms of constraints on representations of mechanisms, not just on the space of possible mechanisms, as previous accounts of integration had it. This way, integration can be analyzed in more detail with the help of constraintsatisfaction account of coherence between scientific representations. In particular, the account has resources to talk of (...) idealizations and research heuristics employed by researchers to combine separate results and theoretical frameworks. The account is subsequently applied to an example of successful integration in the research on hippocampus and memory, and to a failure of integration in the research on mirror neurons as purportedly explanatory of sexual orientation. (shrink)

Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...) computability theory), (ii) a technique that inspired the notion of logic design (a fundamental part of modern computer design), (iii) the first use of computation to address the mind–body problem, and (iv) the first modern computational theory of mind and brain. (shrink)

What kinds of norms constrain mechanistic discovery and explanation? In the mechanistic literature, the norms for good explanations are directly derived from answers to the metaphysical question of what explanations are. Prominent mechanistic accounts thus emphasize either ontic or epistemic norms. Still, mechanistic philosophers on both sides agree that there is no sharp distinction between the processes of discovery and explanation. Thus, it seems reasonable to expect that ontic and epistemic accounts of explanation will be accompanied by ontic and epistemic (...) accounts of discovery, respectively. As we will show here, however, recent discovery accounts implicitly rely on both ontic and epistemic norms to characterize the discovery process. In this paper, we develop an account that makes explicit that, and how, ontic and epistemic norms work together throughout the discovery process. By describing mechanism discovery as a process of pattern recognition we demonstrate that scientists have to develop epistemic activities to distinguish a pattern from its background. Furthermore, they have to determine which epistemic activities successfully describe how the pattern is implemented by identifying the pattern’s components. Our approach reveals that ontic and epistemic norms are equally important in mechanism discovery. (shrink)

This paper proposes an analysis of the discursive dynamics of high-impact concepts in the humanities. These are concepts whose formation and development have a lasting and wide-ranging effect on research and our understanding of discursive reality in general. The notion of a conceptual practice, based on a normative conception of practice, is introduced, and practices are identified, on this perspective, according to the way their respective performances are held mutually accountable. This normative conception of practices is then combined with recent (...) work from philosophy of science that characterizes concepts in terms of conceptual capacities that are productive, open-ended, and applicable beyond the original context they were developed in. It is shown that the formation of concepts can be identified by changes in how practitioners hold exercise of their conceptual capacities accountable when producing knowledge about a phenomenon. In a manner similar to the use of operational definitions in scientific practices, such concepts can also be used to intervene in various discourses within or outside the conceptual practice. Using the formation of the concepts “mechanism” and “performative” as examples, the paper shows how high-impact concepts reconfigure what is at issue and at stake in conceptual practices. As philosophy and other humanities disciplines are its domain of interest, it is a contribution to the methodology of the humanities. (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)

Memory trace was originally a philosophical term used to explain the phenomenon of remembering. Once debated by Plato, Aristotle, and Zeno of Citium, the notion seems more recently to have become the exclusive province of cognitive psychologists and neuroscientists. Nonetheless, this modern appropriation should not deter philosophers from thinking carefully about the nature of memory traces. On the contrary, scientific research on the nature of memory traces can rekindle philosopher's interest on this notion. With that general aim in mind, the (...) present paper has three specific goals. First, it attempts to chart the most relevant philosophical views on the nature of memory traces from both a thematic and historical perspective. Second, it reviews critical findings in the psychology and the neuroscience of memory traces. Finally, it explains how such results lend support to or discredit specific philosophical positions on the nature of memory traces. This paper also touches upon the issues raised by recent empirical research that theories of memory traces need to accommodate in order to succeed. (shrink)

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

A core, constitutive norm of science is to remove or remedy the artefacts in one’s data. Here, we consider examples of artefacts from many fields of science (for example, astronomy, economics, electrophysiology, psychology, and systems neuroscience) and discuss their contribution to a more general evidential selection problem at the heart of the epistemology of evidence. Synthesizing and building on previously disparate discussions in many areas of the philosophy of science, we provide a novel, causal–pragmatic account that fits the examples and (...) clarifies the practices by which artefacts are discovered and remedied. (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)

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

Philosophers of neuroscience have traditionally described interfield integration using reduction models. Such models describe formal inferential relations between theories at different levels. I argue against reduction and for a mechanistic model of interfield integration. According to the mechanistic model, different fields integrate their research by adding constraints on a multilevel description of a mechanism. Mechanistic integration may occur at a given level or in the effort to build a theory that oscillates among several levels. I develop this alternative model using (...) a putative exemplar of reduction in contemporary neuroscience: the relationship between the psychological phenomena of learning and memory and the electrophysiological phenomenon known as Long-Term Potentiation. A new look at this historical episode reveals the relative virtues of the mechanistic model over reduction as an account of interfield integration. (shrink)

As opposed to the dismissive attitude toward reductionism that is popular in current philosophy of mind, a “ruthless reductionism” is alive and thriving in “molecular and cellular cognition”—a field of research within cellular and molecular neuroscience, the current mainstream of the discipline. Basic experimental practices and emerging results from this field imply that two common assertions by philosophers and cognitive scientists are false: (1) that we do not know much about how the brain works, and (2) that lower-level neuroscience cannot (...) explain cognition and complex behavior directly. These experimental practices involve intervening directly with molecular components of sub-cellular and gene expression pathways in neurons and then measuring specific behaviors. These behaviors are tracked using tests that are widely accepted by experimental psychologists to study the psychological phenomenon at issue (e.g., memory, attention, and perception). Here I illustrate these practices and their importance for explanation and reduction in current mainstream neuroscience by describing recent work on social recognition memory in mammals. (shrink)

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving (...) research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts. (shrink)

Prominent research programs dealing with the nature and mechanisms of interpersonal social coordination have emerged in cognitive science, developmental psychology and evolutionary anthropology. I argue that the mechanistic approach to explanation in contemporary philosophy of science can facilitate interdisciplinary integration and division of labor between these different disciplinary research programs. By distinguishing phenomenal models from mechanistic models and structural decomposition from functional decomposition in the process of mechanism discovery, I argue that behavioral and cognitive scientists can make interlocking contributions to (...) families of mechanism models representing a) what central forms of interpersonal social coordination consist in, b) what types of agents engage in such forms of coordination, c) what types of cognitive mechanisms give rise to such forms of coordination, d) how the operation of such mechanisms is modulated by the natural and social environments that the agents populate. Thus mechanistic philosophy of science can play a heuristic role in guiding the research strategies of scientists in different scientific disciplines in a manner that is complementary to the research strategies of scientists in other disciplines and thereby efficient from the point of view of the division of epistemic labor. (shrink)

One reason for the popularity of Craver’s mutual manipulability account of constitutive relevance is that it seems to make good sense of the experimental practices and constitutive reasoning in the life sciences. Two recent papers propose a theoretical alternative to in light of several important conceptual objections. Their alternative approach, the no de-coupling account, conceives of constitution as a dependence relation that once postulated provides the best explanation of the impossibility of breaking the common cause coupling of a macro-level mechanism (...) and its micro-level components. This entails an abductive view of constitutive inference. Proponents of the NDC or abductive account recognize that their discussion leaves open a big question concerning the practical dimension of the notion of constitutive relevanssssce: Is it possible to faithfully reconstruct constitutional reasoning in science in terms of a failure to de-couple, via interlevel experiments, phenomena from their mechanistic constituents? Focusing on the field of memory and long-term potential research, this article argues that the abductive account provides a more adequate description of interlevel experiments in neuroscience. We also suggest that the account highlights some significant practical recommendations of how to interpret the findings of interlevel experiments. 1Introduction 2Mutual Manipulability and Constitutive Relevance 2.1Constitutive relevance through an interventionist lens 2.2Mutual manipulability: A methodological application 3Trouble for the Mutual Manipulability Account 4The Abductive Account of Constitution 5The Abductive Account: A Methodological Application 5.1Long-term potential and memory experiments 5.2A comparative summary 6Conclusions. (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.

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)

From its genesis in the 1960s, the focus of inquiry in neuroscience has been on the cellular and molecular processes underlying neural activity. In this pursuit neuroscience has been enormously successful. Like any successful scientific inquiry, initial successes have raised new questions that inspire ongoing research. While there is still much that is not known about the molecular processes in brains, a great deal of very important knowledge has been secured, especially in the last 50 years. It has also attracted (...) the attention of a number of philosophers, some of whom have viewed it as evidence for a ruthlessly reductionistic program that will eventually explain how mental processes are performed in the brain in purely molecular terms. As neuroscience developed, however, there emerged a smaller group of researchers who focused on systems, behavioral, and cognitive neuroscience. These investigators have also made impressive advances in the last 50 years and they have been the focus of an even larger group of philosophers, who have appealed to systems level understanding of the brain as providing the appropriate point of connection to the information processing accounts advanced in psychology. (shrink)

Felix reaches up to catch a high line drive to left field and fires the ball off to Benji at home plate, who then tags the runner trying to score. For Felix to catch the ball and transfer it from his glove to his throwing hand, he needs to have a sense of where his hands are relative to one another and the rest of his body. This sort of information is subconsciously tracked in the body schema (or postural schema), (...) a representation of the current bodily posture that is updated on the basis of proprioceptive inputs. While the existence of the body schema in not in dispute, its origin is. After reviewing the competing proposals, I introduce the conceptual tools needed to move the debate forward and apply them to the question of the extent to which the body schema could be learned from perceptual input in utero. I argue that it could give rise to something recognizable as the body schema, though not quite rising to the level of the mature body schema. After considering the implications for further research on the origins of the body schema, I show how these results apply to other body representations, helping clarify the vexing question of the number, nature, and interactions among body representations in the brain. This theoretical work also promises to advance our understanding and treatment protocols for disorders affecting such body representations (e.g., anorexia nervosa). (shrink)

The idea that remembering involves an engram, becoming stable and permanent via consolidation, has guided the neuroscience of memory since its inception. The shift to thinking of memory as continuo...