There is an argument that has recently been deployed in favor of thinking that the mind is mostly (or even exclusively) composed of cognitive modules; an argument that draws from some ideas and concepts of evolutionary and of developmental biology. In a nutshell, the argument concludes that a mind that is massively composed of cognitive mechanisms that are cognitively modular (henceforth, c-modular) is more evolvable than a mind that is not c-modular (or that is scarcely c-modular), since a cognitive mechanism (...) that is c-modular is likely to be biologically modular (henceforth, b-modular), and b-modular characters are more evolvable (e.g., Sperber 2002, Carruthers 2005). In evolutionary biology, the evolvability of a character in an organism is understood as the “organism’s capacity to facilitate the generation of non-lethal selectable phenotypic variation from random mutation” with respect to that character. Here I will argue that the notion of cognitive modularity needed to make this argument plausible will have to be understood in terms of the biological notion of variational independence; that is, it will have to be understood in such a way that a cognitive feature is c-modular only if few or no other morphological changes (cognitive and not) are significantly correlated with variations of that feature arising in members of the relevant population. I will also argue that all –except for (possibly) one—of the connotations contained in a cluster of notions of cognitive modularity widely accepted in some of the mainstream currents of thought in classical cognitive science, are simply irrelevant to the argument. In order to argue for this, I will have to examine the question as to whether there are any strong theoretical connections between (1) those connotations and (2) notions of modularity accepted in biology, specially in evolutionary and in developmental biology, that are thought to be most relevant to arguments to the effect that biological modularity enhances evolvability. (shrink)

I examine an argument that has recently appeared in the cognitive science literature in favor of thinking that the mind is mostly composed of Fodorian-type cognitive modules; an argument that concludes that a mind that is massively composed of classical cognitive mechanisms that are cognitively modular is more evolvable than a mind that is not cognitively modular, since a cognitive mechanism that is cognitively modular is likely to be biologically modular, and biologically modular characters are more evolvable. I argue that (...) the notion of cognitive modularity needed to make this argument plausible will have to be understood in terms of the biological notion of variational independence, as follows: a cognitive feature is cognitively modular only if few or no other morphological changes are significantly correlated with variations of that feature arising in members of the relevant population as a result of ontogeny. I also argue that most of the connotations contained in a cluster of notions of classical cognitive modularity are, as far as we know, irrelevant to the argument, and that only the presence of selective impairments—also known as cognitive dissociations—can be considered as strong indicators of the type of modularity that genuinely enhances evolvability. (shrink)

This essay explores the universal cognitive bases of biological taxonomy and taxonomic inference using cross-cultural experimental work with urbanized Americans and forest-dwelling Maya Indians. A universal, essentialist appreciation of generic species appears as the causal foundation for the taxonomic arrangement of biodiversity, and for inference about the distribution of causally-related properties that underlie biodiversity. Universal folkbiological taxonomy is domain-specific: its structure does not spontaneously or invariably arise in other cognitive domains, like substances, artifacts or persons. It is plausibly an (...) innately-determined evolutionary adaptation to relevant and recurrent aspects of ancestral hominid environments, such as the need to recognize, locate, react to, and profit from many ambient species. Folkbiological concepts are special players in cultural evolution, whose native stability attaches to more variable and difficult-to-learn representational forms, thus enhancing the latter's prospects for regularity and recurrence in transmission within and across cultures. This includes knowledge that cumulatively enriches (folk expertise), overrides (religious belief) or otherwise transcends (science) the commonsense ontology prescribed by folkbiology. Finally, the studies summarized here indicate that results gathered from “standard populations” in regard to biological categorization and reasoning more often than not fail to generalize in straightforward ways to humanity at large. This suggests the need for much more serious attention to cross-cultural research on basic cognitive processes. (shrink)

What follows is a discussion of three sets of experimental results that deal with various aspects of universal biological understanding among American and Maya children and adults. The first set of experiments shows that by the age of four-to-five years urban American and Yukatek Maya children employ a concept of innate species potential, or underlying essence, as an inferential framework for understanding the affiliation of an organism to a biological species, and for projecting known and unknown biological (...) properties to organisms in the face of uncertainty. The second set of experiments shows that the youngest Maya children do not have an anthropocentric understanding of the biological world. Children do not initially need to reason about non-human living kinds by analogy to human kinds. The third set of results show that the same taxonomic rank is cognitively preferred for biological induction in two diverse populations: people raised in the Mid-western USA and Itza' Maya of the Lowland Meso-american rainforest. This is the generic species  the level of oak and robin. These findings cannot be explained by domain-general models of similarity because such models cannot account for why both cultures prefer species-like groups in making inferences about the biological world, although Americans have relatively little actual knowledge or experience at this level. The implication from these experiments is that folk biology may well represent an evolutionary design: universal taxonomic structures, centred on essence-based generic species, are arguably routine products of our ‘habits of mind,' which may be in part naturally selected to grasp relevant and recurrent ‘habits of the world.' The science of biology is built upon these domain-specific cognitive universals: folk biology sets initial cognitive constraints on the development of any possible macro-biological theory, including the initial development of evolutionary theory. Nevertheless, the conditions of relevance under which science operates diverge from those pertinent to folk biology. For natural science, the motivating idea is to understand nature as it is ‘in itself,' independently of the human observer. From this standpoint, the species-concept, like taxonomy and teleology, may arguably be allowed to survive in science as a regulative principle that enables the mind to readily establish stable contact with the surrounding environment, rather than as an epistemic concept that guides the search for truth. (shrink)

Phytomorphology — if concerned with development — often concentrates on correlative changes of form and neglects the aspects of age, time and clock, although the plant's spatial and temporal organisation are intimately interconnected. Common age as measured in physical time by a physical process is compared to biological age as measured by a biological clock based on a biological process. A typical example for a biological clock on the organ level is, for example, a shoot. Its (...) biological age is measured by the biological time unit of a plastochron, which itself is defined by the cyclic-periodic initiation of the leaves. In a controlled environment biological age may replace physical age. However, biological and physical age are not necessarily linearly convertible into each other. In stationary or steady state conditions the repetitive initiation of any organ, unit or module of an articulate plant or plant modular system may define the biological time unit. A linear — monotonous biological process, e.g. axis elongation, may also define a biological time unit as a certain amount of additional growth, e.g. of length. One may speak of periodical and of continuous plastochron or, perhaps, of plastochron and rheochron. A precise measure of biological age is the generalized plastochron index applying to any modular system and module respectively. However, one should be aware that it is based on two clocks, one of them referring to the periodic process of module initiation for counting the integer plastochrons and the other to the continuous plastochron of module growth for the determination of the fraction of one plastochron. The application of the concepts is restricted to phases of stationary or steady state growth and development. In certain cases of non-stationary or non-steady state conditions a normalized-age concept may apply. (shrink)

Universal ranks in folk biological taxonomy probably apply to taxonomies of cultural artifacts. We cannot call folk biological cognition domain-specific and modular. Color categorization may manifest unique organization, which would result from known neurology and the nature of color as an attribute. But folk biology does not adduce equivalent evidence. A global process of increasing differentiation similarly affects folk taxonomy, color categorization, and other practices germane to Atran's anthropology of science; this is beclouded by claims of specificity and (...) modularity. (shrink)

This study synthesizes current information from the various fields of cognitive science in support of a new and exciting theory of mind. Most psychologists study horizontal processes like memory and information flow; Fodor postulates a vertical and modular psychological organization underlying biologically coherent behaviors. This view of mental architecture is consistent with the historical tradition of faculty psychology while integrating a computational approach to mental processes. One of the most notable aspects of Fodor's work is that it articulates features not (...) only of speculative cognitive architectures but also of current research in artificial intelligence. (shrink)

The premise of biological modularity is an ontological claim that appears to come out of practice. We understand that the biological world is modular because we can manipulate different parts of organisms in ways that would only work if there were discrete parts that were interchangeable. This is the foundation of the BioBrick assembly method widely used in synthetic biology. It is one of a number of methods that allows practitioners to construct and reconstruct biological pathways (...) and devices using DNA libraries of standardized parts with known functions. In this paper, we investigate how the practice of synthetic biology reconfigures biological understanding of the key concepts of modularity and evolvability. We illustrate how this practice approach takes engineering knowledge and uses it to try to understand biological organization by showing how the construction of functional parts and processes can be used in synthetic experimental evolution. We introduce a new approach within synthetic biology that uses the premise of a parts-based ontology together with that of organismal self-organization to optimize orthogonal metabolic pathways in E. coli. We then use this and other examples to help characterize semisynthetic categories of modularity, parthood, and evolvability within the discipline. (shrink)

It is unreasonable to assume that our pre-scientific emotion vocabulary embodies all and only those distinctions required for a scientific psychology of emotion. The psychoevolutionary approach to emotion yields an alternative classification of certain emotion phenomena. The new categories are based on a set of evolved adaptive responses, or affect-programs, which are found in all cultures. The triggering of these responses involves a modular system of stimulus appraisal, whose evoluations may conflict with those of higher-level cognitive processes. Whilst the structure (...) of the adaptive responses is innate, the contents of the system which triggers them are largely learnt. The circuits subserving the adaptive responses are probably located in the limbic system. This theory of emotion is directly applicable only to a small sub-domain of the traditional realm of emotion. It can be used, however, to explain the grouping of various other phenomena under the heading of emotion, and to explain various characteristic failings of the pre-scientific conception of emotion. (shrink)

It is unreasonable to assume that our pre-scientific emotion vocabulary embodies all and only those distinctions required for a scientific psychology of emotion. The psychoevolutionary approach to emotion yields an alternative classification of certain emotion phenomena. The new categories are based on a set of evolved adaptive responses, or affect-programs, which are found in all cultures. The triggering of these responses involves a modular system of stimulus appraisal, whose evoluations may conflict with those of higher-level cognitive processes. Whilst the structure (...) of the adaptive responses is innate, the contents of the system which triggers them are largely learnt. The circuits subserving the adaptive responses are probably located in the limbic system. This theory of emotion is directly applicable only to a small sub-domain of the traditional realm of emotion. It can be used, however, to explain the grouping of various other phenomena under the heading of emotion, and to explain various characteristic failings of the pre-scientific conception of emotion. (shrink)

This work is mainly concerned with the notion of hierarchical modularity and its use in explaining structure and dynamical behavior of complex systems by means of hierarchical modular models, as well as with a concept of my proposal, antimodularity, tied to the possibility of the algorithmic detection of hierarchical modularity. Specifically, I highlight the pragmatic bearing of hierarchical modularity on the possibility of scientific explanation of complex systems, that is, systems which, according to a chosen basic description, (...) can be considered as composed of elementary, discrete, interrelated parts. I stress that hierarchical modularity is also required by the experimentation aimed to discover the structure of such systems. Algorithmic detection of hierarchical modularity turns out to be a task plagued by the demonstrated computational intractability of the search for the best hierarchical modular description, and by the high computational expensiveness of even approximated detection methods. Antimodularity consists in the lack of a modular description fitting the needs of the observer, a lack due either to absence of modularity in the system’s chosen basic description, or to the impossibility, due to the excessive size of the system under assessment in relation to the computational cost of algorithmic methods, to algorithmically produce a valid hierarchical description. I stress that modularity and antimodularity depend on the pragmatic choice of a given basic description of the system, a choice made by the observer based on explanatory goals. I show how antimodularity hinders the possibility of applying at least three well-known types of explanation: mechanistic, deductive-nomological and computational. A fourth type, topological explanation, remains unaffected. I then assess the presence of modularity in biological systems, and evaluate the possible consequences, and the likelihood, of incurring in antimodularity in biology and other sciences, concluding that this eventuality is quite likely, at least in systems biology. I finally indulge in some metaphysical and historical speculations: metaphysically, antimodularity seems to suggest a possible position according to which natural kinds are detected modules, and as such, due to the computational hardness of the detection of the best hierarchical modular description, they are unlikely to be the best possible way to describe the world, because the modularity of natural kinds quite probably does not reflect the best possible modularity of the world. From an historical point of view, the growing use of computational methods for modularity detection or simulation of complex systems, especially in certain areas of scientific research, hints at the envisioning of a multiplicity of emerging scientific disciplines guided by a self- sustained, growing production of possibly human-unintelligible explanations. This, I suggest, would constitute an historical change in science, which, if has not already occurred, could well be on the verge of happening. (shrink)

Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship (...) between that structure and function fails to be manipulable independent of other causal relationships within the system. Contrary to this line of reasoning, I argue that functional robustness often attends feedback control, rather than failures of modularity. Feedback control poses its own challenges to causal explanation and inference, but those challenges do not undermine modularity—and indeed, modularity is crucial to grappling with them. (shrink)

My charge in this chapter is to set out the positive case supporting massively modular models of the human mind.1 Unfortunately, there is no generally accepted understanding of what a massively modular model of the mind is. So at least some of our discussion will have to be terminological. I shall begin by laying out the range of things that can be meant by ‘modularity’. I shall then adopt a pair of strategies. One will be to distinguish some things (...) that ‘modularity’ definitely can’t mean, if the thesis of massive modularity is to be even remotely plausible. The other will be to look at some of the arguments that have been offered in support of massive modularity, discussing what notion of ‘module’ they might warrant. It will turn out that there is, indeed, a strong case in support of massively modular models of the mind on one reasonably natural understanding of ‘module’. But what really matters in the end, of course, is the substantive question of what sorts of structure are adequate to account for the organization and operations of the human mind, not whether or not the components appealed to in that account get described as ‘modules’. So the more interesting question before us is what the arguments that have been offered in support of massive modularity can succeed in showing us about those structures, whatever they get called. (shrink)

Synthetic biology aims at making life easier to an engineer by applying biotechnology engineering principles such as standardization and modularity. I argue that living organisms are inherently non-machine, non-standardized entities and that the current state-of-the-art in SynBio combines pre- and post-standardization efforts, in a scenario without evidence that full standardization in biology is even possible. I finally propose a new view on SynBio based on purpose rather than on technicalities.

There are various approaches to ontology metamodelling, and the notion of biologically inspired modular knowledge representation systems can provide insight in the workings of such phenomena as emergent properties of network structures. What is more relevant from knowledge engineering standpoint, such approach could provide innovation and enhancement of the level of expression as well as overall functionality of modular ontologies. To do so, one needs to find biological structures that would be the basis for modularity on different levels (...) of hierarchy within the artificial system. Network analysis tools as well as systems biology and biocomputing provide a framework for research in this field. (shrink)

In their reviews, Chater and Oaksford, Dutilh Novaes, and Sterelny are critical of our modularist approach to reason. In this response, we clarify our claim that reason is one of many cognitive modules that produce intuitive inferences each in its domain; the reason module producing intuitions about reasons. We argue that in‐principle objections to the idea of massive modularity based on Fodor's peculiar approach are not effective against other interpretations that have led to insightful uses of the notion in (...) psychology and biology. We explain how the reason module evaluates reasons on the basis of their metacognitive properties. We show how the module fulfils a social function, that of producing reasons to justify oneself and convince others and of evaluating the reasons others produce to convince us. (shrink)

In a recent survey of contemporary philosophy of emotion, Ronald de Sousa states that "in recent years … emotions have once again become the focus of vigorous interest in philosophy, as well as in other branches of cognitive science" (de Sousa 2003, 1). He then goes on to make the important observation that "in view of the proliferation of increasingly fruitful exchanges between researchers of different stripes, it is no longer useful to speak of the philosophy of emotion in isolation (...) from the approaches of other disciplines, particularly psychology, neurology and evolutionary biology" (de Sousa 2003, 1). This last remark is particularly apt in the case of a topic like modularity and emotion, which represents an ideal opportunity for reflecting on the emerging alliance between the philosophy of emotion and emotion science. In addition to being interesting in its own right, the topic also illustrates some of the perils associated with the new alliance, as different academic traditions must adapt to interdisciplinary dialogue... (shrink)

The leading hypothesis concerning the “reuse” or “recycling” of neural circuits builds on the assumption that evolution might prefer the redeployment of established circuits over the development of new ones. What conception of cognitive architecture can survive the evidence for this hypothesis? In particular, what sorts of “modules” are compatible with this evidence? I argue that the only likely candidates will, in effect, be the columns which Vernon Mountcastle originally hypothesized some 60 years ago, and which form part of the (...) well-known columnar hypothesis in neuroscience—systems that cannot handle gross cognitive functions as distinct from strictly exiguous subfunctions. This is in stark contrast to the modules postulated by much of cognitive psychology, cognitive neuropsychology, and evolutionary psychology. And yet the fate of this revised notion is unclear. The main issue confronting it is the effect of the neural network context on local function. At some point the effects of context are so strong that the degree of specialization required for modularity is not able to be met. Still, despite indications from neuroimaging that peripheral and central systems deploy shared circuitry, some skills clearly do seem to display modularization and autonomy. This article: provides an in-depth analytical and historical review of the fortunes of modular thinking in cognitive science; offers a systematic calibration of brain regions in terms of degrees of functional specificity and robustness; and suggests another way of accounting for the partially encapsulated character of expertise and other highly practiced skills without having to resort to domain-specific modules. (shrink)

This essay in the "anthropology of science" is about how cognition constrains culture in producing science. The example is folk biology, whose cultural recurrence issues from the very same domain-specific cognitive universals that provide the historical backbone of systematic biology. Humans everywhere think about plants and animals in highly structured ways. People have similar folk-biological taxonomies composed of essence-based species-like groups and the ranking of species into lower- and higher-order groups. Such taxonomies are not as arbitrary in structure and (...) content, nor as variable across cultures, as the assembly of entities into cosmologies, materials or social groups. (shrink)

Evolutionary developmental biology (“evo-devo”) may provide insights and new methods for studies of cognition and cultural evolution. For example, I propose using cultural selection and individual learning to examine constraints on cultural evolution. Modularity, the idea that traits vary independently, can facilitate evolution (increase “evolvability”), because evolution can act on one trait without disrupting another. I explore links between cognitive modularity, evolutionary modularity, and cultural evolvability. (Published Online November 9 2006).

Modularity has become a central and remarkably useful concept in evolutionary developmental biology, offering an explanation of how independent, interacting units make possible developmental events and evolutionary changes. These modules exist at several different levels of organization, from genes to signal transduction pathways to cell populations. Cell populations, which are multicellular modules, provide an opportunity both to clarify our notion of modularity and to reexamine such central concepts as cell-to-cell communication. Rosine Chandebois’s work on “cell sociology” is reframed (...) in the language of modularity in order to show how groups of cells maintain their collective identity during development and how signaling information from the group’s environment is received by the constituent cells. In a “test case” for our account of multicellular modules, we consider the vertebrate neural crest, a migratory cell population made up of several subpopulations. The neural crest proves yet again to be a complex case, showing the importance of taking into account both developmental and evolutionary transformations of multicellular modules. (shrink)

This paper explores the connections between inheritance systems, evolvability and modularity. I argue that the transmission of symbiotic micro-organisms is an inheritance system, and one that is evolutionarily significant because symbionts generate biologically crucial aspects of their hosts’ organisation through modular developmental pathways. More specifically, I develop and defend five theses.

Synthetic biology presents a challenge to traditional accounts of biology: Whereas traditional biology emphasizes the evolvability, variability, and heterogeneity of living organisms, synthetic biology envisions a future of homogeneous, humanly engineered biological systems that may be combined in modular fashion. The present paper approaches this challenge from the perspective of the epistemology of technoscience. In particular, it is argued that synthetic-biological artifacts lend themselves to an analysis in terms of what has been called ‘thing knowledge’. As such, they (...) should neither be regarded as the simple outcome of applying theoretical knowledge and engineering principles to specific technological problems, nor should they be treated as mere sources of new evidence in the general pursuit of scientific understanding. Instead, synthetic-biological artifacts should be viewed as partly autonomous research objects which, qua their material-biological constitution, embody knowledge about the natural world—knowledge that, in turn, can be accessed via continuous experimental interrogation. (shrink)

Evolutionary psychologists argue that selective pressures in our ancestral environment yield a highly specialized set of modular cognitive capacities. However, recent papers in developmental psychology and neuroscience claim that evolutionary accounts of modularity are incompatible with the flexibility and plasticity of the developing brain. Instead, they propose cortical and neuronal brain structures are fixed through interactions with our developmental environment. Buller and Gray Hardcastle contend that evolutionary accounts of cognitive development are unacceptably rigid in light of evidence of cortical (...) plasticity. The developing structure of the brain is both too random and too sensitive to external stimuli to be the product of a fixed genetic mechanism. They also claim that the complexity of the human brain cannot be explained in terms of our meager genetic endowment. There simply are not enough genes to program the intricate neuronal structures that are essential to cognition. I argue that neither of these arguments are persuasive. Small numbers of genes can function to determine diverse phenotypical outcomes through evolutionarily selected developmental systems. Similarly, theories of modularity do not rule out the possibility that innate cognitive systems exploit environmental regularities to guide the developing structure of the brain. Consequently, the anti-adaptionist consequences of these positions should be rejected. (shrink)

The conception of a modular structure of mind, which postulates that the mind is composed of more or less autonomous subsystems, is widespread in contemporary psychology. Proponents of a modular structure of the mind, such as Marshall (1980; 1984; 1985), Fodor (1983), Gardner (1983), and Shallice (1988), have linked their work to F. J. Gall's theory of organology or of the “functions of the brain”. This paper argues: (1) Gall's organology defends a view of the capacities of the mind that (...) relies on a specific relation between the organism and its organs. The organs of Gall stem from and originate “needs” so that they embody not so much processing capacities, but perception-for-action cycles. (2) Modules and organs arise at different levels of description that cannot be easily matched. (3) It is just this central distinction between organs and modules which explains the inherent relation between organology, comparative biology and differential psychology on the one hand and modularity and cognitive science on the other. (shrink)

For some, biology explains all there is to know about the mind. Yet many big questions remain: is the mind shaped by genes or the environment? If mental traits are the result of adaptations built up over thousands of years, as evolutionary psychologists claim, how can such claims be tested? If the mind is a machine, as biologists argue, how does it allow for something as complex as human consciousness? The Biological Mind: A Philosophical Introduction explores these questions and (...) more, using the philosophy of biology to introduce and assess the nature of the mind. Drawing on the four key themes of evolutionary biology; molecular biology and genetics; neuroscience; and biomedicine and psychiatry Justin Garson addresses the following key topics: moral psychology, altruism and levels of selection evolutionary psychology and modularity genes, environment and the nature-nurture debate neuroscience, reductionism and the relation between biology and free will function, selection and mental representation psychiatric classification and the maladapted mind. Extensive use of examples and case studies is made throughout the book, and additional features such as chapter summaries, annotated further reading and a glossary make this an indispensable introduction to those teaching philosophy of mind and philosophy of psychology. It will also be an excellent resource for those in related fields such as biology. (shrink)

Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic program or genetic control. Still, we (...) suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems. (shrink)

Although the concept of modularity is pervasive across fields and disciplines, philosophers and scientists use the term in a variety of different ways. This paper identifies two distinct ways of thinking about modularity, and considers what makes them similar and different. For philosophers of mind and cognitive science, cognitive modularity helps explain the capacities of brains to process sundry and distinct kinds of informational input. For philosophy of biology and evolutionary science, biological modularity helps explain (...) the capacity of random evolutionary processes to give rise to highly complex and sophisticated biological systems. Although these different ways of thinking about modularity are largely distinct, this paper proposes a unifying feature common to both: isolability, or the capacity of subsystems to undergo changes without resulting in substantial changes to neighboring or interconnected subsystems. (shrink)

Discovery proceeds in stages of construction, evaluation, and revision. Each of these stages is constrained by what is known or conjectured about what is being discovered. A new characterization of mechanism aids in specifying what is to be discovered when a mechanism is sought. Guidance in discovering mechanisms may be provided by the reasoning strategies of schema instantiation, modular subassembly, and forward/backward chaining. Examples are found in mechanisms in molecular biology, biochemistry, immunology, and evolutionary biology.

Discovery proceeds in stages of construction, evaluation, and revision. Each of these stages is constrained by what is known or conjectured about what is being discovered. A new characterization of mechanism aids in specifying what is to be discovered when a mechanism is sought. Guidance in discovering mechanisms may be provided by the reasoning strategies of schema instantiation, modular subassembly, and forward/backward chaining. Examples are found in mechanisms in molecular biology, biochemistry, immunology, and evolutionary biology.

It is commonly supposed that evolutionary explanations of cognitive phenomena involve the assumption that the capacities to be explained are both innate and modular. This is understandable: independent selection of a trait requires that it be both heritable and largely decoupled from other ”nearby’ traits. Cognitive capacities realized as innate modules would certainly satisfy these contraints. A viable evolutionary cognitive psychology, however, requires neither extreme nativism nor modularity, though it is consistent with both. In this paper, we seek to (...) show that rather weak assumptions about innateness and modularity are consistent with evolutionary explanations of cognitive capacities. Evolutionary pressures can affect the degree to which the development of a capacity is canalized by biasing acquisition/learning in ways that favor development of concepts and capacities that proved adaptive to an organism’s ancestors. (shrink)

The aim of synthetic biology is to rationally design devices, systems, and organisms with desired innovative and useful functions (Slusarczyk, Lin, and Weiss 2012). To achieve this aim, synthetic biology uses a concept similar to engineering sciences: well-characterized and standardized modular biological building blocks are reassembled in a systematic and rational manner to generate complex devices and systems with a predicted function. In the past, molecular biological research in combination with intense work in new research areas like systems (...) biology and functional genomics revealed a large inventory of multifaceted modular biological parts that are now in the toolboxes of synthetic biologists. Due to .. (shrink)

Evolutionary developmental biology (Evo-devo) is a loose conglomeration of research programs in the life sciences with two main axes: (a) the evolution of development, or inquiry into the pattern and processes of how ontogeny varies and changes over time; and, (b) the developmental basis of evolution, or inquiry into the causal impact of ontogenetic processes on evolutionary trajectories—both in terms of constraint and facilitation. Philosophical issues are found along both axes surrounding concepts such as evolvability, novelty, and modularity. The (...) developmental basis of evolution has garnered much attention because it speaks to the possibility of revising a standard construal of evolutionary theory, but the evolution of development harbors its own conceptual questions. This article addresses the heterogeneity of Evo-devo’s conglomerate structure (including disagreements over its individuation), as well as the concepts and controversies of philosophical interest pertaining to the evolution of development and the developmental basis of evolution. Future research will benefit from a shift away from global theorizing toward the scientific practices of Evo-devo. (shrink)

It is commonly supposed that evolutionary explanations of cognitive phenomena involve the assumption that the capacities to be explained are both innate and modular. This is understandable: independent selection of a trait requires that it be both heritable and largely decoupled from other `nearby' traits. Cognitive capacities realized as innate modules would certainly satisfy these contraints. A viable evolutionary cognitive psychology, however, requires neither extreme nativism nor modularity, though it is consistent with both. In this paper, we seek to (...) show that rather weak assumptions about innateness and modularity are consistent with evolutionary explanations of cognitive capacities. Evolutionary pressures can affect the degree to which the development of a capacity is canalized by biasing acquisition/ learning in ways that favor development of concepts and capacities that proved adaptive to an organism's ancestors. q 1999 Elsevier Science B.V. All rights reserved. (shrink)

Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...) broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation. (shrink)

A number of debates in philosophy of biology and psychology, as well as in their respective sciences, hinge on particular views about the relationship between genotypes and phenotypes. One such view is that the genotype-phenotype relationship is relatively straightforward, in the sense that a genome contains the ?genes for? the various traits that an organism exhibits. This leads to the assumption that if a particular set of traits is posited to be present in an organism, there must be a corresponding (...) number of genes in that organism's genome to account for those traits. This assumption underlies what can be called the ?counting argument,? in which empirical estimates of the number of genes in a genome are used to support or refute particular hypotheses in philosophical debates about biology and psychology. In this paper, we assess the counting argument as it is used in discussions of the alleged massive modularity of the brain, and conclude that this argument cannot be upheld in light of recent philosophical work on gene concepts and empirical work on genome complexity. In doing so, we illustrate that there are those on both sides of the debate about massive modularity who rely on an incorrect view of gene concepts and the nature of the genotype-phenotype relationship. (shrink)

A classic analytic approach to biological phenomena seeks to refine definitions until classes are sufficiently homogenous to support prediction and explanation, but this approach founders on cases where a single process produces objects with similar forms but heterogeneous behaviors. I introduce object spaces as a tool to tackle this challenging diversity of biological objects in terms of causal processes with well-defined formal properties. Object spaces have three primary components: (1) a combinatorial biological process such as protein synthesis (...) that generates objects with parts that are modular, independent, and organized according to an invariant syntax; (2) a notion of “distance” that relates the objects according to rules of change over time as found in nature or useful for algorithms; (3) mapping functions defined on the space that map its objects to other spaces or apply an evaluative criterion to measure an important quality, such as parsimony or biochemical function. Once defined, an object space can be used to represent and simulate the dynamics of phenomena on multiple scales; it can also be used as a tool for predicting higher-order properties of the objects, including stitching together series of causal processes. Object spaces are the basis for a strategy of theorizing, discovery, and analysis in biology: as heuristic idealizations of biology, they help us transform inchoate, intractable problems into articulated, well-structured ones. Developing an object space is a research strategy with a long, successful history under many other names, and it offers a unifying but not overreaching approach to biological theory. (shrink)

Synthetic biology emerged around 2000 as a new biological discipline. It shares with systems biology the same modular vision of organisms, but is more concerned with applications than with a better understanding of the functioning of organisms. A herald of this new discipline is Craig Venter who aims to create an artificial microorganism with the minimal genome compatible with life and to implement into it different 'functional modules' to generate new micro-organisms adapted to specific tasks. Synthetic biology is based (...) on the possibilities raised by genetic engineering, but it aims to engineer organisms, and not simply to modify them, mimicking the practice of computer engineers. Three points will be discussed: In what regard does synthetic biology represent a new epistemology of the life sciences? What are the relations between synthetic biology and evolutionary biology? What is the raison d'être of synthetic biology as a discipline independent of nanotechnologies? (shrink)

While there is ongoing debate about the existence of basic emotions and about their status as natural kinds, these debates usually carry on under the assumption that basic emotions are modular and therefore cannot account for behavioral variability in emotional situations. Moreover, both sides of the debate have assumed that these putative features of basic emotions distinguish them as products of evolution rather than products of culture and experience. I argue that these assumptions are unwarranted, that there is empirical evidence (...) against them, and that evolutionary theory itself should not lead us to expect that behavioral invariability and modularity mark the distinction between evolved emotions and higher cognitive emotions. I further suggest that claims about behavioral invariability and modularity have functioned as defeasible conjectures aimed at helping test basic emotion theory. Finally, I draw out the implications of these claims for debates about the existence of basic emotions in humans. (shrink)

I see in the nature of our minds and the character of our problem-solving methodologies a search for simplifying tools that will let us model a complex world and get away with it far more often than we might suppose. As it turns out, this broad a reach to mind and world is possible because both turn on common properties of evolved complex adaptive systems. These are in effect “design principles” for the architecture of nature—all of it, from biological (...) systems to ourselves and the technologies that we engineer.I explore how generative systems may, under some circumstances lead to adaptive radiations, and how the growth of complexity is entailed by their compositional embedding of prior systems, their stabilizing their features as architecture thru a process that I call generative entrenchment. I also explore how modularity has two forms: top-down modularity or “quasi-independence” in which evolving systems require the possibility of changing parts of the system without scrambling the organization of the rest, and bottom-up modularity in which a stable alphabet of standardized parts can be combined in various ways to generate an adaptive radiation of diverse systems to accomplish different things. (shrink)

A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned (...) in connectionist models and neural coding in brain and often dismiss localist theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. (shrink)

But as for most genes, they are not the units of interest once we get to the network level: it is the whole conspiracy we care about. Biologists, more precisely evolutionary biologists, and not only psychologists and philosophers also speak of modularity. However the way in which this theoretical construct functions in their discipline is relatively different from the role it obtains in evolutionary psychology and cognitive science. Rather than postulating modules to explain particular traits of organisms, such as (...) the specificity of input systems or limitations of human reasoning abilities, biologists originally simply assume that some form of modularity constitutes a precondition of evolution. They argue that, in order for natural selection to fine tune organisms to their environment, different traits must be able to evolve independently from one another. This implies modularity in one form or another. Organisms will only be able to adapt if they do not come all in one piece, so to speak. It must therefore be possible for changes to occur in one characteristic of an animal without those changes having repercussions throughout the whole organism. (shrink)

It is widely assumed that functional and dispositional properties are not identical to their physical base, but that there is some kind of asymmetrical ontological dependence between them. In this regard, a popular idea is that the former are realized by the latter, which, under the non-identity assumption, is generally understood to be a non-causal, constitutive relation. In this paper we examine two of the most widely accepted approaches to realization, the so-called ‘flat view’ and the ‘dimensioned view’, and we (...) analyze their explanatory relevance in the light of a number of examples from the life sciences, paying special attention to developmental phenomena. Our conclusion is that the emphasis placed by modern-day biology on such properties as variability, evolvability, and a whole collection of phenomena like modularity, robustness, and developmental constraint or developmental bias requires the adoption of a much more dynamic perspective than traditional realization frameworks are able to capture. (shrink)