Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...) find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up —situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. (shrink)

Naturalism as a guiding philosophy for modern science both disavows any appeal to the supernatural or anything else transcendent to nature, and repudiates any philosophical or religious authority over the workings and conclusions of the sciences. A longstanding paradox within naturalism, however, has been the status of scientific knowledge itself, which seems, at first glance, to be something that transcends and is therefore impossible to conceptualize within scientific naturalism itself. In Articulating the World, Joseph Rouse argues that the most pressing (...) challenge for advocates of naturalism today is precisely this: to understand how to make sense of a scientific conception of nature as itself part of nature, scientifically understood. Drawing upon recent developments in evolutionary biology and the philosophy of science, Rouse defends naturalism in response to this challenge by revising both how we understand our scientific conception of the world and how we situate ourselves within it. (shrink)

Mark Wilson presents a highly original and broad-ranging investigation of the way we get to grips with the world conceptually, and the way that philosophical problems commonly arise from this. He combines traditional philosophical concerns about human conceptual thinking with illuminating data derived from a large variety of fields including physics and applied mathematics, cognitive psychology, and linguistics. Wandering Significance offers abundant new insights and perspectives for philosophers of language, mind, and science, and will also reward the interest of psychologists, (...) linguists, and anyone curious about the mysterious ways in which useful language obtains its practical applicability. (shrink)

Starting with some illustrative examples, I develop a systematic account of a specific type of experimentation--an experimentation which is not, as in the "standard view", driven by specific theories. It is typically practiced in periods in which no theory or--even more fundamentally--no conceptual framework is readily available. I call it exploratory experimentation and I explicate its systematic guidelines. From the historical examples I argue furthermore that exploratory experimentation may have an immense, but hitherto widely neglected, epistemic significance.

This lucidly written book examines the social and political significance of the natural sciences through a detailed and original account of science as an interpretive social practice.

In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of the last three decades measured differences in brain activity that are thought to reflect the exercise of human mental capacities (e.g., perception, attention, memory). With the advancement of resting state studies, tractography and graph theory in the last decade, however, it became possible to study human brain connectivity without relying on cognitive tasks or constructs. It (...) therefore is currently an open question whether the assumption that “the mind is what the brain does” is an indispensable working hypothesis in human brain mapping. This paper argues that the hypothesis is, in fact, dispensable. If it is dropped, researchers can “meet the brain on its own terms” by searching for new, more adequate concepts to describe human brain organization. Neuroscientists can establish such concepts by conducting exploratory experiments that do not test particular cognitive hypotheses. The paper provides a systematic account of exploratory neuroscientific research that would allow researchers to form new concepts and formulate general principles of brain connectivity, and to combine connectivity studies with manipulation methods to identify neural entities in the brain. These research strategies would be most fruitful if applied to the mesoscopic scale of neuronal assemblies, since the organizational principles at this scale are currently largely unknown. This could help researchers to link microscopic and macroscopic evidence to provide a more comprehensive understanding of the human brain. The paper concludes by comparing this account of exploratory neuroscientific experiments to recent proposals for large-scale, discovery-based studies of human brain connectivity. (shrink)

At his death in 2010, the Anglo-American analytic philosopher John Haugeland left an unfinished manuscript summarizing his life-long engagement with Heidegger’s Being and Time. As illuminating as it is iconoclastic, Dasein Disclosed is not just Haugeland’s Heidegger—this sweeping reevaluation is a major contribution to philosophy in its own right.

This article examines how scientists move from physical measurementsto actual observation of single-cell recordings in the brain. We highlight how easy it is to change the fundamental nature of ourobservations using accepted methodological techniques for manipulatingraw data. Collecting single-cell data is thoroughly pragmatic. Weconclude that there is no deep or interesting difference betweenaccounting for observations by measurements and accounting forobservations by theories.

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

Philosophers of science turned to historical case studies in part in response to Thomas Kuhn's insistence that such studies can transform the philosophy of science. In this issue Joseph Pitt argues that the power of case studies to instruct us about scientific methodology and epistemology depends on prior philosophical commitments, without which case studies are not philosophically useful. Here I reply to Pitt, demonstrating that case studies, properly deployed, illustrate styles of scientific work and modes of argumentation that are not (...) well handled by currently standard philosophical analyses. I illustrate these claims with exemplary findings from case studies dealing with exploratory experimentation and with interdisciplinary cooperation across sciences to yield multiple independent means of access to theoretical entities. The latter cases provide examples of ways that scientists support claims about theoretical entities that are not available in work performed within a single discipline. They also illustrate means of correcting systematic biases that stem from the commitments of each discipline taken separately. These findings illustrate the transformative power of case study methods, allow us to escape from the horns of Pitt's "dilemma of case studies," and vindicate some of the post-Kuhn uses to which case studies have been put. (shrink)

Why does an object or phenomenon become the subject of scientific inquiry? Why do some of these objects remain provocative, while others fade from center stage? And why do objects sometimes return as the focus of research long after they were once abandoned? Addressing such questions, _Biographies of Scientific Objects_ is about how whole domains of phenomena—dreams, atoms, monsters, culture, society, mortality, centers of gravity, value, cytoplasmic particles, the self, tuberculosis—come into being and sometimes pass away as objects of scientific (...) study. With examples drawn from both the natural and social sciences, and ranging from the sixteenth to the twentieth centuries, this book explores the ways in which scientific objects are both real and historical. Whether discovered or invented, these objects of inquiry broaden and deepen in meaning—growing more "real"—as they become entangled in webs of cultural significance, material practices, and theoretical derivations. Thus their biographies will matter to anyone concerned with the formation of scientific knowledge. Contributors are Jed Z. Buchwald, Lorraine Daston, Rivka Feldhay, Jan Goldstein, Gerard Jorland, Doris Kauffman, Bruno Latour, Theodore M. Porter, Hans-Jörg Rheinberger, Marshall Sahlins, and Peter Wagner. (shrink)

This 1983 book is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about (...) realism. Hacking illustrates how experimentation often has a life independent of theory. He argues that although the philosophical problems of scientific realism can not be resolved when put in terms of theory alone, a sound philosophy of experiment provides compelling grounds for a realistic attitude. A great many scientific examples are described in both parts of the book, which also includes lucid expositions of recent high energy physics and a remarkable chapter on the microscope in cell biology. (shrink)

Why does an object or phenomenon become the subject of scientific inquiry? Why do some of these objects remain provocative, while others fade from center stage? And why do objects sometimes return as the focus of research long after they were once abandoned? Addressing such questions, _Biographies of Scientific Objects_ is about how whole domains of phenomena—dreams, atoms, monsters, culture, society, mortality, centers of gravity, value, cytoplasmic particles, the self, tuberculosis—come into being and sometimes pass away as objects of scientific (...) study. With examples drawn from both the natural and social sciences, and ranging from the sixteenth to the twentieth centuries, this book explores the ways in which scientific objects are both real and historical. Whether discovered or invented, these objects of inquiry broaden and deepen in meaning—growing more "real"—as they become entangled in webs of cultural significance, material practices, and theoretical derivations. Thus their biographies will matter to anyone concerned with the formation of scientific knowledge. Contributors are Jed Z. Buchwald, Lorraine Daston, Rivka Feldhay, Jan Goldstein, Gerard Jorland, Doris Kauffman, Bruno Latour, Theodore M. Porter, Hans-Jörg Rheinberger, Marshall Sahlins, and Peter Wagner. (shrink)

The concept of the receptive field, first articulated by Hartline, is central to visual neuroscience. The receptive field of a neuron encompasses the spatial and temporal properties of stimuli that activate the neuron, and, as Hubel and Wiesel conceived of it, a neuron’s receptive field is static. This makes it possible to build models of neural circuits and to build up more complex receptive fields out of simpler ones. Recent work in visual neurophysiology is providing evidence that the classical receptive (...) field is an inaccurate picture. The receptive field seems to be a dynamic feature of the neuron. In particular, the receptive field of neurons in V1 seems to be dependent on the properties of the stimulus. In this paper, we review the history of the concept of the receptive field and the problematic data. We then consider a number of possible theoretical responses to these data. (shrink)