In _Matter and Consciousness_, Paul Churchland presents a concise and contemporary overview of the philosophical issues surrounding the mind and explains the main theories and philosophical positions that have been proposed to solve them. Making the case for the relevance of theoretical and experimental results in neuroscience, cognitive science, and artificial intelligence for the philosophy of mind, Churchland reviews current developments in the cognitive sciences and offers a clear and accessible account of the connections to philosophy of mind. For this (...) third edition, the text has been updated and revised throughout. The changes range from references to the iPhone's "Siri" to expanded discussions of the work of such contemporary philosophers as David Chalmers, John Searle, and Thomas Nagel. Churchland describes new research in evolution, genetics, and visual neuroscience, among other areas, arguing that the philosophical significance of these new findings lies in the support they tend to give to the reductive and eliminative versions of materialism. Matter and Consciousness, written by the most distinguished theorist and commentator in the field, offers an authoritative summary and sourcebook for issues in philosophy of mind. It is suitable for use as an introductory undergraduate text. (shrink)

Many philosophers doubt that one can provide any successful explanation of sensory qualities - of how things look, feel, or seem to a perceiving subject. To provide such an explanation, one would need to explain qualitative facts in non-qualitative terms. Attempts to construct such explanations have seemed, in principle, doomed. Austen Clark examines the strategy used in psychophysics, psychometrics, and sensory neurophysiology to explain qualitative facts. He argues that this strategy could succeed: its structure is sound, and it can answer (...) the various philosophical objections lodged against it. On this basis Professor Clark presents an analysis of senosry qualities that offers the possibility of explaining at least some qualia, and he sketches how this scheme might eventually reduce to neurophysiology. If he is correct, we are not doomed to an eternity of mere acquaintance with our qualia. (shrink)

This article examines the role of experimental generalizations and physical laws in neuroscientific explanations, using Hodgkin and Huxley’s electrophysiological model from 1952 as a test case. I show that the fact that the model was partly fitted to experimental data did not affect its explanatory status, nor did the false mechanistic assumptions made by Hodgkin and Huxley. The model satisfies two important criteria of explanatory status: it contains invariant generalizations and it is modular (both in James Woodward’s sense). Further, I (...) argue that there is a sense in which the explanatory heteronomy thesis holds true for this case. †To contact the author, please write to: SNF‐Professorship for Philosophy of Science, University of Basel, Missionsstrasse 21, 4003 Basel, Switzerland; e‐mail: [email protected]. (shrink)

One standard objection to the view that phenomenal experience is functionally determined is based upon what has come to be called ‘The Absent Qualia Hypothesis’, the idea that there could be a person or a machine that was functionally exactly like us but that felt or consciously experienced nothing at all . Advocates of this hypothesis typically maintain that we can easily imagine possible systems that meet the appropriate functional specifications but that intuitively lack any phenomenal consciousness. Ned Block , (...) for example, asks us to suppose that a billion Chinese people are each given a two-way radio with which to communicate with one another and with an artificial body. The movements of the body are controlled by the radio signals, and the signals themselves are made in accordance with instructions the Chinese people receive from a vast display in the sky which is visible to all of them. The instructions are such that the participating Chinese people together realize whatever programs the functionalist supposes underlie human phenomenal experience. (shrink)

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)

Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences (Kaplan and Bechtel; Kaplan and Craver). We argue that mechanistic explanation is defined by localization and decomposition. We argue further that systems neuroscience contains explanations that violate both localization and decomposition. We conclude that the mechanistic model of explanation needs to either stretch to now include explanations wherein localization or decomposition fail or acknowledge that there are counterexamples to mechanistic explanation (...) in the biological sciences. (shrink)

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman’s account of minimal model explanations and that it demonstrates (...) how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated. (shrink)

In the last two decades few topics in philosophy of science have received as much attention as mechanistic explanation. A significant motivation for these accounts is that scientists frequently use the term “mechanism” in their explanations of biological phenomena. While scientists appeal to a variety of causal concepts in their explanations, many philosophers argue or assume that all of these concepts are well understood with the single notion of mechanism. This reveals a significant problem with mainstream mechanistic accounts– although philosophers (...) use the term “mechanism” interchangeably with other causal concepts, this is not something that scientists always do. This paper analyses two causal concepts in biology–the notions of “mechanism” and “pathway”–and how they figure in biological explanation. I argue that these concepts have unique features, that they are associated with distinct strategies of causal investigation, and that they figure in importantly different types of explanation. (shrink)

Images come in many varieties, but for evidential purposes, photographs are privileged. Recent advances in neuroimaging provide us with a new type of image that is used as scientific evidence. Brain images are epistemically compelling, in part because they are liable to be viewed as akin to photographs of brain activity. Here I consider features of photography that underlie the evidential status we accord it, and argue that neuroimaging diverges from photography in ways that seriously undermine the photographic analogy. While (...) neuroimaging remains an important source of scientific evidence, proper interpretation of brain images is much more complex than it appears. ‡This work was supported in part by a grant from the Leslie Humanities Center at Dartmouth College. I thank John Kulvicki for helpful comments, and Kim Sterelny, for making it possible for me to spend some time at the ANU with a grant from the Australian Research Council. †To contact the author, please write to: Dartmouth College, Department of Philosophy, Hanover, NH 03755; e-mail: [email protected]. (shrink)

In this paper, I explore the implications of recent empirical research on concept representation for the philosophical enterprise of conceptual analysis. I argue that conceptual analysis, as it is commonly practiced, is committed to certain assumptions about the nature of our intuitive categorization judgments. I then try to show how these assumptions clash with contemporary accounts of concept representation in cognitive psychology. After entertaining an objection to my argument, I close by considering ways in which conceptual analysis might be altered (...) to accord better with the empirical work. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

There has been considerable optimism recently, among philosophers and neuroscientists, concerning the prospect for major discoveries about the neurophysiological basis of mind. The support for this optimism has been extremely abstract and general. I wish to present some grounds ..

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.

fMRI promises to uncover the functional structure of the brain. I argue, however, that pictures of ‘brain activity' associated with fMRI experiments are poor evidence for functional claims. These neuroimages present the results of null hypothesis significance tests performed on fMRI data. Significance tests alone cannot provide evidence about the functional structure of causally dense systems, including the brain. Instead, neuroimages should be seen as indicating regions where further data analysis is warranted. This additional analysis rarely involves simple significance testing, (...) and so justified skepticism about neuroimages does not provide reason for skepticism about fMRI more generally. (shrink)

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

It turned out that there was no phlogiston, no caloric fluid, and no luminiferous ether. Might it turn out that there are no beliefs and desires? Patricia and Paul Churchland say yes} We say no. In part one we give our positive argument for the existence of beliefs and desires.

Part I of this trilogy, Historical and Scientific Setting, set out a general context for selecting a certain subclass of inter-theoretic relations as achieving appropriate explanatory and ontological unification – hence for properly being labelled reductive. Something of the complexity of these relations in real science was explored. The present article concentrates on the role which identity plays in structuring the reduction relation and so in achieving ontological and explanatory unification.

Any theory of reduction that goes only so far as carried in Parts I and II does only half the job. Prima facie at least, there are cases of would-be reduction which seem torn between two conflicting intuitions. On the one side there is a strong intuition that reduction is involved, and a strongly retentive reduction at that. On the other side it seems that the concepts at one level cross-classify those at the other level, so that there is no (...) way to identify properties at one level with those at the other. There is evidence to suggest that there will be no unique mental state/neural state association that can be set up, because, e.g., many different parts of the nervous system are all capable of taking over ‘control’ of the one mental function. And it is alleged that infinitely many, worse: indefinitely many, different bio-chemo-physical states could correspond to the economic property ‘has a monetary system of economic exchange’; and similarly for the property ‘has just won a game of tennis’. Yet one doesn't want an economic system or a game of tennis to be some ghostly addition to the actual bio-chemo-physical processes and events involved. Similarly one hopes that neurophysiology allied with the rest of natural science will render human experience and behaviour explicable. (shrink)

The Three Papers comprising this series, together with my earlier [34] also published in this journal, constitute an attempt to set out the major issues in the theoretical domain of reduction and to develop a general theory of theory reduction. The fourth paper, [34], though published separately from this trio, is integral to the presentation and should be read in conjunction with these papers. Even so, the presentation is limited in scope – roughly, to intertheoretic reduction among empirical theories – (...) and informal in presentation – not least because a satisfying formal account of theories has yet to be offered. And despite the length, the treatment is still condensed; often corroborating and/or intuitively helpful detail has had to be consigned to footnotes or omitted. I approach the problem from within my own naturalistic realist philosophy of science and formal analysis of abstract hierarchy in theory. The sources for the former are [25], [29], [31], and [32] and those for the latter essentially [27] and [30]. Hierarchical notions played a significant role in the already published [34]. (shrink)

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in (...) parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery. (shrink)

Preface 1 Introduction: The Persistence of the Attitudes 2 Individualism and Supervenience 3 Meaning Holism 4 Meaning and the World Order Epilogue Creation Myth Appendix Why There Still Has to be a Language of Thought Notes References Author Index.

Our ethical obligations to another being depend at least in part on that being’s capacity for a mental life. Our usual approach to inferring the mental state of another is to reason by analogy: If another being behaves as I do in a circumstance that engenders a certain mental state in me, I conclude that it has engendered the same mental state in him or her. Unfortunately, as philosophers have long noted, this analogy is fallible because behavior and mental states (...) are only contingently related. If the other person is acting, for example, we could draw the wrong conclusion about his or her mental state. In this article I consider another type of analogy that can be drawn between oneself and another to infer the mental state of the other, substituting brain activity for behavior. According to most current views of the mind–body problem, mental states and brain states are non-contingently related, and hence inferences drawn with the new analogy are not susceptible to the alternative interpretations that plague the behavioral analogy. The implications of this approach are explored in two cases for which behavior is particularly unhelpful as a guide to mental status: severely brain–damaged patients who are incapable of intentional communicative behavior, and nonhuman animals whose behavioral repertoires are different from ours and who lack language. (shrink)

The eye may be window to the soul, but neuroscientists aim to get inside and measure the interior directly. There's also talk about moving some walls.

In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.

The differences Block attempts to capture with his putative distinction between P-consciousness and A-consciousness are more directly and perspicuously handled in terms of differences in richness of content and degree of influence. Block's critiques, based on his misbegotten distinction, evaporate on closer inspection.

The notion of cognitive system is widely used in explanations in cognitive psychology and neuroscience. Traditional approaches define cognitive systems in an agent-relative way, that is, via top-down functional decomposition that assumes a cognitive agent as starting point. The extended cognition movement challenged that approach by questioning the primacy of the notion of cognitive agent. In response, [Adams, F., and K. Aizawa. 2001. The Bounds of Cognition. Oxford, UK: Wiley-Blackwell.] suggested that to have a clear understanding of what a cognitive (...) system is we may need to solve “the demarcation challenge”: the problem of identifying a reliable way to determine which mechanisms that are causally responsible for the production of a certain cognitive process constitute a cognitive system responsible for such process and which ones do not. Recently, [Rupert, R. 2009. Cognitive Systems and the Extended Mind. Oxford: Oxford University Press.] offered a solution based on the idea that the mechanisms that constitute a cognitive system are integrated in a particular sense. In this paper I critically review Rupert’s solution and argue against it. Additionally, I argue that a successful account of cognitive system must accommodate the fact that the neural mechanisms causally responsible for the production of a cognitive process are diachronically dynamic and yet functionally stable. At the end, I offer a suggestion as to how to accommodate this diachronic dynamicity without losing functional stability. I conclude by drawing some implications for the discussion on cognitive ontologies. (shrink)

This is a unique book. It is excellently written, crammed with information, wise and a pleasure to read.' ---Daniel C. Dennett, Tufts University.

A Neurocomputationial Perspective illustrates the fertility of the concepts and data drawn from the study of the brain and of artificial networks that model the...

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

This paper examines Milner and Goodale’s hypothesis about the two visual streams and raises the questions of whether properties in egocentric space (commonly associated with the vision-for-action, or "dorsal," stream) can be part of the phenomenal content of perceptual experience, or only properties in allocentric space (commonly associated with the vision-for-perception, or "ventral," stream) can play this role, and how (if at all) properties in egocentric space differ from properties in allocentric space. These questions are reminiscent of issues raised by (...) Christopher Peacocke's "equal-sized trees" case: if you are looking at equal-sized trees on the side of a road, the trees will phenomenally look to you to be equally tall. But it is also true that a tree will take up more of the space in your visual field the closer it is to you. So, the equal-sized trees will also phenomenally look to you to have different heights. Your (visual) perceptual experience is not illusory. That is, the trees veridically look to you to have the same height, and they also veridically look to you to have different heights. Call the sort of issue raised here the "problem of dual looks." I provide a solution to the problem of dual looks that helps shed light on whether properties in egocentric space can be part of the phenomenal content of perceptual experience, and how (if at all) properties in egocentric space differ from properties in allocentric space. (shrink)

Machamer, Darden, and Craver argue that causal explanations explain effects by describing the operations of the mechanisms which produce them. One of this paper’s aims is to take advantage of neglected resources of Mechanism to rethink the traditional idea that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal explanations. I think that causal productivity and regularity are by no means the same thing, (...) and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers’ from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research. (shrink)

The need for representations and computations over their contents in psychological explanations is often cited as both the mark of the genuinely cognitive and a source of skepticism about the reducibility of cognitive theories to neuroscience. A generic version of this anti-reductionist argument is rejected in this paper as unsound, since (i) current thinking about associative learning emphasizes the need for cognitivist resources in theories adequate to explain even the simplest form of this phenomena (Pavlovian conditioning), and yet (ii) the (...) most widely accepted recent theory of associative learning, which utilizes cognitivist resources, has already been reduced to a purely neurophysiological account. Psychoneural reduction of genuinely cognitivist theories is thus already an accomplished scientific fact, despite pronouncements by anti-reductionists about its conceptual impossibility or empirical implausibility. In addition, the specific form of reduction involved in this case (“combinatorial” reduction) provides a promising model for further cognitivist-to-neuroscience theory reductions. (shrink)

The focus of much recent debate between realists and eliminativists about the propositional attitudes obscures the fact that a spectrum of positions lies between these celebrated extremes. Appealing to an influential theoretical development in cognitive neurobiology, I argue that there is reason to expect such an “intermediate” outcome. The ontology that emerges is a revisionary physicalism. The argument draws lessons about revisionistic reductions from an important historical example, the reduction of equilibrium thermodynamics to statistical mechanics, and applies them to the (...) relationship developing between propositional attitude psychology and this potential neuroscientific successor. It predicts enough conceptual change to rule out a straightforward realism about the attitudes; but at the same time it also resists the eliminativist's comparison of the fate awaiting the propositional attitudes to that befalling caloric fluid, phlogiston, and the like. (shrink)

Accounts of causal explanation are standard in philosophy of science. Less common are accounts of experimentation to investigate causal relations: detailed discussions of the specific kinds of experiments scientists design and run. Silva, Landreth, and Bickle’s account of “connection experiments” derives directly from landmark experiments in “molecular and cellular cognition.” We start with its key components, and then using a detailed case study from recent social neuroscience we emphasize and extend three features of SLB’s account: a division of distinct types (...) of connection experiments, each providing a different type of evidence for a hypothesized causal relationship; the typically downward-looking nature of the experimental search for mediating causes in mainstream neurobiology; and most importantly, the centrality of multiple-experiment research programs, with each experiment designed such that if successful its results can be integrated with the others, toward the goal of confirming multiple-phenomena causal pathways. Our extension of SLB’s account complements existing philosophical work on experimentation in neurobiology. (shrink)

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...) they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations. (shrink)