This article reviews some of the ways in which philosophical problems concerning music can be informed by approaches from the cognitive sciences (principally psychology and neuroscience). Focusing on the issues of musical expressiveness and the arousal of emotions by music, the key philosophical problems and their alternative solutions are outlined. There is room for optimism that while current experimental data does not always unambiguously satisfy philosophical scrutiny, it can potentially support one theory over another, and in some cases allow us (...) to synthesize or reject traditional philosophical differences. (shrink)

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

Where does the mind stop and the rest of the world begin? The question invites two standard replies. Some accept the demarcations of skin and skull, and say that what is outside the body is outside the mind. Others are impressed by arguments suggesting that the meaning of our words "just ain't in the head", and hold that this externalism about meaning carries over into an externalism about mind. We propose to pursue a third position. We advocate a very different (...) sort of externalism: an _active externalism_, based on the active role of the environment in driving cognitive processes. (shrink)

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology – namely, Behaviorism and evolutionary psychology – that set aside mechanistic explanations or make use of optimality assumptions. Through (...) these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

Many who advocate dynamical systems approaches to cognitive science believe themselves committed to the thesis of extended cognition and to the rejection of representation. I argue that this belief is false. In part, this misapprehension rests on a warrantless re-conception of cognition as intelligent behavior. In part also, it rests on thinking that conceptual issues can be resolved empirically. Once these issues are sorted out, the way is cleared for a dynamical systems approach to cognition that is free to retain (...) the standard conception of cognition as taking place in the head, and over representations. (shrink)

This paper addresses the question whether we can conceive of music cognition in ecosemiotic terms. It claims that music knowledge must be generated as a tool for adaptation to the sonic world and calls forth a shift from a structural description of music as an artifact to a process-like approach to dealing with music. As listeners, we are observers who construct and organize our knowledge and bring with us our observational tools. What matters is not merely the sonic world in (...) its objective qualities, but the world as perceived. In order to make these claims operational we can rely on the ecological concept of coping with the sonic world and the cybernetic concepts of artificial and adaptive devices. Listeners, on this view, are able to change their semantic relations with the sonic world through functional adaptations at the level of sensing, acting and coordinating between action and perception. This allows us to understand music in functional terms of what it affords to us and not merely in terms of its acoustic qualities. There are, however, degrees of freedom and constraints which shape the semiotization of the sonic world. As such we must consider the role of event perception and cognitive economy: listeners do not perceive the acoustical environment in terms of phenomenological descriptions but as ecological events. (shrink)

This paper addresses the question whether we can conceive of music cognition in ecosemiotic terms. It claims that music knowledge must be generated as a tool for adaptation to the sonic world and calls forth a shift from a structural description of music as an artifact to a process-like approach to dealing with music. As listeners, we are observers who construct and organize our knowledge and bring with us our observational tools. What matters is not merely the sonic world in (...) its objective qualities, but the world as perceived. In order to make these claims operational we can rely on the ecological concept of coping with the sonic world and the cybernetic concepts of artificial and adaptive devices. Listeners, on this view, are able to change their semantic relations with the sonic world through functional adaptations at the level of sensing, acting and coordinating between action and perception. This allows us to understand music in functional terms of what it affords to us and not merely in terms of its acoustic qualities. There are, however, degrees of freedom and constraints which shape the semiotization of the sonic world. As such we must consider the role of event perception and cognitive economy: listeners do not perceive the acoustical environment in terms of phenomenological descriptions but as ecological events. (shrink)

Standard models of visual perception hold that vision is an inferential or interpretative process. Such models are said to be superior to competing, non-inferential views in explanatory power. In particular, they are said to be capable of explaining a number of otherwise mysterious, visual phenomena such as multi-stable perception. Multi-stable perception paradigmatically occurs in the presence of ambiguous figures, single images that can give rise to two or more distinct percepts. Different interpretations are said to produce the different percepts. In (...) this paper, I argue that a non-inferential account of visual perception is just as capable of explaining multi-stable perception. I propose an embedded understanding of vision, and show how the embedded account can, after properly qualifying them, use the explanatory resources of the inferential view to explain just what such a view explains. (shrink)

There is a certain excitement in vision science concerning the idea of applying the tools of bayesian decision theory to explain our perceptual capacities. Bayesian models are thought to be needed to explain how the inverse problem of perception is solved, and to rescue a certain constructivist and Kantian way of understanding the perceptual process. Anticlimactically, I argue both that bayesian outlooks do not constitute good solutions to the inverse problem, and that they are not constructivist in nature. In explaining (...) how visual systems derive a single percept from underdetermined stimulation, orthodox versions of bayesian accounts encounter a problem. The problem shows that such accounts need to be grounded in Natural Scene Statistics (NSS), an approach that takes seriously the Gibsonian insight that studying perception involves studying the statistical regularities of the environment in which we are situated. Additionally, I argue that bayesian frameworks postulate structures that hardly rescue a constructivist way of understanding perception. Except for percepts, the posits of bayesian theory are not representational in nature. bayesian perceptual inferences are not genuine inferences. They are biased processes that operate over nonrepresentational states. (shrink)

I defend a model of the musically extended mind. I consider how acts of “musicking” grant access to novel emotional experiences otherwise inaccessible. First, I discuss the idea of “musical affordances” and specify both what musical affordances are and how they invite different forms of entrainment. Next, I argue that musical affordances – via soliciting different forms of entrainment – enhance the functionality of various endogenous, emotiongranting regulative processes, drawing novel experiences out of us with an expanded complexity and phenomenal (...) character. I argue that music therefore ought to be thought of as part of the vehicle needed to realize these emotional experiences. I appeal to different sources of empirical work to develop this idea. (shrink)

In arbitrating between representational and relational theories of perception, perceptual illusions—cases in which a subject’s perceptual experience diverges from the way the world really is—constitute an important battleground. The debate has, however, been dominated by discussions of visual perception. In attempting to extend the debate to audition, it is appropriate to start by considering what is thought to be a key case of auditory illusion. I consider the phenomenon of the ‘missing fundamental’, as well as examining a notion that is (...) often deployed by representationalists to explain it—namely, perceptual inference. Though it is frequently deployed as an explanatory concept by inferentialists, the notion of perceptual inference is somewhat opaque. Here, I formulate a ‘job description’ for perceptual inference, involving rule-following. I then identify two sets of cases that commonly prompt the invocation of perceptual inference: namely, cases of perceptual illusion, and cases of veridical perception where the perceptual content outstrips the information present in the stimulus. I then argue that an appeal to perceptual inference is unnecessary, in the case of the missing fundamental, for two reasons. Firstly, the missing fundamental is not, after all, a clear candidate for the ascription of inferential capacity to the auditory system: it is neither an illusion, nor is it the case that the stimulus is crucially impoverished. That is, it submits to a ‘direct’ explanation. Secondly, given the adequacy of a simpler explanation, and the difficulty between distinguishing between real rule-following and the mere appearance of it, I argue that we should avoid ascribing inferential capacity to the auditory system. I close by considering objections, and offering replies. (shrink)

Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue that their purported confirmation largely relies on a methodology that depends on premises that are inconsistent with the claim that people are Bayesian about learning and inference. Bayesian models in cognitive science derive their appeal from their normative claim that the modeled inference is in some sense rational. Standard accounts of the rationality of Bayesian inference imply predictions that an agent selects the option that maximizes the (...) posterior expected utility. Experimental confirmation of the models, however, has been claimed because of groups of agents that probability match the posterior. Probability matching only constitutes support for the Bayesian claim if additional unobvious and untested (but testable) assumptions are invoked. The alternative strategy of weakening the underlying notion of rationality no longer distinguishes the Bayesian model uniquely. A new account of rationality—either for inference or for decision-making—is required to successfully confirm Bayesian models in cognitive science. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

Why does the world look to us as it does? As Nico Orlandi argues, it is simply because of how the world is. This answer emerges from understanding vision as situated in a structured environment, and it contrasts with the view that visual perception involves an inference.

While philosophers of mind have been arguing over the status of mental representations in cognitive science, cognitive scientists have been quietly engaged in studying perception, action, and cognition without explaining them in terms of mental representation. In this book, Anthony Chemero describes this nonrepresentational approach, puts it in historical and conceptual context, and applies it to traditional problems in the philosophy of mind. Radical embodied cognitive science is a direct descendant of the American naturalist psychology of William James and John (...) Dewey, and follows them in viewing perception and cognition to be understandable only in terms of action in the environment. Chemero argues that cognition should be described in terms of agent-environment dynamics rather than in terms of computation and representation. After outlining this orientation to cognition, Chemero proposes a methodology: dynamical systems theory, which would explain things dynamically and without reference to representation. He also advances a background theory: Gibsonian ecological psychology, "shored up" and clarified. Chemero then looks at some traditional philosophical problems through the lens of radical embodied cognitive science and concludes that the comparative ease with which it resolves these problems, combined with its empirical promise, makes this approach to cognitive science a rewarding one. "Jerry Fodor is my favorite philosopher," Chemero writes in his preface, adding, "I think that Jerry Fodor is wrong about nearly everything." With this book, Chemero explains nonrepresentational, dynamical, ecological cognitive science as clearly and as rigorously as Jerry Fodor explained computational cognitive science in his classic work The Language of Thought. (shrink)

The first comprehensive presentation of the dynamical approach to cognition. It contains a representative sampling of original, current research on topics such as perception, motor control, speech and language, decision making, and development.