Contrary to standard assumptions, reasoning is often an emotional process. Emotions can have good effects, as when a scientist gets excited about a line of research and pursues it successfully despite criticism. But emotions can also distort reasoning, as when a juror ignores evidence of guilt just because the accused seems like a nice guy. In _Hot Thought_, Paul Thagard describes the mental mechanisms -- cognitive, neural, molecular, and social -- that interact to produce different kinds of human thinking, from (...) everyday decision making to legal reasoning, scientific discovery, and religious belief, and he discusses when and how thinking and reasoning should be emotional. Thagard argues that an understanding of emotional thinking needs to integrate the cognitive, neural, molecular, and social levels. Many of the chapters employ computational models of various levels of thinking, including HOTCO models and the more neurologically realistic GAGE model. Thagard uses these models to illuminate thinking in the domains of law, science, and religion, discussing such topics as the role of doubt and reasonable doubt in legal and other contexts, valuable emotional habits for successful scientists, and the emotional content of religious beliefs. Identifying and assessing the impact of emotion, Thagard argues, can suggest ways to improve the process of reasoning. (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)

Philosophy and Neuroscience: A Ruthlessly Reductive Account is the first book-length treatment of philosophical issues and implications in current cellular and molecular neuroscience. John Bickle articulates a philosophical justification for investigating "lower level" neuroscientific research and describes a set of experimental details that have recently yielded the reduction of memory consolidation to the molecular mechanisms of long-term potentiation (LTP). These empirical details suggest answers to recent philosophical disputes over the nature and possibility of psycho-neural scientific reduction, including the multiple realization (...) challenge, mental causation, and relations across explanatory levels. Bickle concludes by examining recent work in cellular neuroscience pertaining to features of conscious experience, including the cellular basis of working memory, the effects of explicit selective attention on single-cell activity in visual cortex, and sensory experiences induced by cortical microstimulation. (shrink)

Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their (...) styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

In many domains of biology, explanation takes the form of characterizing the mechanism responsible for a particular phenomenon in a specific biological system. How are such explanations generalized? One important strategy assumes conservation of mechanisms through evolutionary descent. But conservation is seldom complete. In the case discussed, the central mechanism for circadian rhythms in animals was first identified in Drosophila and then extended to mammals. Scientists' working assumption that the clock mechanisms would be conserved both yielded important generalizations and served (...) as a heuristic for discovery, especially when significant differences between the insect and mammalian mechanism were identified. †To contact the author, please write to: Department of Philosophy and Interdisciplinary Programs in Science Studies and Cognitive Science, 0119, University of California, San Diego, La Jolla, CA 92093‐0119; e‐mail: [email protected]. (shrink)

We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...) causes can be translated into mechanistically mediated effects, the posited relationship is intelligible and should raise no special philosophical objections. When they cannot, they are suspect. (shrink)

A description of mental mechanisms that explain how emotions influence thought, from everyday decision making to scientific discovery and religious belief, and an analysis of when emotion can contribute to good reasoning.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

1. A Historical Look at Unity 2. Field Guide to Modern Concepts of Reduction and Unity 3. Kitcher's Revisionist Account of Unification 4. Critics of Unity 5. Integration Instead of Unity 6. Reduction via Mechanisms 7. Case Studies in Reduction and Unification across the Disciplines.

Jaegwon Kim is one of the most preeminent and most influential contributors to the philosophy of mind and metaphysics. This collection of essays presents the core of his work on supervenience and mind with two sets of postscripts especially written for the book. The essays focus on such issues as the nature of causation and events, what dependency relations other than causal relations connect facts and events, the analysis of supervenience, and the mind-body problem. A central problem in the philosophy (...) of mind is the problem of explaining how the mind can causally influence bodily processes. Professor Kim explores this problem in detail, criticizes the nonreductionist solution of it, and offers a modified reductionist solution of his own. Both professional philosophers and their graduate students will find this an invaluable collection. (shrink)

After the discovery of the structure of DNA in 1953, scientists working in molecular biology embraced reductionism—the theory that all complex systems can be understood in terms of their components. Reductionism, however, has been widely resisted by both nonmolecular biologists and scientists working outside the field of biology. Many of these antireductionists, nevertheless, embrace the notion of physicalism—the idea that all biological processes are physical in nature. How, Alexander Rosenberg asks, can these self-proclaimed physicalists also be antireductionists? With clarity and (...) wit, Darwinian Reductionism navigates this difficult and seemingly intractable dualism with convincing analysis and timely evidence. In the spirit of the few distinguished biologists who accept reductionism—E. O. Wilson, Francis Crick, Jacques Monod, James Watson, and Richard Dawkins—Rosenberg provides a philosophically sophisticated defense of reductionism and applies it to molecular developmental biology and the theory of natural selection, ultimately proving that the physicalist must also be a reductionist. (shrink)