The new mechanists and the autonomy approach both aim to account for how biological phenomena are explained. One identifies appeals to how components of a mechanism are organized so that their activities produce a phenomenon. The other directs attention towards the whole organism and focuses on how it achieves self-maintenance. This paper discusses challenges each confronts and how each could benefit from collaboration with the other: the new mechanistic framework can gain by taking into account what happens outside (...) individual mechanisms, while the autonomy approach can ground itself in biological research into how the actual components constituting an autonomous system interact and contribute in different ways to realize and maintain the system. To press the case that these two traditions should be constructively integrated we describe how three recent developments in the autonomy tradition together provide a bridge between the two traditions: (1) a framework of work and constraints, (2) a conception of function grounded in the organization of an autonomous system, and (3) a focus on control. (shrink)

This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism (...) for countering heat shock—the heat shock response system—in Escherichia coli bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation. (shrink)

The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in (...) the philosophy of biology, situating the new ‘mechanismic program’ in this context. I argue that the leading advocates of the mechanismic program (i.e., Craver, Darden, Bechtel, etc.) inadvertently conflate the different senses of ‘mechanism’. Specifically, they all inappropriately endow causal mechanisms with the ontic status of machine mechanisms, and this invariably results in problematic accounts of the role played by mechanism-talk in scientific practice. I suggest that for effective analyses of the concept of mechanism, causal mechanisms need to be distinguished from machine mechanisms, and the new mechanismic program in the philosophy of biology needs to be demarcated from the traditional concerns of mechanistic biology. (shrink)

Following an analysis of the state of investigations and clinical outcomes in the Alzheimer's research field, I argue that the widely-accepted 'amyloid cascade' mechanistic explanation of Alzheimer's disease appears to be fundamentally incomplete. In this context, I propose that a framework termed 'principled mechanism' (PM) can help with remedying this problem. First, using a series of five 'tests', PM systematically compares different components of a given mechanistic explanation against a paradigmatic set of criteria, and hints at various ways of (...) making the mechanistic explanation more 'complete'. These steps will be demonstrated using the amyloid explanation, and its missing or problematic mechanistic elements will be highlighted. Second, PM makes an appeal for the discovery and application of 'biological principles' (BPs), which approximate ceteris paribus laws and are operative at the level of a biological cell. As such, although thermodynamic, evolutionary, ecological and other laws or principles from chemistry and the broader life sciences could inform them, BPs should be considered ontologically unique. BPs could augment different facets of the mechanistic explanation but also allow further independent nomological explanation of the phenomenon. Whilst this overall strategy can be complementary to certain 'New Mechanist' approaches, an important distinction of the PM framework is its equal attention to the explanatory utility of biological principles. Lastly, I detail two hypothetical BPs, and show how they could each inform and improve the potentially incomplete mechanistic aspects of the amyloid explanation and also how they could provide independent explanations of the cellular features associated with Alzheimer's disease. (shrink)

Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models such (...) as hierarchy and correlation are combined with nomological principles such as general operative rules and generative principles. Depending on the question at hand and the nature of the inquiry, X could range from proven physical laws to speculative biological generalizations, such as the notional principle of cellular synchrony. I argue that the "mechanism-plus-X" approach should ultimately aim to move biological inquiries out of the deadlock of oft-encountered mechanistic pitfalls and reposition biology to its former capacity of illuminating fundamental truths about the world. (shrink)

This paper advances the thesis of methodological mechanism, the claim that to be committed to mechanism is to adopt a certain methodological postulate, i.e. to look for causal pathways for the phenomena of interest. We argue that methodological mechanism incorporates a minimal account of understanding mechanisms, according to which a mechanism just is a causal pathway described in the language of theory. In order to argue for this position we discuss a central example of a (...) class='Hi'>biological mechanism, the mechanism of cell death, known as apoptosis. We argue that this example shows that our philosophically deflationary account is sufficient in order to have an illuminating account of mechanisms as the concept is used in biology. (shrink)

Biological atomism postulates that all life is composed of elementary and indivisible vital units. The activity of a living organism is thus conceived as the result of the activities and interactions of its elementary constituents, each of which individually already exhibits all the attributes proper to life. This paper surveys some of the key episodes in the history of biological atomism, and situates cell theory within this tradition. The atomistic foundations of cell theory are subsequently dissected and discussed, (...) together with the theory’s conceptual development and eventual consolidation. This paper then examines the major criticisms that have been waged against cell theory, and argues that these too can be interpreted through the prism of biological atomism as attempts to relocate the true biological atom away from the cell to a level of organization above or below it. Overall, biological atomism provides a useful perspective through which to examine the history and philosophy of cell theory, and it also opens up a new way of thinking about the epistemic decomposition of living organisms that significantly departs from the physicochemical reductionism of mechanistic biology. (shrink)

Unless one embraces activities as foundational, understanding activities in mechanisms requires an account of the means by which entities in biological mechanisms engage in their activities—an account that does not merely explain activities in terms of more basic entities and activities. Recent biological research on molecular motors exemplifies such an account, one that explains activities in terms of free energy and constraints. After describing the characteristic “stepping” activities of these molecules and mapping the stages of those steps onto (...) the stages of the motors’ hydrolytic cycles, researchers pieced together from images of the molecules in different hydrolyzation states accounts of how the chemical energy in ATP is transformed in the constrained environments of the motors into the characteristic activities of the motors. We argue that New Mechanism’s standard set of analytic categories—entities, activities, and organization—should be expanded to include constraints and energetics. Not only is such an expansion required descriptively to capture research on molecular motors but, more importantly from a philosophical point of view, it enables a non-regressive account of activities in mechanisms. In other words, this expansion enables a philosophical account of mechanistic explanation that avoids a regress of entities and activities “all the way down.” Rather, mechanistic explanation bottoms out in constraints and energetics. (shrink)

According to mainstream philosophical views causal explanation in biology and neuroscience is mechanistic. As the term ‘mechanism’ gets regular use in these fields it is unsurprising that philosophers consider it important to scientific explanation. What is surprising is that they consider it the only causal term of importance. This paper provides an analysis of a new causal concept—it examines the cascade concept in science and the causal structure it refers to. I argue that this concept is importantly different from (...) the notion of mechanism and that this difference matters for our understanding of causation and explanation in science. (shrink)

During the twentieth century, the mechanistic worldview came under attack mainly because of the rise of quantum mechanics but some of its basic characteristics survived and are still evident within current science in some form or other. Many scholars have produced interesting studies of such significant mechanistic trends within current physics and biology but very few have bothered to explore the effects of this worldview on current chemistry. This paper makes a contribution to fill this gap. It presents first a (...) brief historical overview of the mechanistic worldview and then examines the present situation within chemistry by referring to current studies in the philosophy of chemistry and determining which trends are still mechanistic in spirit and which are not. (shrink)

This article presents a distinct sense of ‘mechanism’, which I call the functional sense of mechanism. According to this sense, mechanisms serve functions, and this fact places substantive restrictions on the kinds of system activities ‘for which’ there can be a mechanism. On this view, there are no mechanisms for pathology; pathologies result from disrupting mechanisms for functions. Second, on this sense, natural selection is probably not a mechanism for evolution because it does not serve a (...) function. After distinguishing this sense fromsimilar explications of ‘mechanism’, I argue that it is ubiquitous in biology and has valuable epistemic benefits. (shrink)

The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...) representations in the epistemic practices of mechanism discovery and mechanism description. These examples also indicate that the scope of mechanistic explanation must be re-examined: With new and increasingly powerful methods of discovery and description comes the possibility of describing mechanisms far more complex than traditionally assumed. (shrink)

One of the central aims of science is explanation: scientists seek to uncover why things happen the way they do. This chapter addresses what kinds of explanations are formulated in biology, how explanatory aims influence other features of the field of biology, and the implications of all of this for biology education. Philosophical treatments of scientific explanation have been both complicated and enriched by attention to explanatory strategies in biology. Most basically, whereas traditional philosophy of science based explanation on derivation (...) from scientific laws, there are many biological explanations in which laws play little or no role. Instead, the field of biology is a natural place to turn for support for the idea that causal information is explanatory. Biology has also been used to motivate mechanistic accounts of explanation, as well as criticisms of that approach. Ultimately, the most pressing issue about explanation in biology may be how to account for the wide range of explanatory styles encountered in the field. This issue is crucial, for the aims of biological explanation influence a variety of other features of the field of biology. Explanatory aims account for the continued neglect of some central causal factors, a neglect that would otherwise be mysterious. This is linked to the persistent use of models like evolutionary game theory and population genetic models, models that are simplified to the point of unreality. These explanatory aims also offer a way to interpret many biologists’ total commitment to one or another methodological approach, and the intense disagreements that result. In my view, such debates are better understood as arising not from different theoretical commitments, but commitments to different explanatory projects. Biology education would thus be enriched by attending to approaches to biological explanation, as well as the unexpected ways that these explanatory aims influence other features of biology. I suggest five lessons for teaching about explanation in biology that follow from the considerations of this chapter. (shrink)

Though the realm of biology has long been under the philosophical rule of the mechanistic magisterium, recent years have seen a surprisingly steady rise in the usurping prowess of process ontology. According to its proponents, theoretical advances in the contemporary science of evo-devo have afforded that ontology a particularly powerful claim to the throne: in that increasingly empirically confirmed discipline, emergently autonomous, higher-order entities are the reigning explanantia. If we are to accept the election of evo-devo as our best conceptualisation (...) of the biological realm with metaphysical rigour, must we depose our mechanistic ontology for failing to properly “carve at the joints” of organisms? In this paper, I challenge the legitimacy of that claim: not only can the theoretical benefits offered by a process ontology be had without it, they cannot be sufficiently grounded without the metaphysical underpinning of the very mechanisms which processes purport to replace. The biological realm, I argue, remains one best understood as under the governance of mechanistic principles. (shrink)

Problem Statement. The process of global evolution has entered the Anthropocene. This fact has almost simultaneously generated two cardinal, inseparable imperatives in the rapidly changing ideological and outlook basis of modern civilization. Firstly, the feeling that the new geological epoch also requires fundamentally new algorithms guiding practical activity and its theoretical comprehension, justification in all spheres of political reality, with inevitable exit to the level of international relations and geopolitics. Secondly, the content of the categories of ANTHROPOCEN and (GLOBAL) CRISIS (...) overlap so diversely and widely that they form an almost inseparable logically and mentally amalgam. The purpose of this publication is to reveal the political aspects of the integration of new biopolitical issues into the life of modern society. The content of the term biopolitics is currently not formalized in a definitive form. In our concept, biopolitics is defined as the processes of implementing biopower, that is, the ability (direct or indirect) of the power structures of society to control and manipulate the performance of the biological functions of certain individuals. Based on a combination of methods of conceptual, discursive and evolutionary-anthropological analysis (the concepts of evolutionary strategy and cultural-ecological niche), possible scenarios for the future development of the political process at the domestic and international levels are identified. The mechanism of transbipolitical transition – the inclusion of civilizational and biological evolution in the political process – is investigated. The conclusion formulates the content of the category “transbiolitics” as the main element of rationalization of the global-evolutionary process in the globalizing world. Transbiolitics in our understanding is an international political problematic related to the rationalization of the global evolutionary process. Technologization of the global evolutionary process, the choice of implemented technological projects and forms of their institutional support is determined primarily by geo- and biopolitical motivation of local elites and humanitarian and other convergent technologies available to them. (shrink)

Philosophers of science have examined The Theory of Island Biogeography by Robert MacArthur and E. O. Wilson (1967) mainly due to its important contribution to modeling in ecology, but they have not examined it as a representative case of ecological explanation. In this paper, I scrutinize the type of explanation used in this paradigmatic work of ecology. I describe the philosophy of science of MacArthur and Wilson and show that it is mechanistic. Based on this account and in light of (...) contributions to the mechanistic conception of explanation due to Craver (2007), and Bechtel and Richardson (1993), I argue that MacArthur and Wilson use a mechanistic approach to explain the species-area relationship. In light of this examination, I formulate a normative account of mechanistic explanation in ecology. Furthermore, I argue that it offers a basis for methodological unification of ecology and solves a dispute on the nature of ecology. Lastly, I show that proposals for a new paradigm of biogeography appear to maintain the norms of mechanistic explanation implicit in The Theory of Island Biogeography. (shrink)

In this essay I propose that what design principles in systems biology and systems neuroscience do is to present abstract characterizations of mechanisms, and thereby facilitate mechanistic explanation. To show this, one design principle in systems neuroscience, i.e., the multilayer perceptron, is examined. However, Braillard (2010) contends that design principles provide a sort of non-mechanistic explanation due to two related reasons: they are very general and describe non-causal dependence relationships. In response to this, I argue that, on the one hand, (...) all mechanisms are more or less general (or abstract), and on the other, many (if not all) design principles are causal systems. (shrink)

The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...) argue that large-scale simulations require that the explanandum phenomenon is identified; otherwise, the explanatory value of such explanations is difficult to establish, and testing the model empirically by comparing its behavior with the explanandum remains practically impossible. The completeness of the explanation, and hence of the explanatory value of the explanatory model, is to be assessed vis-à-vis the explanandum phenomenon, which is not to be conflated with raw observational data and may be idealized. I argue that idealizations, which include building models of a single phenomenon displayed by multi-functional mechanisms, lumping together multiple factors in a single causal variable, simplifying the causal structure of the mechanisms, and multi-model integration, are indispensable for complex systems such as brains; otherwise, the model may be as complex as the explanandum phenomenon, which would make it prone to so-called Bonini paradox. I conclude by enumerating dimensions of empirical validation of explanatory models according to new mechanism, which are given in a form of a “checklist” for a modeler. (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.

John Searle has argued that functions owe their existence to the value that we put into life and survival. In this paper, I will provide a critique of Searle’s argument concerning the ontology of functions. I rely on a standard analysis of functional predicates as relating not only a biological entity, an activity that constitutes the function of this entity and a type of system but also a goal state. A functional attribution without specification of such a goal state (...) has no truth-value. But if completed with a goal state, functional attributions understood as four-place relations attain a truth-value. The truth conditions of all attributions of function involve a dependence claim of the goal state on the function bearer’s activity. The nature of this dependence may differ; I consider five different possibilities: causality, mechanistic constitution, mereology, supervenience and metaphysical grounding. If these dependency relations are objective, Searle’s central ontological thesis fails. What he ought to have said is that our valuing survival or other goal states may be the reason why biology seeks functional knowledge, but this has nothing to do with ontology. I will show further that Searle also raised an interesting challenge concerning the relationship of functional and causal truths, but it does not threaten the objectivity of functions either. At best, it could show that functional vocabulary is eliminable. However, I will show that functional vocabulary is not so eliminable. (shrink)

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...) external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized. (shrink)

Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary (...) class='Hi'>biological research practice shows the need for quantitative, probabilistic models of mechanisms, too. In this paper we argue that the formal framework of causal graph theory is well-suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the ba-sis of an example from contemporary biological practice, namely feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multi-level character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes, while being insufficient for others. (shrink)

The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also (...) unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. (shrink)

In this dissertation I achieve the following: (1) I present motivating criteria for a general comprehensive theory of scientific explanation. I review historical approaches to modeling explanation in light of these criteria. (2) I present New Mechanist Explanation ("NME") as the leading candidate for a contemporary, complete theory of scientific explanation. (3) I present constraints on the applicability of New Mechanism in modeling biology, chemistry, and physics. I argue for the unsuitability of NME as a candidate for a general (...) theory of explanation due to its significant omissions of explanatory content and subsequent incompleteness. (4) I present arguments for the indispensable explanatory power of mathematics in science, noting that much of NME's failures are owed to its poor integration of mathematical explanation as applied to science. (5) I propose a Rational-Relational theory of explanation(“RRE”). I present RRE in detail and demonstrate it as a true working general theory of explanation which best meets the motivating criteria presented in (1). I disambiguate RRE from structural explanation ("SE"). I show that historical models of explanation, including the deductive nomological (DNE) model, statistical relevance ("SRE") model, structural model (SE) and unification model ("UE") may be successfully treated as sub-classes of explanation within the scope of RRE. I provide a rubric for selecting amongst sub-theories of explanation under RRE in the purpose of highlighting particular features of relational explanations. (6) In conclusion, I argue that philosophers of science should move forward using RRE as a general model of scientific explanation as a working alternative to the incomplete model of NME. (shrink)

Evidence-Based Medicine has little consideration for mechanisms and philosophers of science and medicine have recently made pleas to increase the place of mechanisms in the medical evidence hierarchy. However, in this debate the notions of mechanisms seem to be limited to 'mechanistic processes' and 'complex-systems mechanisms,' understood as 'componential causal systems'. I believe that this will not do full justice to how mechanisms are used in biological, psychological and social sciences and, consequently, in a more biopsychosocial approach to medicine. (...) Here, I propose, following (Kuorikoski, 2009), to pay more attention to 'abstract forms of interaction' mechanisms. The present work scrutinized review articles on depression and medically unexplained pain, which are considered to be of multifactorial pathogenesis, for their use of mechanisms. In review articles on these disorders there seemed to be a range of uses between more 'abstract forms of interaction' and 'componential causal system' mechanisms. I therefore propose to expand the notions of mechanisms considered in medicine to include that of more 'abstract forms of interaction' to better explain and manage biopsychosocial disorders. (shrink)

Although biological autonomy is widely discussed, its description in scientific terms remains elusive. I present here a series of recent evidences on the existence of genuine biological autonomy. Nevertheless, nowadays it seems that the only acceptable ground to account for any natural phenomena, including biological autonomy, is physics. But if this were the case, then arguably there would be no way to account for genuine biological autonomy. The way out of such a situation is to build (...) up an exact theoretical biology, and one of the first steps is to clarify the basic concepts of biology, among them biological aim, function and autonomy. We found a physical mechanism to realize biological autonomy, namely, biologically initiated vacuum processes. In the newly emerging picture, biological autonomy shows up as a new, fundamental and inevitable element in our scientific world picture. It offers new perspectives for solving problems regarding the origin and nature of life, connecting ancient Greek philosophy with modern science. Namely, our proposal sheds light in what sense can the God as conceived by Xenophanes can move the material objects of the Universe by its thoughts without toil. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

In the first part of this article we survey general similarities and differences between biological and social macroevolution. In the second (and main) part, we consider a concrete mathematical model capable of describing important features of both biological and social macroevolution. In mathematical models of historical macrodynamics, a hyperbolic pattern of world population growth arises from non-linear, second-order positive feedback between demographic growth and technological development. This is more or less identical with the working of the collective learning (...) mechanism. Based on diverse paleontological data and an analogy with macrosociological models, we suggest that the hyperbolic character of biodiversity growth can be similarly accounted for by non-linear, second-order positive feedback between diversity growth and the complexity of community structure, suggesting the presence within the biosphere of a certain analogue of the collective learning mechanism. We discuss how such positive feedback mechanisms can be modelled mathematically. (shrink)

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two (...) groups of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

Are living organisms--as Descartes argued--just machines? Or is the nature of life such that it can never be fully explained by mechanistic models? In this thought-provoking and controversial book, eminent geophysicist Walter M. Elsasser argues that the behavior of living organisms cannot be reduced to physico-chemical causality. Suggesting that molecular biology today is at the same point as Newtonian physics on the eve of the quantum revolution, Elsasser lays the foundation for a theoretical biology that points the way toward a (...) natural philosophy of organic life. Explicitly repudiating "vitalism" (the notion that the laws of nature need to be modified when applied to living organisms), Elsasser argues instead that the structural complexity of even a single living cell is "transcomputational"--that is, beyond the power of any imaginable system to compute. Beginning from this insight, Elsasser leads the reader through a step-by-step process that ultimately arrives at the conclusion that living and non-living matter are separated by "a no-man's land of irrationality." Trained in Germany as a physicist, Elsasser first pondered the implications of quantum mechanics for biology as early as 1951. The more closely he studied the inherent complexity of life, the more skeptical he became of the reductionist view of organisms as tiny machines. "An organism," he concluded, "is a source of causal chains which cannot be traced beyond a terminal point because they are lost in the unfathomable complexity of the organism." Like the physicist who works within the bounds of an unfathomable universe, Elsasser argues, the biologist must seek answers within a system that is no less unfathomable. (shrink)

Racial disparities in health outcomes have recently become a flashpoint in the debate about the value of race as a biological concept. What role, if any, race has in the etiology of disease is a philosophically and scientifically contested topic. In this article, I expand on the insights of the new mechanistic philosophy of science to defend a mechanism discovery approach to investigating epidemiological racial disparities. The mechanism discovery approach has explanatory virtues lacking in the populational approach (...) typically employed in the study of race and biomedicine. The explanatory constraints that form an integral part of the new mechanistic approach enable mechanism discovery to avoid the epistemic and normative shortcomings of the populational approach. The methodology of mechanism discovery can fruitfully be extended to the treatment and reversal of epidemiological racial disparities. (shrink)

Philippe Huneman has recently questioned the widespread application of mechanistic models of scientific explanation based on the existence of structural explanations, i.e. explanations that account for the phenomenon to be explained in virtue of the mathematical properties of the system where the phenomenon obtains, rather than in terms of the mechanisms that causally produce the phenomenon. Structural explanations are very diverse, including cases like explanations in terms of bowtie structures, in terms of the topological properties of the system, or in (...) terms of equilibrium. The role of mathematics in bowtie structured systems and in topologically constrained systems has recently been examined in different papers. However, the specific role that mathematical properties play in equilibrium explanations requires further examination, as different authors defend different interpretations, some of them closer to the new-mechanistic approach than to the structural model advocated by Huneman. In this paper, we cover this gap by investigating the explanatory role that mathematics play in Blaser and Kirschner’s nested equilibrium model of the stability of persistent long-term human-microbe associations. We argue that their model is explanatory because: i) it provides a mathematical structure in the form of a set of differential equations that together satisfy an ESS; ii) that the nested nature of the ESSs makes the explanation of host-microbe persistent associations robust to any perturbation; iii) that this is so because the properties of the ESS directly mirror the properties of the biological system in a non-causal way. The combination of these three theses make equilibrium explanations look more similar to structural explanations than to causal-mechanistic explanation. (shrink)

All the central assumptions of the Modern Synthesis (Neo-Darwinism) have been disproven. [1, 2] An article with the title, "Rocking the foundations of molecular genetics,” appearing in the prestigious Proceedings of the National Academy of Sciences at the end of 2012 [3] would have not been possible a decade ago. Groundbreaking experimental evidence of epigenetic maternal inheritance over several generations was published in the same journal, throwing the whole foundation of 21st century molecular genetics into question. Neo-Darwinism attributed genetic change (...) to random events, in which physiology was assumed to play little role. "The germ line was thought to be isolated from any influence by the rest of the organism and its response to the environment. [3] The fundamental concepts that constitute the foundations of contemporary systems biology include holism, emergentism, and robustness, compared to the concepts of reductionism, mechanism, and homeostasis, that form the foundations of molecular biology. [18] Holism is to be contrasted with reductionism which considers a system as merely composed of a sum of parts. Emergentism, the appearance of hierarchical levels of organization, is contrasted with mechanism of independent linear events. Robustness refers to the preservation of the functionality of a system to a certain degree despite external or internal changes, while homeostasis refers to maintaining the stability of the state of a system. The Vedantic view also proposes viewing life from the Organic Whole perspective, in which consciousness forms the supporting basis. The conscious agent is an important part of that view, but the absolute conception of a unifying center is not to be omitted if a proper conception is to be achieved. (shrink)

Autoinhibition is a design principle realized in many molecular mechanisms in biology. After explicating the notion of a design principle and showing that autoinhibition is such a principle, we focus on how researchers discovered instances of autoinhibition, using research establishing the autoinhibition of the molecular motors kinesin and dynein as our case study. Research on kinesin and dynein began in the fashion described in accounts of mechanistic explanation but, once the mechanisms had been discovered, researchers discovered that they exhibited a (...) second phenomenon, autoinhibition. The discovery of autoinhibition not only reverses the pattern in terms of which philosophers have understood mechanism discovery but runs counter to the one phenomenon-one mechanism principle assumed to relate mechanisms and the phenomena they explain. The ubiquity of autoinhibition as a design principle, therefore, necessitates a philosophical understanding of mechanisms that recognizes how they can participate in more than one phenomenon. Since mechanisms with this design are released from autoinhibition only when they are acted on by control mechanisms, we advance a revised account of mechanisms that accommodates attribution of multiple phenomena to the same mechanism and distinguishes them from other processes that control them. (shrink)

Kant’s theory of biology in the Critique of the Power of Judgment may be rejected as obsolete and attacked from two opposite perspectives. In light of recent advances in biology one can claim contra Kant, on the one hand, that biological phenomena, which Kant held could only be explicated with the help of teleological principles, can in fact be explained in an entirely mechanical manner, or on the other, that despite the irreducibility of biology to physico-mechanical explanations, it is (...) nonetheless proper science. I argue in response that Kant’s analysis of organisms is by no means obsolete. It reveals biology’s uniqueness in much the same way as several current theorists do. It brings to the fore the unique purposive characteristics of living phenomena, which are encapsulated in Kant’s concept of “natural end” and which must be explicated in natural terms in order for biology to become a science. I maintain that Kant’s reluctance to consider biology proper science is not a consequence of his critical philosophy but rather of his inability to complete this task. Kant lacked an appropriate theoretical framework, such as provided later by modern biology, which would enable the integration of the unique features of biology in an empirical system. Nevertheless, as I show in this paper, the conceptual problems with which Kant struggled attest more to the relevance and depth of his insights than to the shortcomings of his view. His contribution to the biological thought consists in insisting on an empirical approach to biology and in providing the essential philosophical underpinning of the autonomous status of biology. (shrink)

A formal model of the processes of digestion in a hypothetical cell is developed and discussed as a case study of how the threefold logic of Peircean semiotics works within Rosen’s paradigm of relational ontology. The formal model is used to demonstrate several fundamental differences between a relational description of biological processes and a mechanistic description. The formal model produces a logic of embodied generalization that is mediated and determined by the cell through its interactions with the environment. Specifically, (...) the synchronization of the functions of pattern recognition and semantic attribution results in an open and adaptive learning system that is stabilized by a hermeneutical circle. The relational principles of biosemiotics demonstrated through this case study are applicable to other biological systems, as well as to the relational ontology of systems theory, artificial intelligence systems, and relativistic quantum theory. (shrink)

Should we think of our universe as law-governed and “clockwork”-like or as disorderly and “soup”-like? Alternatively, should we consciously and intentionally synthesize these two extreme pictures? More concretely, how deterministic are the postulated causes and how rigid are the modeled properties of the best statistical methodologies used in the biological and behavioral sciences? The charge of this entry is to explore thinking about causation in the temporal evolution of biological and behavioral systems. Regression analysis and path analysis are (...) simply explicated with reference to a thought experiment of painting three universes (clockwork, soup, and conscious) useful for imagining our actual universe. Attention to historical, structural, and mechanistic explanatory perspectives broadens the palette of methodologies available for analyzing determinism in, and explanation of, biological and behavioral systems. Each justified methodology provides a partial perspective on complex reality. Is a total explanation of any system ever possible, and what would it require? (shrink)

Living organisms act as integrated wholes to maintain themselves. Individual actions can each be explained by characterizing the mechanisms that perform the activity. But these alone do not explain how various activities are coordinated and performed versatilely. We argue that this depends on a specific type of mechanism, a control mechanism. We develop an account of control by examining several extensively studied control mechanisms operative in the bacterium E. coli. On our analysis, what distinguishes a control mechanism (...) from other mechanisms is that it relies on measuring one or more variables, which results in setting constraints in the control mechanism that determine its action on flexible constraints in other mechanisms. In the most basic arrangement, the measurement process directly determines the action of the control mechanism, but in more complex arrangements signals mediate between measurements and effectors. This opens the possibility of multiple responses to the same measurement and responses based on multiple measurements. It also allows crosstalk, resulting in networks of control mechanisms. Such networks integrate the behaviors of the organism but also present a challenge in tailoring responses to particular measurements. We discuss how integrated activity can still result in differential, versatile, responses. (shrink)

Known as the Darwin of the twenty-first century, the German biologist Ernst Walter Mayr (1904-2005) studied a great variety of subjects such as Ornithology, Genetics, Evolution, Classification, History, and Philosophy of Biology. This scientist was a giant of the previous century and an icon of Evolutionary Biology. He became famous for his Biological Species Concept and his conclusion that allopatry is the main cause for the origin of species. He provided a decisive contribution to the New Systematics and was (...) the pioneer of the punctuated equilibrium idea. Mayr was one of the main architects of the evolutionary synthesis as also of the Neo-Darwinian wave. Evaluated together, all of his works reveal several elements of his ambition – to organize a philosophical conception inherent for Biology. An assiduous defender of autonomous Biology, Mayr asserted that four sets of factors in Biology differ from those in the Exact Sciences: (I) refutation of essentialism, mechanism, vitalism, and teleology; (II) some physical principles cannot be applied to Biology; (III) absence of general laws in Biology; and (IV) basic principles of biology and their specific character cannot be applied to the inanimate world. The present study took as an axis a minor or even invisible theme from the Ernst Mayr literature and aims to analyze critically the theoretical and epistemological basis that subsidizes – or not– the affirmation that Biology is an autonomous Science. - O biólogo alemão Ernst Walter Mayr (1904-2005), conhecido como o Darwin do século XXI, trabalhou com uma grande variedade de temas: Ornitologia, Genética, Evolução, Classificação, História e Filosofia da Biologia. Esse cientista foi um dos gigantes do século XX e um ícone para a Biologia Evolutiva. Ficou famoso com o seu Conceito Biológico de Espécie e sua conclusão de que a alopatria era a principal causa da origem das espécies. Forneceu uma contribuição decisiva à Nova Sistemática, foi precursor da ideia de equilíbrio pontuado e um dos principais arquitetos da síntese evolutiva, bem como do movimento Neodarwinista. Quando avaliados em conjunto, seus trabalhos revelam os diversos elementos de sua ambição – organizar um corpo de concepções filosóficas próprias da Biologia. Defensor assíduo de uma Biologia autônoma, Mayr afirmou que há quatro conjuntos de fatores que diferenciam a Biologia do conjunto das Ciências Exatas: (I) refutação do essencialismo, do mecanicismo, do vitalismo e da teleologia; (II) convicção de que certos princípios da Física não podem ser aplicados à Biologia; (III) ausência de leis naturais universais em Biologia; e (IV) percepção do caráter único de certos princípios básicos da Biologia não aplicáveis ao mundo inanimado. O presente artigo tomou por eixo um tema aparentemente menor ou mesmo invisível na obra de Ernst Mayr e pretende realizar uma análise crítica acerca de suas bases teóricas e epistemológicas que subsidiaram – ou não – a afirmação da Biologia como uma Ciência autônoma. (shrink)

I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation of chemotaxis (...) in Escherichia coli—I argue that each strategy invokes a different combination of abstraction types and that each targets its abstractions to different mechanistic details. (shrink)

Polger and Shapiro argue that their official recipe, a criterion for judging when the phenomenon of multiple realization exists, renders MR less widespread than its proponents have assumed. I argue that, although Polger and Shapiro’s criterion is a useful contribution, they arrive at their conclusion too hastily. Contrary to Polger and Shapiro, I claim that the phenomenon of multiple realization in the biological world, judged by their criterion, is not as scarce as they suggest. To show this, an updated (...) official recipe, namely a multiple mechanistic realization thesis, integrating Polger and Shapiro’s criterion with a compositional conception of realization, is developed. Then, three examples of varied kinds are examined, showing that cases of MR are not so hard to find in the biological world. (shrink)

Evolutionary psychologists often try to “bring together” biology and psychology by making predictions about what specific psychological mechanisms exist from theories about what patterns of behaviour would have been adaptive in the EEA for humans. This paper shows that one of the deepest methodological generalities in evolutionary biology—that proximate explanations and ultimate explanations stand in a many-to-many relation—entails that this inferential strategy is unsound. Ultimate explanations almost never entail the truth of any particular proximate hypothesis. But of course it does (...) not follow that there are no other ways of “bringing together” biology and psychology. Accordingly, this paper explores one other strategy for doing just that, the pursuit of a very specific kind of consilience. However, I argue that inferences reflecting the pursuit of this kind of consilience with the best available theories in contemporary evolutionary biology indicate that psychologists should have a preference for explanations of adaptive behavior in humans that refer to learning and other similarly malleable psychological mechanisms—and not modules or instincts or any other kind of relatively innate and relatively non-malleable psychological mechanism. (shrink)

Philosophical biologists have attempted to define the distinction between life and non-life to more adequately define what it is to be human. They are reacting against idealism, but idealism is their point of departure, and they have embraced the reaction by idealists against the mechanistic notion of humans developed by the scientific materialists. Theoretical biologists also have attempted to develop a more adequate conception of life, but their point of departure has been within science itself. In their case, it has (...) involved efforts to overcome the reductionism of scientific materialism to develop a form of science able to identify and explain the distinctive characteristics of living beings. So, while both philosophical biologists and theoretical biologists are struggling to overcome scientific materialism, they are approaching the question: What is Life? from different directions. Focussing on the work of Robert Rosen, I will try to show what revisions in our understanding of science theoretical biologists need to accept in order to do justice to the insights of the philosophical biologists. I will suggest that not only will this involve major revisions in what we understand science to be, but that scientists must accept that science is indissociable from natural philosophy, and that to properly comprehend life mathematics must ultimately be subordinated to stories. (shrink)

It has been claimed that the intentional stance is necessary to individuate behavioral traits. This thesis, while clearly false, points to two interesting sets of problems concerning biological explanations of behavior: The first is a general in the philosophy of science: the theory-ladenness of observation. The second problem concerns the principles of trait individuation, which is a general problem in philosophy of biology. After discussing some alternatives, I show that one way of individuating the behavioral traits of an organism (...) is by a special use of the concept of biological function, as understood in an enriched causal role (not selected effect) sense. On this view, a behavioral trait is essentially a special kind of regularity, namely a regularity that is produced by some regulatory mechanism. Regulatory mechanisms always require goal states, which can only be provided by functional considerations. As an example from actual (as opposed to folk) science, I examine the case of social behavior in nematodes. I show that the attempt to explain this phenomenon actually transformed it. This supports the view that scientific explanation does not explain an explanandum phenomenon that is given prior to the explanation; rather, the explanandum is changed by the explanation. This means that there could be a plurality of stances that have some heuristic value initially, but which will be abandoned in favor of a functional characterization eventually. (shrink)

Seminal work intended to found a new field of integrative Noetic Science is summarized. Until now the philosophy of Biological Mechanism has ruled medicine and psychology. Penrose claims, AA scientific world-view which does not profoundly come to terms with the problem of conscious mind can have no serious pretensions of completeness@. A noetic action principle synonymous with the historic concept of élan vital is introduced as the basis of a Continuous State Conscious Universe (CSCU). The least unit of (...) CSCU superspace defines Awareness as a fundamental physical quantity like charge in electrodynamics. This cosmological context reveals the origin of complexity in self-organized living-systems wherein the physical basis of qualia is formalized. The dynamics of this teleological action principle, mediated by a unitary noetic field pervading all biochemical species, optimizes the state of well-being through homeostasis and provides the fundamental basis for developing a Moral Psychology. (shrink)

Mechanistic explanations are often said to explain because they reveal the causal structure of the world. Conversely, dynamical models supposedly lack explanatory power because they do not describe causal structure. The only way for dynamical models to produce causal explanations is via the 3M criterion: the model must be mapped onto a mechanism. This framing of the situation has become the received view around the viability of dynamical explanation. In this paper, I argue against this position and show that (...) dynamical models can themselves reveal causal structure and consequently produce nonmechanistic, dynamical explanations. Taking the example of cell fates from systems biology, I show how dynamical models, and specifically the attractor landscapes they describe, identify the causes of cell differentiation and explain why cells select particular fates. These dynamical features of the system better fit Woodward’s (2010, 2018) criteria of specificity and proportionality and make them the best candidate causes of cell fates than mechanisms. I also show how these causes are irreducible and inaccessible to mechanistic models, making 3M unworkable and counterproductive in this case. Dynamical models can reveal dynamical causes and thereby provide causal explanations. (shrink)

Mechanisms, in the prominent biological sense of the term, are historical entities. That is, whether or not something is a mechanism for something depends on its history. Put differently, while your spontaneously-generated molecule-for-molecule double has a heart, and its heart pumps blood around its body, its heart does not have a mechanism for pumping, since it does not have the right history. My argument for this claim is that mechanisms have proper functions; proper functions are historical entities; (...) so, mechanisms are historical entities, too. This thesis runs against the mainstream new mechanist way of thinking about mechanisms, where mechanisms are generally thought of in an ahistorical way. After arguing for this thesis, I draw out some consequences for philosophy of science and metaphysics. (shrink)

Biological organisms, languages and selves are normative entities, so must be understood in terms of norms. Mechanistic understanding is based on causal necessity, but normative understanding relies on a grasp of the contingencies of evolution, history and personal experience.