An increasing number of philosophers have promoted the idea that mechanism provides a fruitful framework for thinking about the explanatory contributions of computational approaches in cognitive neuroscience. For instance, Piccinini and Bahar :453–488, 2013) have recently argued that neural computation constitutes a sui generis category of physical computation which can play a genuine explanatory role in the context of investigating neural and cognitive processes. The core of their proposal is to conceive of computational explanations in cognitive neuroscience as a subspecies (...) of mechanistic explanations. This paper identifies several challenges facing their mechanistic account and sketches an alternative way of thinking about the epistemic roles of computational approaches used in the study of brain and cognition. Drawing on examples from both low-level and systems-level computational neuroscience, I argue that at least some computational explanations of neural and cognitive processes are partially independent from mechanistic constraints. (shrink)

This article focuses on emergence in social systems. The author begins by proposing a new tool to explore the mechanisms of social emergence: multi agent–based computer simulation. He then draws on philosophy of mind to develop an account of social emergence that raises potential problems for the methodological individualism of both social mechanism and of multi agent simulation. He then draws on various complexity concepts to propose a set of criteria whereby one can determine whether a given social mechanism generates (...) emergent properties, in the sense that their explanation cannot be reduced to a mechanistic account of individuals and their interactions. This combined account helps to resolve the competing claims of methodological individualists and social realists. The author’s conclusion is that the scope of mechanistic explanation may be limited due to the extreme complexity of many social systems. Key Words: emergence • mechanism • computer simulation • methodological individualism • social realism. (shrink)

I explore a type of computational social simulation known as artificial societies. Artificial society simulations are dynamic models of real-world social phenomena. I explore the role that these simulations play in social explanation, by situating these simulations within contemporary philosophical work on explanation and on models. Many contemporary philosophers have argued that models provide causal explanations in science, and that models are necessary mediators between theory and data. I argue that artificial society simulations provide causal mechanistic explanations. I conclude that (...) in their current form, these simulations are based on methodologically individualist assumptions that could limit their potential scope of social explanation. (shrink)

Computational explanations focus on information processing required in specific cognitive capacities, such as perception, reasoning or decision-making. These explanations specify the nature of the information processing task, what information needs to be represented, and why it should be operated on in a particular manner. In this article, the focus is on three questions concerning the nature of computational explanations: What type of explanations they are, in what sense computational explanations are explanatory and to what extent they involve a special, “independent” (...) or “autonomous” level of explanation. In this paper, we defend the view computational explanations are genuine explanations, which track non-causal/formal dependencies. Specifically, we argue that they do not provide mere sketches for explanation, in contrast to what for example Piccinini and Craver :283–311, 2011) suggest. This view of computational explanations implies some degree of “autonomy” for the computational level. However, as we will demonstrate that does not make this view “computationally chauvinistic” in a way that Piccinini or Kaplan :339–373, 2011) have charged it to be. (shrink)

Our aim in the present paper is to approach the nature of life from the perspective of autonomy, showing that this perspective can be helpful for overcoming the traditional Cartesian gap between the physical and cognitive domains. We first argue that, although the phenomenon of life manifests itself as highly complex and multidimensional, requiring various levels of description, individual organisms constitute the core of this multifarious phenomenology. Thereafter, our discussion focuses on the nature of the organization of individual living entities, (...) proposing autonomy as the main concept to grasp it. In the second part of the article we show how autonomy is also fundamental to explaining major evolutionary transitions, in an attempt to rethink evolution from the point of view of the organizational structure of the entities/organisms involved. This gives further support to the idea of autonomy not only as a key to understanding life in general but also the complex expressions of it that we observe on our planet. Finally, we suggest a possible general principle that underlies those evolutionary transitions, which allow for the open-ended redefinition of autonomous systems: namely, the relative dynamic decoupling that must be articulated among distinct parts, modules or modes of operation in these systems. (shrink)

Malware has been around since the 1980s and is a large and expensive security concern today, constantly growing over the past years. As our social, professional and financial lives become more digitalised, they present larger and more profitable targets for malware. The problem of classifying and preventing malware is therefore urgent, and it is complicated by the existence of several specific approaches. In this paper, we use an existing malware taxonomy to formulate a general, language independent functional description of malware (...) as transformers between states of the host system and described by a trust relation with its components. This description is then further generalised in terms of mechanisms, thereby contributing to a general understanding of malware. The aim is to use the latter in order to present an improved classification method for malware. (shrink)

In this paper, we address the question whether a mechanistic approach can account for evolutionary causes. The last decade has seen a major attempt to account for natural selection as a mechanism. Nevertheless, we stress the relevance of broadening the debate by including the other evolutionary causes inside the mechanistic approach, in order to be a legitimate conceptual framework on the same footing as other approaches to evolutionary theory. We analyse the current debate on natural selection as a mechanism, and (...) extend it to the rest of the evolutionary causes. We focus on three approaches that we call the stochastic view, the functional view, and the minimalist view. We argue that all of them are unable to account for evolutionary causes as mechanisms. It is concluded that the current mechanistic proposals cannot be accepted as a common framework for evolutionary causes. Finally, we outline some guidelines and requirements that any mechanistic proposal should meet in order to be applied to evolutionary theory. (shrink)

Teleosemantics explains mental representation in terms of etiological history: a mental state’s representational contents are the result of natural selection, or some other selection process. Critics have argued that the “swampman” thought experiment poses a counterexample to teleosemantics. In several recent papers, Papineau has argued that a merely possible swampman cannot serve as a counterexample to teleosemantics, but has acknowledged that actual swampmen would pose a problem for teleosemantics. In this paper, I argue that there are real-world cases of swampman-like (...) representation, in the form of functional tetrachromacy. People with functional tetrachromacy are born with four types of cones in each eye, rather than the usual three, and as a result can represent a wider variety of colors than the average person. I argue that the functional tetrachromat’s additional color representations are not the result of a selection process. Functional tetrachromacy is therefore a real-world case of mental representation without an etiological history, and therefore poses a genuine counterexample to teleosemantics. (shrink)

This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic tools for (...) the improvement of empirically-riven work in the debates about mechanistic explanation of ecological phenomena. (shrink)

My topic is the confluence of two recently active philosophical research programs. One research program concerns the metaphysics of realization. The other research program concerns scientific explanation in terms of mechanisms. In this paper I introduce a distinction between descriptive and explanatory approaches to realization. I then use this distinction to argue that a well-known account of realization, due to Carl Gillett, is incompatible with a well-known account of mechanistic explanation, due to Peter Machamer, Lindley Darden, and Carl Craver (MDC, (...) Philos Sci 57: 1-25, 2000). This is surprising, not least of which because Gillett has cited MDC's work as evidence that his account of realization is the right way to think about realization in the sciences. (shrink)

This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...) It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr’s theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (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)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...) justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...) properties. Finally, I briefly illustrate how my account sheds light on some issues in the history and philosophy of computing as well as the philosophy of mind. (shrink)

Although the literature on the issue of pluralism within the philosophy of science is very extensive, this paper focuses on the metaphysical causal pluralism that emerges from the new mechanistic discussion on causality. The main aim is to situate the new mechanistic views on causation within the account of varieties of causal pluralism framed by Psillos ( 2009 ). Paying attention to his taxonomy of metaphysical views on causation (i.e., the straightjacket view, the functional view, the two-concept view, the agnostic (...) view and the atheist view) will help clarify differences in opinion and, at the same time, make it possible to elucidate the main metaphysical theses present within the new mechanistic debate. Special attention is given to S. Glennan’s theory of causation, since it is unique in offering an overall metaphysical view of the issue. It is also argued that mechanists are not “atheists” on causation: while all of them are causal realists, most mechanists are “agnostic” on causation, with a few exceptions such as S. Glennan, P. Machamer and J. Bogen. (shrink)

Functional language is ubiquitous in ecology, mainly in the researches about biodiversity and ecosystem function. However, it has not been adequately investigated by ecologists or philosophers of ecology. In the contemporary philosophy of ecology we can recognize a kind of implicit consensus about this issue: while the etiological approaches cannot offer a good concept of function in ecology, Cummins’ systemic approach can. Here we propose to go beyond this implicit consensus, because we think these approaches are not adequate for ecology. (...) We argue that a sound epistemological framework to function in ecology is to be found in organizational approaches. In this line, we define function in ecology as a precise effect of a given constraint on the ecosystem flow of matter and energy performed by a given item of biodiversity, within a closure of constraints. We elaborate on this definition by developing a case study of a bromeliad ecosystem. (shrink)

In the increasing body of metatheoretical literature on "causal mechanisms," definitions of "mechanism" proliferate, and these increasingly divergent definitions reproduce older theoretical and methodological oppositions. The reason for this proliferation is the incompatibility of the various metatheoretical expectations directed to them: (1) to serve as an alternative to the scientific theory of individual behavior (for some social theorists, most notably Jon Elster); (2) to provide solutions for causal inference problems in the quantitative social sciences, in social history, and in the (...) (3) qualitative research context; and (4) to serve as an alternative for narratives (Charles Tilly). Mechanisms can do (1) only as under-specified law-like regularities, deliver (2) as robust generative processes represented by models, and accomplish (3) as fragile generative processes (stories), but these are not all compatible. (edited). (shrink)

Mechanisms are a way of explaining how biological phenomena work rather than why single elements of biological systems are there. However, mechanisms are usually described as physiological entities, and little or no attention is paid to malfunction as an independent theoretical concept. On the other hand, malfunction is the main focus of interest of applied sciences such as medicine. In this paper I argue that malfunctions are parts of pathological mechanisms, which should be considered separate theoretical entities, conceptually having a (...) priority over physiological sequences. While pathological mechanisms can be described in terms of a Cummins-like mechanistic explanation, they show some unnoticed peculiarities when compared to physiological ones. Some features of pathological mechanisms are considered, such as outcome variability, ambivalence and dependence on a range. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

This paper argues that a minimal notion of function and a notion of normal-proper function are used in explaining how bodies and brains operate. Neither is Cummins’ notion, as originally defined, and yet his is often taken to be the clearly relevant notion for such an explanatory context. This paper also explains how adverting to normal-proper functions, even if these are selected functions, can play a significant scientific role in the operational explanations of complex systems that physiologists and neurophysiologists provide, (...) despite a lack of relevant causal efficacy on the part of such functions. (shrink)

In this paper, I examine metaphysical aspects in the neuroeconomics debate. I propose that part of the debate can be better understood by supposing two metaphysical stances, mechanistic and functional. I characterize the two stances, and discuss their relations. I consider two models of framing, in order to illustrate how the features of mechanistic and functional stances figure in the practice of the sciences of individual decision making.

In this paper, we develop an organizational account that defines biological functions as causal relations subject to closure in living systems, interpreted as the most typical example of organizationally closed and differentiated self-maintaining systems. We argue that this account adequately grounds the teleological and normative dimensions of functions in the current organization of a system, insofar as it provides an explanation for the existence of the function bearer and, at the same time, identifies in a non-arbitrary way the norms that (...) functions are supposed to obey. Accordingly, we suggest that the organizational account combines the etiological and dispositional perspectives in an integrated theoretical framework. IntroductionDispositional ApproachesEtiological TheoriesBiological Self-maintenance Closure, teleology, and normativityOrganizational differentiationFunctions C1: Contributing to the maintenance of the organization C2: Producing the functional trait Implications and Objections Functional versus useful Dysfunctions, side effects, and accidental contributionsProper functions and selected effectsReproductionRelation with other ‘unitarian’ approachesConclusions. (shrink)

Although the analogy between macroscopic machines and biological molecular devices plays an important role in the conceptual framework of both neo-mechanistic accounts and nanotechnology, it has recently been claimed that certain complex molecular devices cannot be considered machines since they are subject to physicochemical forces that are different from those of macroscopic machines. However, the structural and physicochemical conditions that allow both macroscopic machines and microscopic devices to work and perform new functions, through a combination of elemental functional parts, have (...) not yet been examined. In order to fill this void, this paper has a threefold aim: first, to clarify the structural and organisational conditions of macroscopic machines and microscopic devices; second, to determine whether the machine-like analogy fits nanoscale devices; and third, to assess whether the machine-like analogy is appropriate for describing the behaviour of some biological macromolecules. Finally, the paper gives an account of ‘machine’ which, while acknowledging the physicochemical and organisational differences between man-made machines and biological microscopic devices, nevertheless identifies a common conceptual core that allows us to consider the latter ‘machines’. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

Multifunctionality poses significant challenges for human brain mapping. Cathy Price and Karl Friston argue that brain regions perform many functions in one sense and a single function in another. Thus, neuroscientists must revise their “cognitive ontologies” to obtain systematic mappings. Colin Klein draws a different lesson from these findings: neuroscientists should abandon systematic mappings for context-sensitive ones. I claim that neither account succeeds as a general treatment of multifunctionality. I argue that brain areas, like genes or organs, are multifunctional in (...) different ways. I call this the “functional heterogeneity hypothesis.” I contend that different multifunctional parts require different mapping strategies. (shrink)

Functional localization is a central aim of cognitive neuroscience. But the nature and extent of functional localization in the human brain have been subjects of fierce theoretical debate since the 19th Century. In this essay, I first examine how concepts of functional localization have changed over time. I then analyze contemporary challenges to functional localization drawing from research on neural reuse, neural degeneracy, and the context-dependence of neural functions. I explore the consequences of these challenges for topics in philosophy of (...) science and philosophy of mind including localizationist versus anti-localizationist approaches to cognitive neuroscience, multiple realizability, reverse inference in functional neuroimaging, and the modularity of mind. (shrink)

mechanism" is frequently encountered in the social science literature, but there is considerable confusion about the exact meaning of the term. The article begins by addressing the main conceptual issues. Use of this term is the hallmark of an approach that is critical of the explanatory deficits of correlational analysis and of the covering-law model, advocating instead the causal reconstruction of the processes that account for given macro-phenomena. The term "social mechanisms" should be used to refer to recurrent processes generating (...) a specific kind of outcome. Explanation of social macro-phenomena by mechanisms typically involves causal regression to lower-level elements, as stipulated by methodological individualism. While there exist a good many mechanism models to explain emergent effects of collective behavior, we lack a similarly systematic treatment of generative mechanisms in which institutions and specific kinds of structural configurations play the decisive role. Key Words: causal regression • correlational analysis • emergent effects • micro-macro processes • social mechanisms • structural determinants. (shrink)

The aim of this thesis is to argue in favour of the embodied music cognition paradigm, as opposed to traditional theories of musical mind. The thesis consists of three chapters. The goal of the first chapter is to examine computational music cognition, focusing on the main problem of this approach. In the second chapter, I will present and discuss Marc Leman’s EMC, that may serve as a response to the problems of the computational view of the musical mind. Although this (...) framework is interesting, it is unclear in several places. For that reason, I intend to enrich it with the references to the recent works on human mirror neuron system and enactivist views on music cognition. Given that, in the last chapter, I will answer the question, whether mental representations are necessary in music cognition. (shrink)

Species are considered the basic unit of biological classification and evolution. Hence, they are used as a benchmark in several fields, although the ontological status of such a category has always been a matter of debate. This paper aims to discuss the problem of the definition of species within the new mechanistic approach. Nevertheless, the boundary between entities, activities, and mechanisms remains difficult to establish and always requires an analysis of what is meant by explanation. As a case study, the (...) paper describes the debate concerning the species category by considering different kingdoms: Animals, Bacteria, and Fungi. The inherently biological differences between those groups prevent the use of a single, universally applicable concept of species that could fit the mechanisms responsible for the variability present in these kingdoms. The same issue is encountered within each group, as highlighted through a focus on mammals and microbes. This controversy has given rise to opposite approaches, namely: monism, which looks for a single definition that might account for all species, and pluralism, which admits that different groups of organisms require somewhat different definitions. In order to develop an adequate definition of species, we propose to apply a new mechanistic framework, which considers the ontic-epistemic dimensions of scientific explanation in close parallel. The apt correlation between epistemic and the ontic aspects highlights the way in which the concept of species and the reference to data are strictly co-determined. This suggests that the concept of species is better understandable within a dual ontic-epistemic approach. (shrink)

In this paper, we address the question of what current computers are from the point of view of human-computer interaction. In the early days of computing, the Turing machine (TM) has been the cornerstone of the understanding of computers. The TM defines what can be computed and how computation can be carried out. However, in the last decades, computers have evolved and increasingly become interactive systems, reacting in real-time to external events in an ongoing loop. We argue that the TM (...) does not provide a mechanistic explanation for interactive computing. The reason is that the fundamental phenomena relevant to interactive computing are out of the scope of classical computability theory. Part of the explanatory power of the TM relies on what we propose to call an execution model. An execution model belongs to a level of abstraction where it is possible to describe both the functional architecture and the execution in mechanistic terms. An updated execution model is warranted to provide the minimal mechanistic description for interactive computation as a counterpart of what the TM could explain regarding Church-Turing computation. It would support an explanation of the ubiquitous computing devices we know - those interacting with humans, e.g., through digital interfaces. We show that such a model is not available within interactive models of computation and that relevant abstractions and concerns are available in computer engineering but need to be identified and gathered. To fill this void, we propose to reflect on the level of abstraction required to support the mechanistic description of an interactive execution and propose some preliminary requirements. (shrink)

In 1958, Francis Crick distinguished the flow of information from the flow of matter and the flow of energy in the mechanism of protein synthesis. Crick’s claims about information flow and coding in molecular biology are viewed from the perspective of a new characterization of mechanisms and from the perspective of information as holding a key to distinguishing work in molecular biology from that of biochemistry in the 1950s–1970s . Flow of matter from beginning to end does not occur in (...) the protein synthesis mechanism; flow of information does. The flow of information and coding in molecular biological mechanisms are distinguished, on the one hand, from formal information theory, and, on the other, from information as used in cognitive neuroscience, where information and representation are often coupled. (shrink)

The distinction between causal role and selected effect functions is typically framed in terms of their respective explanatory roles. However, much of the controversy over functions in genomics takes place in an investigative, not an explanatory context. Specifically, the process of component-driven functional investigation begins with the designation of some genetic or epigenetic element as functional —i.e. not junk— because it possesses properties that, arguably, suggest some biologically interesting organismal effect. The investigative process then proceeds, in a bottom-up fashion, to (...) search for those effects. I argue that this process encounters a problem reminiscent of one that Gould and Lewontin associated with the adaptationist program. Just as their stereotypical adaptationst became trapped in the myopic pursuit of one selectionist hypothesis after another, so can the investigation of CR functions in genomics lead to an unending series putative organism-level CR functions for junk DNA. This is an acute problem for genomics, because eukaryotic genomes are littered with transposable elements and their deactivated descendants which often masquerade as interesting CR-functional components and it is experimentally onerous to determine whether they lack such a function. I further argue that selectionist reasoning about TE-host coevolutionary dynamics can greatly streamline the investigative process. Importantly, selectionist hypotheses need not be well confirmed to be illuminating in this context. Informed selectionist reasoning about the strategic roles of TEs in the genome offers a corrective to the idea that most of our DNA is somehow CR functional for the organism. (shrink)

Carl Craver’s recent book offers an account of the explanatory and theoretical structure of neuroscience. It depicts it as centered around the idea of achieving mechanistic understanding, i.e., obtaining knowledge of how a set of underlying components interacts to produce a given function of the brain. Its core account of mechanistic explanation and relevance is causal-manipulationist in spirit, and offers substantial insight into casual explanation in brain science and the associated notion of levels of explanation. However, the focus on mechanistic (...) explanation leaves some open questions regarding the role of computation and cognition. (shrink)

It is generally acknowledged by proponents of ‘new mechanism’ that mechanistic explanation involves adopting a perspective, but there is less agreement on how we should understand this perspective-taking or what its implications are for practising science. This paper examines the perspectival nature of mechanistic explanation through the lens of the ‘mechanistic stance’, which falls somewhere between Dennett’s more familiar physical and design stance. We argue this approach implies three distinct and significant ways in which mechanistic explanation can be interpreted as (...) perspectival: ‘phenomenon perspectivism’, ‘pattern perspectivism’ and ‘hierarchy perspectivism’. We evaluate the strength of the perspective-dependency implied by each of these, and along the way, discuss their significance for wider debates within the new mechanism literature, such as the nature of function attribution and an ontic vs epistemic understanding of explanation. (shrink)

A promising strategy for defending the role that representation plays in explanations of cognition frames the concept in terms of internal models or map‐like mechanisms. “Structural representation” offers an account of representation that is grounded in well‐specified, empirical criteria. However, anti‐representationalists continue to press the issue of how to account for the paradigmatic semantic properties of representation at the subpersonal level. In this paper, I offer an account of how the proponent of structural representation should think about content. There are (...) really two problems of content any account of representation must overcome: the “hard problem of content” and the “content determination problem.” I argue that the structural representation account has the resources to provide a naturalistically respectable notion of content that overcomes both problems. (shrink)

Jacques Monod (1971) argued that certain molecular processes rely critically on the property of chemical arbitrariness, which he claimed allows those processes to “transcend the laws of chemistry”. It seems natural, as some philosophers have done, to interpret this in modal terms: a biological relationship is chemically arbitrary if it is possible, within the constraints of chemical “law”, for that relationship to have been otherwise than it is. But while modality is certainly important for understanding chemical arbitrariness, understanding its biological (...) role also requires an account of the concrete causal-functional features that distinguish arbitrary from non-arbitrary phenomena. In this paper I elaborate on this under-emphasised aspect by offering a general account of these features: arbitrary relations are instantiated by mechanisms that involve molecular adapters, which causally couple two properties or processes which would otherwise be uncorrelated. Additionally, adapters work by acting as intermediate rather than cooperating causes. (shrink)

Scientists of many disciplines use theoretical models to explain and predict the dynamics of the world. They often have to rely on digital computer simulations to draw predictions fromthe model. But to deliver phenomenologically adequate results, simulations deviate from the assumptions of the theoretical model. Therefore the role of simulations in scientific explanation demands itself an explanation. This paper analyzes the relation between real-world system, theoretical model, and simulation. It is argued that simulations do not explain processes in the real (...) world directly. The way in which simulations help explaining real-world processes is conceived as indirect, mediated by the theoretical model. Simulacra are characterized further, and turn out to be a priori measurable. This gives a clue to a better understanding of the epistemic role of computer simulations in scientific research. (shrink)

We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...) We conclude from this that topological explanations are autonomous from their mechanistic counterparts. (shrink)

This paper examines the application of the mutual manipulability criterion as a way to demarcate constituents of cognitive systems from resources having a mere causal influence on cognitive systems. In particular, it is argued that on at least one interpretation of the mutual manipulability criterion, the criterion is inadequate because the criterion is conceptualized as identifying synchronic dependence between higher and lower ‘levels’ in mechanisms. It is argued that there is a second articulation of the mutual manipulability criterion available, and (...) that it should be preferred for at least two reasons. The first is that the criterion of mutual manipulability is an instance of continuous reciprocal causation. The second is that it has implications for how to understand this distinction between causation and constitution. It is shown that when considering dynamic systems, continuous reciprocal causation - ubiquitous in dynamical systems - is a form of constitutive causality, which entails that causal factors may, in the right circumstances, by genuine constitutive factors of cognition. This notion of constitutive causality lends support to conceiving of the mutual manipulability criterion as a genuine demarcation principle in the debate over the boundaries of mind. (shrink)