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)

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)

This paper examines the phenomenon of ‘interactive kinds’ first identified by Ian Hacking. An interactive kind is one that is created or significantly modified once a concept of it has been formulated and acted upon in certain ways. Interactive kinds may also ‘loop back’ to influence our concepts and classifications. According to Hacking, interactive kinds are found exclusively in the human domain. After providing a general account of interactive kinds and outlining their philosophical significance, I argue that they are not (...) confined to the human realm, but that they can also occur elsewhere. Hence, I conclude by arguing that interactive kinds pose a challenge to scientific realism about kinds by making it difficult to make a distinction between real and non-real kinds. (shrink)

A pluralistic view of psychiatric classification is defended, according to which psychiatric categories take a variety of structural forms. An ordered taxonomy of these forms—non-kinds, practical kinds, fuzzy kinds, discrete kinds, and natural kinds—is presented and exemplified. It is argued that psychiatric categories cannot all be understood as pragmatically grounded, and at least some reflect naturally occurring discontinuities without thereby representing natural kinds. Even if essentialist accounts of mental disorders are generally mistaken, they are not implied whenever a psychiatric category (...) that is not pragmatically grounded is posited. (shrink)

Here the distinguished philosopher Ian Hacking uses the MPD epidemic and its links with the contemporary concept of child abuse to scrutinize today's moral...

It is common to defend the Homeostatic Property Cluster ( HPC ) view as a third way between conventionalism and essentialism about natural kinds ( Boyd , 1989, 1991, 1997, 1999; Griffiths , 1997, 1999; Keil , 2003; Kornblith , 1993; Wilson , 1999, 2005; Wilson , Barker , & Brigandt , forthcoming ). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a similarity generating ( (...) or homeostatic ) mechanism . I argue that conventional elements are involved partly but ineliminably in deciding which mechanisms define kinds , for deciding when two mechanisms are mechanisms of the same type, and for deciding where one particular mechanism ends and another begins. This intrusion of conventional perspective into the idea of a mechanism raises doubts as to whether the HPC view is sufficiently free of conventional elements to serve as an objective arbiter in scientific disputes about what the kinds of the special sciences should be. (shrink)

is a term introduced by Ian Hacking to refer to the kinds of people—child abusers, pregnant teenagers, the unemployed—studied by the human sciences. Hacking argues that classifying and describing human kinds results in feedback, which alters the very kinds under study. This feedback results in human kinds having histories totally unlike those of natural kinds (such as gold, electrons and tigers), leading Hacking to conclude that human kinds are radically unlike natural kinds. Here I argue that Hacking's argument fails and (...) that he has not demonstrated that human kinds cannot be natural kinds. Introduction Natural kinds Hacking's feedback mechanisms 3.1 Cultural feedback 3.2 Conceptual feedback. (shrink)

A variety of scientific disciplines have set as their task explaining mental activities, recognizing that in some way these activities depend upon our brain. But, until recently, the opportunities to conduct experiments directly on our brains were limited. As a result, research efforts were split between disciplines such as cognitive psychology, linguistics, and artificial intelligence that investigated behavior, while disciplines such as neuroanatomy, neurophysiology, and genetics experimented on the brains of non-human animals. In recent decades these disciplines integrated, and with (...) the advent of techniques for imaging activity in human brains, the term cognitive neuroscience has been applied to the integrated investigations of mind and brain. This book is a philosophical examination of how these disciplines continue in the mission of explaining our mental capacities. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

William Uttal is concerned that in an effort to prove itself a hard science, psychology may have thrown away one of its most important methodological tools—a critical analysis of the fundamental assumptions that underlie day-to-day empirical research. In this book Uttal addresses the question of localization: whether psychological processes can be defined and isolated in a way that permits them to be associated with particular brain regions. New, noninvasive imaging technologies allow us to observe the brain while it is actively (...) engaged in mental activities. Uttal cautions, however, that the excitement of these new research tools can lead to a neuroreductionist wild goose chase. With more and more cognitive neuroscientific data forthcoming, it becomes critical to question their limitations as well as their potential. Uttal reviews the history of localization theory, presents the difficulties of defining cognitive processes, and examines the conceptual and technical difficulties that should make us cautious about falling victim to what may be a "neo-phrenological" fad. (shrink)

This book offers a philosophy for error-prone humans trying to understand messy systems in the real world.

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.