According to the computational theory of mind (CTM), mental capacities are explained by inner computations, which in biological organisms are realized in the brain. Computational explanation is so popular and entrenched that it’s common for scientists and philosophers to assume CTM without argument.

A mechanistic explanation is a desired outcome in many studies of perception. Such explanations require discovering the processes that contribute to the realization of a perceptual phenomenon at different levels of information processing. The present analysis aims at investigating the obstacles to develop such mechanistic explanations and their potential solutions in the context of psychopathology. Geometric-Optical Illusions (GOIs) are among perceptual phenomena that have been studied to understand psychopathology in various clinical populations. In the present analysis, the (...) GOIs will be discussed as a methodological tool in the investigation of the mechanistic approach to understanding perception in such populations. I will argue that the fact that most such studies are mainly focused on the investigation of susceptibility to GOIs can only lead to classifying such phenomena or to reporting some correlations between different aspects of such phenomena with certain brain activities, without formulating a mechanistic explanation. The investigation of the variables that mediate perceptual phenomena at earlier stages of information processing is required for the formulation of such explanations. Thus, the objective of the present analysis is twofold: 1) showing how ignoring such variables have prevented the formulation of mechanistic explanations of responses to GOIs in clinical populations, such as schizophrenia and autism, 2) analyzing the methodological aspects of an effective approach in which a top-down guidance based on phenomenological insights (the first-person data) along with the insights provided by the existing theories help overcome obstacles in developing mechanistic explanations of GOIs. (shrink)

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)

One assumption of the new mechanistic approach is that there are two kinds of mechanistic explanations: etiological and constitutive ones. While the former explain phenomena in terms of their preceding causes, the latter are supposed to refer to mechanisms that constitute phenomena. Based on arguments by Kaiser and Krickel (Br J Philos Sci 68(3):745–779, 2017) and Krickel (The mechanical world, vol. 13, Springer International Publishing, 2018), I will show that this view is too narrow. Indeed, three different types (...) of explanation are usually subsumed under the label “constitutive explanation”. However, one of those types of explanation is not a version of constitutive explanation. Rather it is a variant of etiological explanation. As a result, I will show that there are four types of mechanistic explanation, two variants of etiological explanation—which I will call output mechanistic explanations and input-output mechanistic explanations—and two variants of constitutive explanation—which I will call filler mechanistic explanations and dimensioned mechanistic explanations. Keeping these apart is crucial as they come with different ontological implications. An evaluation of the mechanistic approach regarding its stance on reduction, levels, and interlevel causation crucially depends on which notion of mechanistic explanation one has in mind. (shrink)

There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that (...) individual models do not provide mechanistic explanations by themselves. Instead, individual models are always used to complement a huge body of background information and pre-existing models about the target system. With this in mind, I argue that mechanistic explanations are distributed across sets of different, and sometimes contradictory, scientific models. Each of these models contributes limited, but essential, information to the same mechanistic explanation, but none can be considered a mechanistic explanation in isolation of the others. (shrink)

This chapter explores some of the ways that mechanisms are invoked in neuroscience and looks at a selection of the philosophical problems that arise when trying to understand mechanistic explanations. It introduces a series of historical case studies that illustrate how neuroscientists have depended on mechanistic metaphors in their efforts to understand the mind and brain, and how their mechanistic explanations have developed over time. The chapter highlights what contemporary philosophers have identified as the fundamental features (...) of mechanisms and mechanistic explanation. It considers some of the methodological issues that arise in neuroscience including how to integrate psychological with neural models, how to generalize findings in model organisms like the sea slug Aplysia to human learning and memory, and whether to favor top-down or bottom-up methods. Constructing multi-level mechanistic explanations involves intensive collaboration across different branches of science, and involves many challenges, both pragmatic and methodological. (shrink)

Resurgent interest in both mechanistic and counterfactual theories of explanation has led to a fair amount of discussion regarding the relative merits of these two approaches. James Woodward is currently the pre-eminent counterfactual theorist, and he criticizes the mechanists on the following grounds: Unless mechanists about explanation invoke counterfactuals, they cannot make sense of claims about causal interactions between mechanism parts or of causal explanations put forward absent knowledge of productive mechanisms. He claims that these shortfalls can (...) be offset if mechanists will just borrow key tenets of his counterfactual theory of causal claims. What mechanists must bear in mind, however, is that by pursuing this course they risk both the assimilation of the mechanistic theories of explanation into Woodward’s own favored counterfactual theory, and they risk the marginalization of mechanistic explanations to a proper subset of all explanations. An outcome more favorable to mechanists might be had by pursuing an actualist-mechanist theory of the contents of causal claims. While it may not seem obvious at first blush that such an approach is workable, even in principle, recent empirical research into causal perception, causal belief, and mechanical reasoning provides some grounds for optimism. (shrink)

The Extended Mind Thesis (EMT) is traditionally formulated against the bedrock of functionalism, and ongoing debates are typically bogged down with questions concerning the exact relationship between EMT and different versions of functionalism. In this paper, I offer a novel ally for EMT: the new mechanistic approach to explanation. I argue that the mechanistic framework provides useful resources not just to disambiguate EMT, and to show which objections fail to pose a serious challenge, but also to (...) answer some of the deeper problems that stem from the functionalist roots of EMT. (shrink)

Cognitive science, as an interdisciplinary research endeavour, seeks to explain mental activities such as reasoning, remembering, language use, and problem solving, and the explanations it advances commonly involve descriptions of the mechanisms responsible for these activities. Cognitive mechanisms are distinguished from the mechanisms invoked in other domains of biology by involving the processing of information. Many of the philosophical issues discussed in the context of cognitive science involve the nature of information processing. For philosophy of science, a central question is (...) what counts as a scientific explanation. But what is a mechanistic explanation and how does it work, how can philosophy of science use it as a solution for the problem of integration in cognitive science? By answering these questions and merging my answers with discussion of concepts of philosophy, normativity and generality, I will investigate the following claim. -/- I claim that philosophy by using strength concepts such as normativity, generality, and a mechanistic philosophy of explanations, can be a most important contributor to cognitive science. I also investigate how philosophy of science could be (can be) a bridge between psychology and neuroscience. We need a distinction between philosophy of cognitive science and philosophy in cognitive science; I am talking about the latter. -/- This claim is very important for the integration and the future of the interdisciplinary field known as cognitive science. -/- Philosophy as a true cognitive science -/- When the Cognitive Science Society was founded, in the late 1970s, philosophy, neuroscience, and anthropology were playing smaller roles. The three disciplines that formed the core group were artificial intelligence, psychology, and linguistics. The curious thing is that George Miller, a psychologist and an important founder of cognitive sciences in a hexagon diagram that he presented, put philosophy at the top of the diagram and neuroscience at the very bottom. There is enough agreement now that neuroscience is the most important contributor to cognitive science and there are fair connections between philosophy and neuroscience. In that diagram there was almost no connection between philosophy and neuroscience. -/- The developments and rise of cognitive science in the last half-century has been accompanied by considerable amount of philosophical activity. Perhaps no other area within analytic philosophy in the second half of that period has attracted more attention or produced more publications. (Bechtel and Graham, 1998. Rumelhart and Bly 1999. Bechtel, Mandik, Mundale 2001. Thagard, 2007. Bennett and Dennett et al, 2007. Bennett and Hacker, 2008. Andler, 2009. Frankish and Ramsey, 2012.) -/- Many philosophers of science offer conclusions that have a direct bearing on cognitive science and its practitioners can profit from closer engagement with the rest of cognitive science. For example, William Bechtel has discussed three projects, two in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years, that he contends, can make theoretical and methodological contributions to cognitive science (Bechtel, 2009). Paul Thagard is another example of the mentioned emerging school of philosophers of science that define cognitive science as the interdisciplinary investigation of mind and intelligence (Thagard, 2006). Thagard by presenting some general but important philosophical questions such as, “What is the nature of the explanations and theories developed in cognitive science?”, and by providing answers to these central questions has showed how philosophy of science can help cognitive science by the advantage of its generality. Andrew Brook, however, believes that philosophical approaches have never had a settled place in cognitive science but he is listed in a group of the philosophers of science that they are contributing very closely the cognitive science (Brook, 2009). Daniel Dennett , as well as being a member the mentioned naturalistic philosophers of science, believes that there is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science. -/- What are mechanisms? Let us begin abstractly before considering an example. Mechanisms are collections of entities and activities organized together to do something (cf. Machamer, Darden, & Craver, 2000; Craver & Darden, 2001; Bechtel &Richardson, 1993; Glennan, 1996). These explanations are known as ‘mechanistic explanations’. By using and developing these mechanistic explanations of philosophy of science one can draw normative consequences for cognitive science. Paul Thagard (Thagard, 2006 and 2009), William Bechtel (Bechtel, 2008 and 2009), Andrew Brook (Brook, 2008) investigated and promoted using the ‘normativity’ in philosophy to show a better and crucial role for philosophy of science in an interdisciplinary known as cognitive science. Some philosophers have thought that, in order to pursue this normative function, philosophy must distance itself from empirical matters, but there are examples where the investigations of descriptive and normative issues go hand in hand. ( Thagard, 2009). -/- I will investigate how we can reduce a higher-level science such as psychology to neuroscience without the problems of reductionism but via mechanistic explanations. By problem I mean psychology does not lose its autonomy. -/- Conclusion -/- If cognitive science is all about understanding the human mind, or if cognitive science is the interdisciplinary investigation of mind and intelligence, since the whole life of philosophy was involving with the ways of knowing (epistemology) and conceptions of reality (metaphysics), also philosophy has considered the so-called mind-body problem ( identity theory, functionalism, and heuristic identity theory) , then philosophy could be the most deserved discipline to be a most contributor in cognitive science. I tried to discuss this by using the three advantages in philosophy, normativity, and generality and by introducing an emerging school of mechanistic (not mechanical) philosophers. One thing left, as cognitive science is a two-way street, philosophers need also to stop in a station of cognitive science and learn from the most important advances in brain and neuroscience. -/- . (shrink)

One of the main early forms of “functionalism,” developed by writers like Jerry Fodor and William Lycan, focused on “mechanistic” explanation in the special sciences and argued that “functional properties” in psychology were continuous in nature with the special science properties posited in such mechanistic explanations. I dub the latter position“Continuity Functionalism” and use it to critically examine the “Standard Picture” of the metaphysics of functionalism which takes “functional” properties to be second-order properties and claims there are (...) two metaphysical forms of “functionalism,” in so-called “role” and “realizer” functionalism. Looking at mechanistic explanations, I show that the “functional properties” posited in the special sciences are not second-order properties and that Continuity Functionalism is a distinctive metaphysical version of functionalism not covered by the Standard Picture. My conclusion is that the Standard Picture offers us a false dichotomy of ways to be a “functionalist” and that “functionalists” thus need to look once more to the special sciences to configure their views, thus eschewing the machinery inherited from “analytic” philosophers. (shrink)

Arguments for the autonomy of psychology or other higher-level sciences have often taken the form of denying the possibility of reduction. The form of reduction most proponents and critics of the autonomy of psychology have in mind is theory reduction. Mechanistic explanations provide a different perspective. Mechanistic explanations are reductionist insofar as they appeal to lower-level entities—the component parts of a mechanism and their operations— to explain a phenomenon. However, unlike theory reductions, mechanistic explanations also recognize (...) the fundamental role of organization in enabling mechanisms to engage their environments as units (as well as the role of yet higher-level structures in constraining such engagement). Especially when organization is non-linear, it can enable mechanisms to generate phenomena that are quite surprising given the operations of the components taken in isolation. Such organization must be discovered—it cannot simply be derived from knowledge of lower-level parts and their operations. Moreover, the organized environments in which mechanisms operate must also be discovered. It is typically the higher-level disciplines that have the tools for discovering the organization within and between mechanisms. Although these inquiries are constrained by the knowledge of the parts and operations constituting the mechanism, they make their own autonomous contribution to understanding how a mechanism actually behaves. Thus, mechanistic explanations provide a strong sense of autonomy for higher levels of organization and the inquiries addressing them even while recognizing the distinctive contributions of reductionistic research investigating the operations of the lower level components. (shrink)

Recently the functional model of reduction has become something like the standard model of reduction in philosophy of mind. In this paper, I argue that the functional model fails as an account of reduction due to problems related to three key concepts: functionalization, realization and causation. I further argue that if we try to revise the model in order to make it more coherent and scientifically plausible, the result is merely a simplified version of what in philosophy of science (...) is known as mechanistic explanation. Hence, instead of analyzing reduction in philosophy of mind in terms of functional reduction, it should be analyzed in terms of mechanistic explanation. (shrink)

Wegner, Giuliano, and Hertel (1985) defined the notion of a transactive memory system (TMS) as a group level memory system that “involves the operation of the memory systems of the individuals and the processes of communication that occur within the group (p. 191). Those processes are the collaborative procedures (“transactions”) by which groups encode, store, and retrieve information that is distributed among their members. Over the past 25+ years, the conception of a TMS has progressively garnered an increased interest among (...) social and organizational psychologists, communication scholars, and management theorists (Ren & Argote 2011). But there remains considerable disagreement about how exactly Wegner’s appeal to group memory should be understood. My goal in this paper is contribute to this debate, by articulating more clearly the value of conceptualizing groups as TMSs. This value, I argue, consists in providing us with a blueprint for how to explain group memory in terms of collective information-processing mechanisms. Collective information-processing mechanisms are dependent on, and interact with, the brain-bound information-processing of individuals, but cannot be reduced to the latter. In my analysis, I lean on extant accounts of mechanistic explanation in the philosophy of science (Bechtel & Richardson 1993; Machamer, Darden, & Craver 2000; Wimsatt 2007) that have been used to analyze the explanatory practices of psychology and cognitive neuroscience (Bechtel 2008, 2009). Based on my reconstruction of Wegner’s conceptualization of a TMS, I argue that the reality of emergent group cognition is compatible with its mechanistic explanation. More generally, my analysis shows that group cognition cannot be reduced to individual cognition, while avoiding the false dilemma between “wholism” and “nothing but-ism” which has hampered traditional construals of the “group mind” thesis (Allport 1968). (shrink)

Context: Challenges by embodied, enactive, extended and ecological approaches to cognition have provided good reasons to shift away from neurocentric theories. Problem: Classic cognitivist accounts tend towards internalism, representationalism and methodological individualism. Such accounts not only picture the brain as the central and almost exclusive mechanism of cognition, they also conceive of brain function in terms that ignore the dynamical relations among brain, body and environment. Method: I review four areas of research where enactivist accounts have shown alternative ways of (...) thinking about the brain. Results: Taken together, such analyses form a comprehensive alternative to the classic conceptions of cognitivist, computational neuroscience. Implications: Such considerations motivate the need to re-think our understanding of how the brain itself works. They suggest that the best explanation of brain function may be found in the mixed vocabularies of embodied and situated cognition, developmental psychology, ecological psychology, dynamic systems theory, applied linguistics, the theory of affordances and material engagement, rather than the narrow vocabulary of computational neuroscience. Constructivist content: This account is consistent with an enactivist-constructivist approach to cognition. (shrink)

de Bruin & Gallagher suggest that the view of embodied simulation put forward in our recent article lacks explanatory power. We argue that the notion of reuse of mental states represented with a bodily format provides a convincing simulational account of the mirroring mechanism and its role in mind -reading.

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, (...) we make some recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (shrink)

The notion of reduction continues to play a key role in philosophy of mind and philosophy of cognitive science. Supporters of reductionism claim that psychological properties or explanations reduce to neural properties or explanations, while antireductionists claim that such reductions are not possible. In this book, I apply recent developments in philosophy of science, particularly the mechanistic explanation paradigm and the interventionist theory of causation, to reassess the traditional approaches to reduction in philosophy of mind. I (...) then elaborate and defend a pluralistic framework for philosophy of mind, and show how reductionist ideas can be incorporated into it. This leads to a novel synthesis of pluralism and reductionism that I call pluralistic physicalism. (shrink)

Upshot: The computational theory of mind has been elaborated in many different ways throughout the last decades. In Explaining the Computational Mind, Milkowski defends his view that the mind can be explained as computational through his defense of mechanistic explanation. At no point in this book is there explicit mention of constructivist approaches to this topic. We will, nevertheless, argue that it is interesting for constructivist readers.

Biological processes are often explained by identifying the underlying mechanisms that generate a phenomenon of interest. I characterize a basic account of mechanistic explanation and then present three challenges to this account, illustrated with examples from molecular biology. The basic mechanistic account is insufficient for explaining nonsequential and nonlinear dynamic processes, is insufficient for explaining the inherently stochastic nature of many biological mechanisms, and fails to give a proper framework for analyzing organization. I suggest that biological processes (...) are best approached as a multidimensional gradient—with some processes being paradigmatic cases of mechanisms and some being marginal cases. (shrink)

I introduce and defend verbialism, a metaphysical framework appropriate for accommodating the mind within the natural sciences and the mechanistic model of explanation that ties the natural sciences together. Verbialism is the view that mental phenomena belong in the basic ontological category of activities. If mind is what brain does, then explaining the mind is explaining how it occurs, and the ontology of mind is verbialist -- at least, it ought to be. I motivate (...) verbialism by revealing a kind of inattentional blindness philosophers of mind have shown when it comes to conceiving of their explanandum as a kind of complex activity. I also show how the project of naturalizing the mind is altered when we correct for this inattention. (shrink)

This paper considers Margaret Cavendish's distinctive anti-mechanist materialism, focusing on her 1664 Philosophical Letters, in which she discusses the views of Hobbes, Descartes, and More, among others. The paper examines Cavendish's views about natural, material souls: the soul of nature, the souls of finite individuals, and the relation between them. After briefly digressing to look at Cavendish's views about divine, supernatural souls, the paper then turns to the reasons for Cavendish's disagreement with mechanist accounts. There are disagreements over the (...) class='Hi'>explanation of particular phenomena, but also a broader disagreement over what to take as one's most basic causal model. (shrink)

I argue that psychologists interested in human causal judgment should understand and adopt a representation of causal mechanisms by directed graphs that encode conditional independence (screening off) relations. I illustrate the benefits of that representation, now widely used in computer science and increasingly in statistics, by (i) showing that a dispute in psychology between ‘mechanist’ and ‘associationist’ psychological theories of causation rests on a false and confused dichotomy; (ii) showing that a recent, much-cited experiment, purporting to show that human subjects, (...) incorrectly let large causes ‘overshadow’ small causes, misrepresents the most likely, and warranted, causal explanation available to the subjects, in the light of which their responses were normative; (iii) showing how a recent psychological theory (due to P. Cheng) of human judgment of causal power can be considerably generalized: and (iv) suggesting a range of possible experiments comparing human and computer abilities to extract causal information from associations. (shrink)

In this thesis I examine a number of topics that bear on explanation and understanding in molecular and cell biology, in order to shed new light on explanatory practice in those areas and to find novel angles from which to approach relevant philosophical debates. The topics I look at include mechanism, emergence, cellular complexity, and the informational role of the genome. I develop a perspective that stresses the intimacy of the relations between ontology and epistemology. Whether a phenomenon looks (...) mechanistic, or complex, or indeed emergent, is largely an epistemic matter, yet has an objective basis in features of the world. After reviewing several concepts of mechanism I consider the influential recent account of Machamer, Darden and Craver (MDC). That account makes interesting proposals concerning the relationship between mechanistic explanation and intelligibility, which are consistent with the results of the investigation I undertake into the science surrounding protein folding. In relation to a number of other issues pertaining to biological systems I conclude that the MDC account is insufficiently nuanced, however, leading me to outline an alternative approach to mechanism. This emphasizes the importance of structure—function relations and addresses issues raised by reflection on the nature of cellular complexity. These include the distinction between structure and process and the different possible bases on which system organization may be maintained. The account I give of emergence construes the phenomenon in terms of psychological deficit: phenomena are emergent when we lack the capacity to trace through and model their causal structures using our cognitive schemas. I conclude by developing these ideas into a preliminary and partial account of explanation and understanding. This aspires to cover the significant fraction of work in molecular and cell biology that correlates biological structures, processes and functions by visualizing phenomena and making them imaginable. (shrink)

Recent findings in different areas of psychology and cognitive science have brought the unconscious mind back to center stage. However, the unconscious mind worry remains: What renders unconscious phenomena mental? I suggest a new strategy for answering this question, which rests on the idea that categorizing unconscious phenomena as “mental” should be scientifically useful relative to the explanatory research goals. I argue that this is the case if by categorizing an unconscious phenomenon as “mental” one picks out explanatorily (...) relevant similarities to a corresponding paradigmatically mental conscious phenomenon. Explanatory relevance is spelled out in terms of mechanistic norms. (shrink)

From a cognitive point of view, the adhesion to religious beliefs, especially those involving adult subjects, are quite mysterious. Religious representations entail paradoxical claims that should imply skepticism or cautious doubts in any rational mind. Nevertheless, it is not rare that they prompt an act of total commitment from the converts. The aim of this paper is to propose a naturalist explanation of the conversion phenomenon. The argument relies on the postulated existence of an emotional signal selected by (...) evolution to motivate the child to look for the underlying structure of the world by providing a strong positive feeling when a solution is found. By the use of different examples of historical conversions, the author shows how this emotional mechanism can be triggered in the presence of religious representations, causing in the subjects the feeling that they have discovered a good solution to problems they were confronted with. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects (...) of scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

Rakover has thought about the nature of explanation for a long time and he has written some insightful pieces on the possibility of incorporating mentalistic language into serious explanations of our activities. Here he takes an extreme tack and grounds his arguments on the oldest of all chestnuts, the mind/body problem. Ironically, as an undergraduate he may have misinterpreted the words of his favorite professor so as to lead him to agonize for decades over the proper interpretation of (...) private experience [for him it’s “mentalistic”]. This has ultimately led to this article, proposing a Multi-Explanation Framework that mixes what he calls “mentalistic” and “mechanistic” elements in behavioral sequences, incorporating a Mentalistic Purposive Explanation Scheme that has the virtue, in his eyes, of adding what “radical behaviorism” lacks. The reader is left with the impression that the explanations produced using this framework would seem more satisfying only because the vocabulary involved is the one we learned as children, and that their usefulness would be no more than that of the folk psychology that has always prevailed. Rakover and many others confuse radical behaviorism with behavior analysis, which leads to tiresome and pointless critiques of the former. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with (...) content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with (...) content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient (e.g., mental) properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

This paper argues that in some explanations mathematics are playing an explanatory rather than a representational role, and that this feature unifies many types of non-causal or non-mechanistic explanations that some philosophers of science have been recently exploring under various names. After showing how mathematics can play either a representational or an explanatory role by considering two alternative explanations of a same biological pattern—“Bergmann’s rule”—I offer an example of an explanation where the bulk of the explanatory job is (...) done by a mathematical theorem, and where mechanisms involved in the target systems are not explanatorily relevant. Then I account for the way mathematical properties may function in an explanatory way within an explanation by arguing that some mathematical propositions involving variables non directly referring to the target system features constitute constraints to which a whole class of systems should comply, provided they are describable by a mathematical object concerned by those propositions. According to such “constraint account”, those mathematical facts are directly entailing the explanandum, as a consequence of such constraints. I call those explanations “structural”, because here properties of mathematical structures are accounting for the explanandum; various kinds of mathematical structures thereby define various types of structural explanations. (shrink)

Explanations in behavioural neuroscience are often said to be mechanistic in the sense that they explain an organism’s behaviour by describing the activities and organisation of the organism’s parts that are “constitutively relevant” to organism behaviour. Much has been said about the constitutive relevance of working parts (in debates about the so-called “mutual manipulability criterion”), but relatively little has been said about the constitutive relevance of the organising relations between working parts. Some New Mechanists seem to endorse a simple (...) causal-linking account: organising relations are constitutively relevant to organism behaviour if and only if (and because) they are causal relations that link the working parts that are constitutively relevant to organism behaviour. In this paper, I argue that the causal-linking account is inadequate because it neglects the constitutive relevance of anatomical relations that organise the working parts of a behaving organism. I demonstrate this by considering a case study where the anatomical organisation of the barn owl (Tyto alba) is constitutively relevant to their mechanism for sound localization. The anatomical organisation of this mechanism is best understood as the back-and-forth flow of task information across 7 “levels of anatomy” (a notion that I distinguish from levels of mechanism). A further implication, I conclude, is that at least some of the interlevel structure of neuroscientific explanation is accounted for by levels of anatomy, not levels of mechanism. (shrink)

his monograph examines the metaphysical commitments of the new mechanistic philosophy, a way of thinking that has returned to center stage. It challenges a variant of reductionism with regard to higher-level phenomena, which has crystallized as a default position among these so-called New Mechanists. Furthermore, it opposes those philosophers who reject the possibility of interlevel causation. Contemporary philosophers believe that the explanation of scientific phenomena requires the discovery of relevant mechanisms. As a result, new mechanists are, in the (...) main, concerned solely with epistemological questions. But, the author argues, their most central claims rely on metaphysical assumptions. Thus, they must also take into account metaphysics, a system of thought concerned with explaining the fundamental nature of being and the world around it. This branch of philosophy does indeed matter to the empirical sciences. The chapters investigate the nature of mechanisms, their components, and the ways in which they can bring about different phenomena. In addition, the author develops a novel account of causation in terms of activities. The analysis provides the basis for many further research projects on mechanisms and their relations to, for example, the mind-body problem, realization, multiple realization, natural kinds, causation, laws of nature, counterfactuals, and scientific levels. (shrink)

Nine lead papers, all with two or three commentators, and six with replies to the commentators. It is the Identity theorists cum cybernetician versus the "non-Cartesian dualists" and C. D. Broad-style interactionists. The most sparks are generated with MacKay's paper, "From Mechanism to Mind," and the ensuing exchange between MacKay and Beloff; MacKay's paper is intended as a summary of his work in cybernetics as it relates to the philosophy of mind, and Beloff's criticisms range from the cautious (...) to the devastating. Beloff's own paper is a well-ordered, rear-guard action against the Identity theory, which fastens on the dual nature of consciousness and para-psychological phenomena as the theory's present obstacles. Flew's "A Rational Animal" is an incisive challenging of what he dubs the "Co-existence Thesis," i.e., the view defended by such people as Winch and MacIntyre, that explanations by reasons and explanations by causes, or, in another idiom, teleological and mechanical explanations, can exist together in irreducible harmony—even given the ideal of a unified science. It should be mentioned that Price's paper is the bulk of his 1952 lecture before the Members of the Society for Psychical Research, "Survival and the Idea of 'Another World.'"—E. A. R. (shrink)

In this article we propose an extended approach in terms of Cognitive Pragmatics (CP) to the explanation of the development of the higher cognitive processes. Therefore, we explain in terms of CP how linguistic and pre-linguistic social practices shape the mind. CP, as we understand it here presents a broader transdisciplinary position covering developmental psychology, primatology, comparative psychology, cultural psychology, anthropology and philosophy. We present an argumentation for the thesis that CP provides an explanation to the origins (...) and developmental mechanisms of some of higher mental functions unique to humans. Thus, we want to extend the notion of CP beyond its standard definition by emphasizing the transformative component of communicative acts. In our approach, CP first and foremost examines the cognitive mechanisms underlying social pre-linguistic and linguistic communication. Secondly, it explores how this communication reorganizes and transforms cognitive abilities and processes. We would like to extend the tasks of CP as well, because its goal is to not only describe cognitive processes that enable communication, but also to explain the social mechanisms of transformation of mind and cognition. We provide an example of said mechanisms of development of higher cognitive functions through the account of metacognition. (shrink)

Bruineberg and colleagues highlight work using Markov blankets to demarcate the bounds of the mind. This echoes earlier attempts to demarcate the bounds of the mind from a dynamical systems perspective. Advocates of mechanistic explanation have challenged the dynamical approach to independently motivate the application of the formalism, a challenge that Markov blanket theorists must also meet.

The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of (...) processes at the level at which cognitive theories attempt to function: One is drawn from too low a level, the other from too high a level. If there is a distinctly cognitive level, then we still need to determine what are the basic organizational principles at that level. (shrink)

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and (...) outline some promising answers that are being developed by a number of authors. (shrink)

This book aims to understand human cognition and psychology through a comprehensive computational theory of the human mind, namely, a computational "cognitive architecture". The goal of this work is to develop a unified framework for understanding the human mind, and within the unified framework, to develop process-based, mechanistic explanations of a large variety of psychological phenomena. Specifically, the book first describes the essential Clarion framework and its cognitive-psychological justifications, then its computational instantiations, and finally its applications to (...) capturing, simulating, and explaining various psychological phenomena and empirical data. The book shows how the models and simulations shed light on psychological mechanisms and processes through the lens of a unified framework.In fields ranging from cognitive science, to psychology, to artificial intelligence, and even to philosophy, researchers, graduate and undergraduate students, and practitioners of various kinds may have interest in topics covered by this book. The book may also be suitable for seminars or courses, at graduate or undergraduate levels, on cognitive architectures or cognitive modeling. (shrink)

Intentionalism is a research program that seeks to explain facts about meaning and communication in psychological terms, with our capacity for intention recognition playing a starring role. My aim here is to recommend a methodological reorientation in this program. Instead of a focus on intuitive counterexamples to proposals about necessary-and-sufficient conditions, we should aim to investigate the psychological mechanisms whose activities and interactions explain our capacity to communicate. Taking this methodologi- cal reorientation to heart, I sketch a theory of the (...) cognitive architecture underlying language use that I have defended elsewhere. I then show how this theory can be used to give an account of non-communicative language use—a phenomenon that has long posed a challenge to intentionalism. (shrink)

This book is an excellent collection of papers which partly spring from, and partly bear on the Study Group on the Unity of Knowledge held in various universities, October, 1967-March, 1970. The papers all bear on the problem of reduction. In "Unity of Physical Law and Levels of Description," Ilya Prigogine argues that organized structures need physical laws of organization, not of entropy only, to explain their genesis and operation." The editor’s paper, "Reducibility: Another Side Issue," argues, following Polanyi, that (...) living things as machines already transcend physics, since they demand both chemical and engineering principles for their explanation." "How is Mechanism Conceivable?" points out that ordinary ways of talking about and explaining behavior, i.e., as involving intention and purpose, differs in logic from mechanistic explanation. But this difference in logic of the two languages is "never an obstacle to the reduction of one theory to another, indeed, there is always such a noncongruence of the conceptual mesh." Anthony J. P. Kenny’s "The Homunculus Fallacy" argues against "the reckless application of human-being predicates to insufficiently human-like objects." In "Behavior, Belief, and Emotion," A. C. MacIntyre argues for the thesis that "there is no necessary connection between at least some emotions and particular forms of behavior." In "The Critique of Artificial Reason," H. Dreyfus criticizes both the empirical and a priori arguments for optimism underlying the work in artificial intelligence. It displays the underlying philosophical assumption inherent in Western philosophical tradition since Plato. The last two papers concern Polanyi’s theory of knowledge. In "Tacit Knowledge and the Concept of Mind," W. T. Scott shows how Ryle’s "Concept of Mind can be significantly extended by considering certain features of the philosophical position that Michael Polanyi has developed around the concept of tacit knowing." R. S. Cohen’s "Tacit, Social and Hopeful" discusses the difficulties in Polanyi’s epistemology and the merits of the logical reconstruction work in science. Only the papers by Dreyfus and Scott have been previously published. Throughout the collection, the editor has provided useful introductory remarks focusing upon the unifying themes in the collection.—A. S. C. (shrink)

This paper presents a new approach to resolving an apparent tension in Descartes’ discussion of scientific theories and explanations in the Principles of Philosophy. On the one hand, Descartes repeatedly claims that any theories presented in science must be certain and indubitable. On the other hand, Descartes himself presents an astonishing number of speculative explanations of various scientific phenomena. In response to this tension, commentators have suggested that Descartes changed his mind about scientific theories having to be certain and (...) indubitable, that he lacked the conceptual resources to describe the appropriate epistemic attitude towards speculative theories, or that the presence of geometrical principles in these explanations guarantee their certainty. I argue that none of these responses is satisfactory and suggest a different resolution to the tension by examining Descartes’ notion of explanation. On Descartes’ view, providing an adequate explanation does not require being certain of the theories that constitute the explanans. Relatedly, the purpose of Cartesian explanations is not to discover the truth about the various underlying mechanisms that such explanations appeal to, but to support his general philosophical thesis that all natural phenomena can be explained by appealing to the extension of matter. (shrink)

The biological sciences study (bio)complex living systems. Research directed at the mechanistic explanation of the "live" state truly requires a pluralist research program, i.e. BioComplexity research. The program should apply multiple intra-level and inter-level theories and methodologies. We substantiate this thesis with analysis of BioComplexity: metabolic and modular control analysis of metabolic pathways, emergence of oscillations, and the analysis of the functioning of glycolysis.

Jon Elster worries about the explanatory power of the social sciences. His main concern is that they have so few well-established laws. Elster develops an interesting substitute: a special kind of mechanism designed to fill the explanatory gap between laws and mere description. However, his mechanisms suffer from a characteristic problem that I will explore in this article. As our causal knowledge of a specific problem grows we might come to know too much to make use of an Elsterian mechanism (...) but still lack a law. We might then find ourselves in the paradoxical position of knowing more relevant causal truths about the phenomenon we are interested in than we did before, but being able to explain less. If this possibility is realized in social science settings, as I argue it might well be, Elster?s mechanistic account is threatened. Moreover, even if the possibility is rarely realized in that way, it raises, simply as a possibility, a conceptual problem with Elster?s mechanistic framework. (shrink)

In this article we analyze the methodological commitments of a radical embodied cognition approach to social interaction and social cognition, specifically with respect to the explanatory framework it adopts. According to many representatives of REC, such as enactivists and the proponents of dynamical and ecological psychology, sociality is to be explained by focusing on the social unit rather than the individuals that comprise it and establishing the regularities that hold on this level rather than modeling the sub-personal mechanisms that could (...) be said to underlie social phenomena. We point out that, despite explicit commitment, such a view implies an implicit rejection of the mechanistic explanation framework widely adopted in traditional cognitive science, which, in our view, hinders comparability between REC and these approaches. We further argue that such a position is unnecessary and that enactive mechanistic explanation of sociality is both possible and desirable. We examine three distinct objections from REC against mechanistic explanation, which we dub the decomposability, causality and extended cognition worries. In each case we show that these complaints can be alleviated by either appreciation of the full scope of the mechanistic account or adjustments on both mechanistic and REC sides of the debate. (shrink)

Recently, some mechanists have embraced reductionism and some reductionists have endorsed mechanism. However, the two camps disagree sharply about the extent to which mechanistic explanation is a reductionistic enterprise. Reductionists maintain that cellular and molecular mechanisms can explain mental phenomena without necessary appeal to higher-level mechanisms. Mechanists deny this claim. I argue that this dispute turns on whether reduction is a transitive relation. I show that it is. Therefore, mechanistic explanations at the cellular and molecular level explain (...) mental phenomena. I make my case in part by noting that mechanisms at higher levels are composed of mechanisms at lower levels. Compositional relations are transitive. In addition, they are explanatory. I conclude that there are explanatory linkages from cellular and molecular mechanisms to mental phenomena within a hierarchy of nested mechanisms. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids (...) certain objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophical discussions of systems biology have enriched the notion of mechanistic explanation by pointing to the role of mathematical modeling. However, such accounts still focus on explanation in terms of tracking a mechanism's operation across time (by means of mental or computational simulation). My contention is that there are explanations of molecular systems where the explanatory understanding does not consist in tracking a mechanism's operation and productive continuity. I make this case by a discussion of bifurcation analysis (...) in dynamical systems, articulating the distinctive way in which explanatory understanding is provided, especially about the reversibility or irreversibility of molecular processes. (shrink)