As yet, there is no enactive account of social cognition. This paper extends the enactive concept of sense-making into the social domain. It takes as its departure point the process of interaction between individuals in a social encounter. It is a well-established finding that individuals can and generally do coordinate their movements and utterances in such situations. We argue that the interaction process can take on a form of autonomy. This allows us to reframe the problem of social cognition as (...) that of how meaning is generated and transformed in the interplay between the unfolding interaction process and the individuals engaged in it. The notion of sense-making in this realm becomes participatory sense-making. The onus of social understanding thus moves away from strictly the individual only. (shrink)

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)

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)

The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. These experimental strategies include activation strategies, interference strategies, and additive strategies. These strategies are mutually reinforcing, (...) providing a kind of interlevel and intratheoretic robustness that has not previously been recognized. (shrink)

The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. These experimental strategies include activation strategies, interference strategies, and additive strategies. These strategies are mutually reinforcing, (...) providing a kind of interlevel and intratheoretic robustness that has not previously been recognized. (shrink)

In what sense are the activities and properties of components in a mechanism explanatorily relevant to the behavior of a mechanism as a whole? I articulate this problem, the problem of constitutive relevance, and I show that it must be solved if we are to understand mechanisms and mechanistic explanation. I argue against some putative solutions to the problem of constitutive relevance, and I sketch a positive account according to which relevance is analyzed in terms ofrelationships of mutual manipulability between (...) the behavior of a mechanism as a whole and the properties and activities of its components. My account is a causal-mechanical account in the sense that it is a particular expression of the idea that constitutive explanation is a matter of showing how an explanandum phenomenon is situated within the causal structure of the world. It is thus offered as a rival to epistemic (argument-centered) and psychological accounts of interlevel explanation. (shrink)

In what sense are the activities and properties of components in a mechanism explanatorily relevant to the behavior of a mechanism as a whole? I articulate this problem, the problem of constitutive relevance, and I show that it must be solved if we are to understand mechanisms and mechanistic explanation. I argue against some putative solutions to the problem of constitutive relevance, and I sketch a positive account according to which relevance is analyzed in terms ofrelationships of mutual manipulability between (...) the behavior of a mechanism as a whole and the properties and activities of its components. My account is a causal-mechanical account in the sense that it is a particular expression of the idea that constitutive explanation is a matter of showing how an explanandum phenomenon is situated within the causal structure of the world. It is thus offered as a rival to epistemic (argument-centered) and psychological accounts of interlevel explanation. (shrink)

Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform. The representation and algorithmic perspective offers an understanding of how information about the environment is (...) encoded within the mechanism and what are the patterns of organization that enable the parts of the mechanism to produce the phenomenon. The implementation perspective yields an understanding of the neural details of the mechanism and how they constrain function and algorithms. Once we adequately characterize the distinct role of each level of analysis, it is fairly straightforward to see how they relate. (shrink)

This article argues that the basic account of mechanism and mechanistic explanation, involving sequential execution of qualitatively characterized operations, is itself insufficient to explain biological phenomena such as the capacity of living organisms to maintain themselves as systems distinct from their environment. This capacity depends on cyclic organization, including positive and negative feedback loops, which can generate complex dynamics. Understanding cyclically organized mechanisms with complex dynamics requires coordinating research directed at decomposing mechanisms into parts and operations with research using computational (...) models to recompose mechanisms and determine their dynamic behavior. This coordinated endeavor yields dynamic mechanistic explanations. (shrink)

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)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

This chapter discusses the flaws of Clark’s extended mind hypothesis. Clark’s hypothesis assumes that the nature of the processes internal to an object has nothing to do with whether that object carries out cognitive processing. The only condition required is that the object is coupled with a cognitive agent and interacts with it in a certain way. In making this tenuous connection, Clark commits the most common mistake extended mind theorists make; alleging that an object becomes cognitive once it is (...) connected to a cognitive agent is a “coupling-constitution fallacy.” From this fallacy, many hastily proceed to the conclusion that the object or process constitutes part of the agent’s cognitive apparatus or cognitive processing. (shrink)

This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...) shows that many different areas and traditions of cognitive scientific research can be unified under the mechanistic framework. (shrink)

People are minded creatures; we have thoughts, feelings and emotions. More intriguingly, we grasp our own mental states, and conduct the business of ascribing them to ourselves and others without instruction in formal psychology. How do we do this? And what are the dimensions of our grasp of the mental realm? In this book, Alvin I. Goldman explores these questions with the tools of philosophy, developmental psychology, social psychology and cognitive neuroscience. He refines an approach called simulation theory, which starts (...) from the familiar idea that we understand others by putting ourselves in their mental shoes. Can this intuitive idea be rendered precise in a philosophically respectable manner, without allowing simulation to collapse into theorizing? Given a suitable definition, do empirical results support the notion that minds literally create surrogates of other peoples mental states in the process of mindreading? Goldman amasses a surprising array of evidence from psychology and neuroscience that supports this hypothesis. (shrink)

I argue that there is no conflict between the simulation theory, once it is freed from certain constraints carried over from theory theory, and Gallagher's view that our primary and pervasive way of engaging with others rests on 'direct', non-mentalizing perception of the 'meanings' of others' facial expressions, gestures, and intentional actions.

The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary dynamicist (...) research reveals the need for a more sophisticated account of mechanistic explanation. (shrink)

Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of the system's parts if it depends upon their mode of organization--a view consistent with reduction. Emergence can be analyzed as a failure of aggregativity--a state in which "the whole is nothing more than the sum of its parts." Aggregativity requires four conditions, giving tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different (...) degrees, these conditions provide powerful evaluation criteria for choosing decompositions, and heuristics for detecting biases of vulgar reductionisms. This analysis of emergence is compatible with reduction. (shrink)

The autopoietic theory and the enactive approach are two theoretical streams that, in spite of their historical link and conceptual affinities, offer very different views on the nature of living beings. In this paper, we compare these views and evaluate, in an exploratory way, their respective degrees of internal coherence. Focusing the analyses on certain key notions such as autonomy and organizational closure, we argue that while the autopoietic theory manages to elaborate an internally consistent conception of living beings, the (...) enactive approach presents an internal tension regarding its characterization of living beings as intentional systems directed at the environment. (shrink)

Eliminativism has been a major focus of discussion in the philosophy of mind for the last two decades. According to eliminativists, beliefs and other intentional states are the posits of a folk theory of mind standardly called "folk psychology". That theory, they claim, is radically false and hence beliefs and other intentional states do not exist. We argue that the expression "folk psychology" is ambiguous in an important way. On the one hand, "folk psychology" is used by many philosophers and (...) cognitive scientists to refer to an internally represented theory of human psychology exploited in the prediction of behavior. On the other hand, "folk psychology" is used to refer to the theory of mind implicit in our everyday talk about mental states. We then argue that sorting out the conceptual and terminological confusion surrounding "folk psychology" has major consequences for the eliminativism debate. In particular, if certain models of cognition turn out to be true, then on some readings of "folk psychology" the arguments for eliminativism collapse. (shrink)

This paper, in opposition to the standard theories of social cognition found in psychology and cognitive science, defends the idea that direct perception plays an important role in social cognition. The two dominant theories, theory theory and simulation theory , both posit something more than a perceptual element as necessary for our ability to understand others, i.e., to “mindread” or “mentalize.” In contrast, certain phenomenological approaches depend heavily on the concept of perception and the idea that we have a direct (...) perceptual grasp of the other person’s intentions, feelings, etc. This paper explains precisely what the notion of direct perception means, offers evidence from developmental studies, and proposes a non-simulationist interpretation of the neuroscience of mirror systems. (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)

According to the new mechanistic approach, an acting entity is at a lower mechanistic level than another acting entity if and only if the former is a component in the mechanism for the latter. Craver and Bechtel :547–563, 2007. doi:10.1007/s10539-006-9028-8) argue that a consequence of this view is that there cannot be causal interactions between acting entities at different mechanistic levels. Their main reason seems to be what I will call the Metaphysical Argument: things at different levels of a mechanism (...) are related as part and whole; wholes and their parts cannot be related as cause and effect; hence, interlevel causation in mechanisms is impossible. I will analyze this argument in more detail and show under which conditions it is valid. This analysis will reveal that interlevel causation in mechanisms is indeed possible, if we take seriously the idea that the relata of the mechanistic level relation are acting entities and accept a slightly modified notion of a mechanistic level that is highly plausible in the light of the first clarification. (shrink)

Philosophical accounts of the constitution relation have been explicated in terms of synchronic relations between higher‐ and lower‐level entities. Such accounts, I argue, are temporally austere or impoverished, and are consequently unable to make sense of the diachronic and dynamic character of constitution in dynamical systems generally and dynamically extended cognitive processes in particular. In this paper, my target domain is extended cognition based on insights from nonlinear dynamics. Contrariwise to the mainstream literature in both analytical metaphysics and extended cognition, (...) I develop a nonstandard, alternative conception of constitution, which I call “diachronic process constitution”. It will be argued that only a diachronic and dynamical conception of constitution is consistent with the nature of constitution in distributed cognitive processes. (shrink)

Researchers in the enactivist tradition have recently argued that social interaction can constitute social cognition, rather than simply serve as the context for social cognition. They contend that a focus on social interaction corrects the overemphasis on mechanisms inside the individual in the explanation of social cognition. I critically assess enactivism’s claims about the explanatory role of social interaction in social cognition. After sketching the enactivist approach to cognition in general and social cognition in particular, I identify problems with an (...) enactivist taxonomy of roles for social interaction in the explanation of social cognition (contextual, enabling, and constitutive). In particular, I show that this enactivist taxonomy does not clearly distinguish between enabling conditions and constitutive elements, which would make them in danger of committing the coupling-constitution fallacy found in some attempts to extend cognition. I explore resources enactivism has to more clearly demarcate constitutive parts of a cognitive system, but identify problems in applying them to some of the main cases of social cognition enactivists characterize as being constituted by social interaction. I offer the mechanistic approach to explanation as an alternative that captures much of what enactivists want to say about the relations between social and individual levels, but views social interactions from the perspective of embedded cognition rather than as being constitutive of social cognition. (shrink)

Recent studies of emotion mindreading reveal that for three emotions, fear, disgust, and anger, deficits in face-based recognition are paired with deficits in the production of the same emotion. What type of mindreading process would explain this pattern of paired deficits? The simulation approach and the theorizing approach are examined to determine their compatibility with the existing evidence. We conclude that the simulation approach offers the best explanation of the data. What computational steps might be used, however, in simulation-style emotion (...) detection? Four alternative models are explored: a generate-and-test model, a reverse simulation model, a variant of the reverse simulation model that employs an “as if” loop, and an unmediated resonance model. (shrink)

The aim of this paper is to study interpretation, specifically, to work toward an account of interpretation that seems descriptively and explanatorily correct. No account of interpretation can be philosophically helpful, I submit, if it is incompatible with a correct account of what people actually do when they interpret others. My question, then, is: how does the (naive) interpreter arrive at his/her judgments about the mental attitudes of others? Philosophers who have addressed this question have not, in my view, been (...) sufficiently psychological, or cognitivist, even those who are otherwise psychologically inclined. I shall defend some proposals about the activity of interpretation that are, I believe, psychologically more realistic than their chief competitors. (shrink)

Identities formed with proper names may be contingent. this claim is made first through an example. the paper then develops a theory of the semantics of concrete things, with contingent identity as a consequence. this general theory lets concrete things be made up canonically from fundamental physical entities. it includes theories of proper names, variables, cross-world identity with respect to a sortal, and modal and dispositional properties. the theory, it is argued, is coherent and superior to its rivals, in that (...) it stems naturally from a systematic picture of the physical world. (shrink)

Gricean pragmatics has often been criticised for being implausible from a psychological point of view. This line of criticism is never backed up by empirical evidence, but more importantly, it ignores the fact that Grice never meant to advance a processing theory, in the first place. Taking our lead from Marr, we distinguish between two levels of explanation: at the W-level, we are concerned with what agents do and why; at the H-level, we ask how agents do whatever it is (...) they do. Whereas pragmatics is pitched at the W-level, processing theories are at the H-level. This is not to say that pragmatics has no implications for psychology at all, but it is to say that its implications are less direct than is often supposed. (shrink)

Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brainenvironmentbrain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.

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)

What makes a living system a living system? What kind of biological phenomenon is the phenomenon of cognition? These two questions have been frequently considered, but, in this volume, the authors consider them as concrete biological questions. Their analysis is bold and provocative, for the authors have constructed a systematic theoretical biology which attempts to define living systems not as objects of observation and description, nor even as interacting systems, but as self-contained unities whose only reference is to themselves. The (...) consequence of their investigations and of their living systems as self-making, self-referring autonomous unities, is that they discovered that the two questions have a common answer: living systems are cognitive systems, and living as a process is a process of cognition. The result of their investigations is a completely new perspective of biological (human) phenomena. During the investigations, it was found that a complete linguistic description pertaining to the ‘organization of the living’ was lacking and, in fact, was hampering the reporting of results. Hence, the authors have coined the word ‘autopoiesis’ to replace the expression ‘circular organization’. Autopoiesis conveys, by itself, the central feature of the organization of the living, which is autonomy. (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)

The Embodied Mind provides a unique, sophisticated treatment of the spontaneous and reflective dimension of human experience.

Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As such it is (...) not historically true that there has been a thoroughly entrenched and agreed upon conception of "cognition." Next, I take up mechanistic frameworks. Although 'mechanism' is an umbrella term for a set of loosely related characteristics, there are common features: linearity, localization, and component dominance. I then describe complexity science, with emphasis on its utilization of dynamical systems modeling. Next, I discuss two phenomena that typically fall under the purview of complexity science: nonlinearity and interaction dominance. -/- A complexity science framework guided by the theory of self-organized criticality and utilizing the methods of dynamical systems modeling can surmount a number of challenges that face mechanistic frameworks when investigating some kinds of cognition. The first challenge is epistemic and concerns the inadequacy of mechanistic frameworks to facilitate the comprehensibility of massive amounts of data across various scales and areas of inquiry. I argue that complexity science is more appropriate for making big data comprehensible when investigating cognition, particularly across disciplines. I demonstrate this via an approach called nested dynamical modeling (NDM). NDM can facilitate comprehensibility of large amounts of data obtained from various scales of investigation by eliminating irrelevant degrees of freedom of that system as relates to the target of investigation. -/- The second shortcoming concerns ontological blind spots within mechanistic frameworks. Cognitive phenomena like extended cognition often fail to meet most, if not all, of the criteria assumed by many mechanistic approaches, especially component dominance. I argue that research guided by the notion of interaction dominance allows for extended cognition to be a real, empirically supported phenomenon within complex systems frameworks. In this chapter I discuss some of my experimental work on extended cognitive systems. -/- The search for mechanisms can be a reasonable starting position when attempting to explain natural phenomena in the life sciences. However, too strict of an adherence to theoretical and methodological commitments such as linearity, localization, and component dominance can result in intractable epistemic challenges and ontological blind spots. Complexity science has theories and methods to overcome such challenges in the investigation of cognition. (shrink)

Much of cognitive neuroscience as well as traditional cognitive science is engaged in a quest for mechanisms through a project of decomposition and localization of cognitive functions. Some advocates of the emerging dynamical systems approach to cognition construe it as in opposition to the attempt to decompose and localize functions. I argue that this case is not established and rather explore how dynamical systems tools can be used to analyze and model cognitive functions without abandoning the use of decomposition and (...) localization to understand mechanisms of cognition. (shrink)