The power of possibility: causal learning, counterfactual reasoning, and pretend play

We argue for a theoretical link between the development of an extended period of immaturity in human evolution and the emergence of powerful and wide-ranging causal learning mechanisms, specifically the use of causal models and Bayesian learning. We suggest that exploratory childhood learning, childhood play in particular, and causal cognition are closely connected. We report an empirical study demonstrating one such connection--a link between pretend play and counterfactual causal reasoning. Preschool children given new information about a causal system made very similar inferences both when they considered counterfactuals about the system and when they engaged in pretend play about it. Counterfactual cognition and causally coherent pretence were also significantly correlated even when age, general cognitive development and executive function were controlled for. These findings link a distinctive human form of childhood play and an equally distinctive human form of causal inference. We speculate that, during human evolution, computations that were initially reserved for solving particularly important ecological problems came to be used much more widely and extensively during the long period of protected immaturity.     

On the thermodynamics of multilevel evolution

Biodiversity is hierarchically structured both phylogenetically and functionally. Phylogenetic hierarchy is understood as a product of branching organic evolution as described by Darwin. Ecosystem biologists understand some aspects of functional hierarchy, such as food web architecture, as a product of evolutionary ecology; but functional hierarchy extends to much lower scales of organization than those studied by ecologists. We argue that the more general use of the term “evolution” employed by physicists and applied to non-living systems connects directly to the narrow biological meaning. Physical evolution is best understood as a thermodynamic phenomenon, and this perspective comfortably includes all of biological evolution. We suggest four dynamical factors that build on each other in a hierarchical fashion and set the stage for the Darwinian evolution of biological systems: (1) the entropic erosion of structure; (2) the construction of dissipative systems; (3) the reproduction of growing systems and (4) the historical memory accrued to populations of reproductive agents by the acquisition of hereditary mechanisms. A particular level of evolution can underpin the emergence of higher levels, but evolutionary processes persist at each level in the hierarchy. We also argue that particular evolutionary processes can occur at any level of the hierarchy where they are not obstructed by material constraints. This theoretical framework provides an extensive basis for understanding natural selection as a multilevel process. The extensive literature on thermodynamics in turn provides an important advantage to this perspective on the evolution of higher levels of organization, such as the evolution of altruism that can accompany the emergence of social organization.     

Causation and the Origin of Life. Metabolism or Replication First?

The conceptual gulf that separates the 'metabolism first' and 'replication first' mechanisms for the emergence of life continues to cloud the origin of life debate. In the present paper we analyze this aspect of the origin of life problem and offer arguments in favor of the 'replication first' school. Utilizing Wicken's two-tier approach to causation we argue that a causal connection between replication and metabolism can only be demonstrated if replication would have preceded metabolism. In conjunction with existing empirical evidence and theoretical reasoning, our analysis concludes that there is no substantive evidence for a 'metabolism first' mechanism for life's emergence, while a coherent case can be made for the 'replication first' group of mechanisms. The analysis reaffirms our conviction that life is an extreme expression of kinetic control, and that the emergence of metabolic pathways can be understood by considering life as a manifestation of 'replicative chemistry'.     

The concept of mechanism in biology

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.     

Molecular characteristics of the heterochromatic I elements from a reactive strain ofDrosophila melanogaster

Summary There are two categories of strains inDrosophila melanogaster with respect to the I-R system of hybrid dysgenesis. The inducer strains contain particular transposable elements named I factors. They are not present in the strains of the other category called reactive (R) strains. Defective I elements are present in the pericentromeric regions of both categories of strains. This last subfamily of I sequences has not yet been described in detail and little is known about its origin. In this paper, we report that the defective I elements display an average of 94% of sequence identity with each other and with the transposable I factor. The results suggest that they cannot be the progenitors of the present day I factors, but that each of these two subfamilies started to evolve independently several million years ago. Furthermore, the sequence comparison of these I elements with an active I factor fromDrosophila teissieri provides useful information about when the deleted I elements became immobilized.     

Integrating the Multiple Biological Causes of Human Behavior

I introduce a range of examples of different causal hypotheses about human mate selection. The hypotheses I focus on come from evolutionary psychology, fluctuating asymmetry research and chemical signaling research. I argue that a major obstacle facing an integrated biology of human behavior is the lack of a causal framework that shows how multiple proximate causal mechanisms can act together to produce components of our behavior.     

Emergence in the central nervous system

“Emergence” is an idea that has received much attention in consciousness literature, but it is difficult to find characterizations of that concept which are both specific and useful. I will precisely define and characterize a type of epistemic (“weak”) emergence and show that it is a property of some neural circuits throughout the CNS, on micro-, meso- and macroscopic levels. I will argue that possession of this property can result in profoundly altered neural dynamics on multiple levels in cortex and other systems. I will first describe emergent neural entities (ENEs) abstractly. I will then show how ENEs function specifically and concretely, and demonstrate some implications of this type of emergence for the CNS.     

Vacated niches,competitive release and the community ecology of pathogen eradication

A recurring theme in the epidemiological literature on disease eradication is that each pathogen occupies an ecological niche, and eradication of one pathogen leaves a vacant niche that favours the emergence of new pathogens to replace it. However, eminent figures have rejected this view unequivocally, stating that there is no basis to fear pathogen replacement and even that pathogen niches do not exist. After exploring the roots of this controversy, I propose resolutions to disputed issues by drawing on broader ecological theory, and advance a new consensus based on robust mechanistic principles. I argue that pathogen eradication (and cessation of vaccination) leads to a ‘vacated niche’, which could be re-invaded by the original pathogen if introduced. Consequences for other pathogens will vary, with the crucial mechanisms being competitive release, whereby the decline of one species allows its competitors to perform better, and evolutionary adaptation. Hence, eradication can cause a quantitative rise in the incidence of another infection, but whether this leads to emergence as an endemic pathogen depends on additional factors. I focus on the case study of human monkeypox and its rise following smallpox eradication, but also survey how these ideas apply to other pathogens and discuss implications for eradication policy.     

Emergence,therefore antireductionism? A critique of emergent antireductionism

Emergent antireductionism in biological sciences states that even though all living cells and organisms are composed of molecules, molecular wholes are characterized by emergent properties that can only be understood from the perspective of cellular and organismal levels of composition. Thus, an emergence claim (molecular wholes are characterized by emergent properties) is thought to support a form of antireductionism (properties of higher-level molecular wholes can only be understood by taking into account concepts, theories and explanations dealing with higher-level entities). I argue that this argument is flawed: even if molecular wholes are characterized by emergent properties and even if many successful explanations in biology are not molecular, there is no entailment between the two claims.     

Beyond Disciplinary Boundaries: Leptospirosis as a Model of Incorporating Transdisciplinary Approaches to Understand Infectious Disease Emergence

Leptospirosis is a zoonotic infectious disease of global significance. Political, economic, demographic, ecologic, and other anthropogenically driven environmental changes have fueled the reemergence of this disease in industrialized and developing countries, and in both urban and rural settings. We argue that conventional disciplinary, even interdisciplinary, research methods are not sufficient to elucidate the complex mechanisms and causal relationships among the myriad factors responsible for infectious disease emergence. To address the significant gaps in the field of leptospirosis, an integrated research agenda is needed to guide successful public health remediation of the disease. Based on both working group analysis of literature and newly obtained information, we describe cross-disciplinary collaborative approaches that allow a novel approach to understand leptospirosis emergence with regard to mountain-to-sea ecosystems in Hawai‘i and other region-specific ecosystems. Leptospirosis research is a model for how complementary disciplines in the social, cultural, ecological, and biomedical sciences can optimally interact towards a higher understanding of emerging infectious diseases.     

Nonlinear developmental processes as sources of dominance

Phenotypes are the products of developmental processes whose dynamics are controlled by genes. In many developmental processes there is a nonlinear relationship between genetic variation and phenotypic variation. These nonlinear relationships can result in the emergence of dominance among alleles that control the developmental process. We explore the properties of dominance relationships in a simple developmental system consisting of a diffusion-gradient-threshold mechanism commonly deployed in pattern formation. We show that a single nonlinear process (diffusion) within this integrated mechanism leads to the emergence of dominance in all components of the mechanism. Unlike the situation in metabolic pathways, where new mutations are most likely to be recessive, the structure of the nonlinearities in this developmental mechanism is such that in certain circumstances new mutations are equally likely to be dominant or recessive. Although the dominance we observe in this system is the result of a physiological process, we also find that dominance can evolve by microevolutionary mechanisms and thus are able to reconcile the opposing views of Fisher and Wright on dominance.     

Emergent properties and the context objection to reduction

Reductionism is a central issue in the philosophy of biology. One common objection to reduction is that molecular explanation requires reference to higher-level properties, which I refer to as the context objection. I respond to this objection by arguing that a well-articulated notion of a mechanism and what I term mechanism extension enables one to accommodate the context-dependence of biological processes within a reductive explanation. The existence of emergent features in the context could be raised as an objection to the possibility of reduction via this strategy. I argue that this objection can be overcome by showing that there is no tenable argument for the existence of emergent properties that are not susceptible to a reductive explanation.     

Phenotypic and dynamical transitions in model genetic networks. I. Emergence of patterns and genotype-phenotype relationships

SUMMARY Genotype–phenotype interactions during the evolution of form in multicellular organisms is a complex problem but one that can be aided by computational approaches. We present here a framework within which developmental patterns and their underlying genetic networks can be simulated. Gene networks were chosen to reflect realistic regulatory circuits, including positive and negative feedback control, and the exchange of a subset of gene products between cells, or within a syncytium. Some of these networks generate stable spatial patterns of a subset of their molecular constituents, and can be assigned to categories (e.g., "emergent" or "hierarchic") based on the topology of molecular circuitry. These categories roughly correspond to what has been discussed in the literature as "self-organizing" and "programmed" processes of development. The capability of such networks to form patterns of repeating stripes was studied in network ensembles in which parameters of gene-gene interaction were caused to vary in a manner analogous to genetic mutation. The evolution under mutational change of individual representative networks of each category was also simulated. We have found that patterns with few stripes (≤3) are most likely to originate in the form of a hierarchic network, whereas those with greater numbers of stripes (≥4) originate most readily as emergent networks. However, regardless of how many stripes it contains, once a pattern is established, there appears to be an evolutionary tendency for emergent mechanisms to be replaced by hierarchic mechanisms. These results have potential significance for the understanding of genotype-phenotype relationships in the evolution of metazoan form.     

Mechanisms, determination and the metaphysics of neuroscience

In this paper, I evaluate recently defended mechanistic accounts of the unity of neuroscience from a metaphysical point of view. Considering the mechanistic framework in general (Sections 2 and 3), I argue that explanations of this kind are essentially reductive (Section 4). The reductive character of mechanistic explanations provides a sufficiency criterion, according to which the mechanism underlying a certain phenomenon is sufficient for the latter. Thus, the concept of supervenience can be used in order to describe the relation between mechanisms and phenomena (Section 5). Against this background, I show that the mechanistic framework is subject to the causal exclusion problem and faces the classical metaphysical options when it comes to the relations obtaining between different levels of mechanisms (Section 6). Finally, an attempt to improve the metaphysics of mechanisms is made (Section 7) and further difficulties are pointed out (Section 8).     

The evolution of connectivity in metabolic networks

Processes in living cells are the result of interactions between biochemical compounds in highly complex biochemical networks. It is a major challenge in biology to understand causes and consequences of the specific design of these networks. A characteristic design feature of metabolic networks is the presence of hub metabolites such as ATP or NADH that are involved in a high number of reactions. To study the emergence of hub metabolites, we implemented computer simulations of a widely accepted scenario for the evolution of metabolic networks. Our simulations indicate that metabolic networks with a large number of highly specialized enzymes may evolve from a few multifunctional enzymes. During this process, enzymes duplicate and specialize, leading to a loss of biochemical reactions and intermediary metabolites. Complex features of metabolic networks such as the presence of hubs may result from selection of growth rate if essential biochemical mechanisms are considered. Specifically, our simulations indicate that group transfer reactions are essential for the emergence of hubs.     

The effect of population structure on the adaptive radiation of microbial populations evolving in spatially structured environments

Spatial structure is thought to be an important factor influencing the emergence and maintenance of genetic diversity. Previous studies have demonstrated that environmental heterogeneity, provided by spatial structure, leads to adaptive radiation of populations. In the present study, we investigate not only the impact of environmental heterogeneity on adaptive radiation, but also of population fragmentation and niche construction. Replicate populations founded by a single genotype of Escherichia coli were allowed to evolve for 900 generations by serial transfer in either a homogeneous environment, or a spatially structured environment that was either kept intact or destroyed with each daily transfer. Only populations evolving in the structured environment with intact population structure diversified: clones are significantly divergent in sugar catabolism, and show frequency-dependent fitness interactions indicative of stable coexistence. These findings demonstrate an important role for population fragmentation, a consequence of population structure in spatially structured environments, on the diversification of populations.     

Molecular mechanisms underlying the emergence of bacterial pathogens: an ecological perspective

The rapid emergence of new bacterial diseases negatively affects both human health and agricultural productivity. Although the molecular mechanisms underlying these disease emergences are shared between human‐ and plant‐pathogenic bacteria, not much effort has been made to date to understand disease emergences caused by plant‐pathogenic bacteria. In particular, there is a paucity of information in the literature on the role of environmental habitats in which plant‐pathogenic bacteria evolve and on the stress factors to which these microbes are unceasingly exposed. In this microreview, we focus on three molecular mechanisms underlying pathogenicity in bacteria, namely mutations, genomic rearrangements and the acquisition of new DNA sequences through horizontal gene transfer (HGT). We briefly discuss the role of these mechanisms in bacterial disease emergence and elucidate how the environment can influence the occurrence and regulation of these molecular mechanisms by directly impacting disease emergence. The understanding of such molecular evolutionary mechanisms and their environmental drivers will represent an important step towards predicting bacterial disease emergence and developing sustainable management strategies for crops.     

Evolving experience-dependent robust behaviour in embodied agents

In this work, based on behavioural and dynamical evidence, a study of simulated agents with the capacity to change feedback from their bodies to accomplish a one-legged walking task is proposed to understand the emergence of coupled dynamics for robust behaviour. Agents evolve with evolutionary-defined biases that modify incoming body signals (sensory offsets). Analyses on whether these agents show further dependence to their environmental coupled dynamics than others with no feedback control is described in this article. The ability to sustain behaviours is tested during lifetime experiments with mutational and sensory perturbations after evolution. Using dynamical systems analysis, this work identifies conditions for the emergence of dynamical mechanisms that remain functional despite sensory perturbations. Results indicate that evolved agents with evolvable sensory offset depends not only on where in neural space the state of the neural system operates, but also on the transients to which the inner-system was being driven by sensory signals from its interactions with the environment, controller, and agent body. Experimental evidence here leads discussions on a dynamical systems perspective on behavioural robustness that goes beyond attractors of controller phase space.     

Aging in language dynamics

Human languages evolve continuously, and a puzzling problem is how to reconcile the apparent robustness of most of the deep linguistic structures we use with the evidence that they undergo possibly slow, yet ceaseless, changes. Is the state in which we observe languages today closer to what would be a dynamical attractor with statistically stationary properties or rather closer to a non-steady state slowly evolving in time? Here we address this question in the framework of the emergence of shared linguistic categories in a population of individuals interacting through language games. The observed emerging asymptotic categorization, which has been previously tested - with success - against experimental data from human languages, corresponds to a metastable state where global shifts are always possible but progressively more unlikely and the response properties depend on the age of the system. This aging mechanism exhibits striking quantitative analogies to what is observed in the statistical mechanics of glassy systems. We argue that this can be a general scenario in language dynamics where shared linguistic conventions would not emerge as attractors, but rather as metastable states.     

Error identification/propagation/remediation in biomonitoring surveys—A knowledge-based approach towards standardization via fault tree analysis

Biomonitoring has become a key concept in environmental management since it is the most ecologically-relevant means for assessing pollution impact. Its broad applicability, however, raises the need for harmonization, optimization and standardization. The main difficulty met in the development of a generalized methodological framework for standardizing biomonitoring surveys is to reconcile a theoretical approach with an operational approach: in any set-up the survey strategy should ensure that the measured values represent the status of the environment. This leads, inevitably, to the application of a variety of methods, techniques and strategies in order to accommodate the special ecogeomorphological characteristics of each area and handle adequately the knowledge gaps related to local species stress response mechanisms and tolerances. Thereby, comparability of the results, even between subsequent surveys in the same area or concurrent surveys at neighbouring areas, is unfeasible, yet indispensable in defining spatiotemporal pollution patterns in large ecosystems. This inevitably requires some kind of normalization/harmonization that would strengthen any observed correlations between exposure and health effects, which ultimately may point at potential causal relationships. The aim of this work is to design/develop a knowledge management tool, built on a cybernetic infrastructure for (i) localizing the variation source(s) in each project that prohibit inter-survey normalisation/comparability, (ii) determining the path of error propagation as a causal chain when a fault is identified, (iii) testing the ultimate causes suggested as mostly responsible for this fault, and (iv) proceeding to remedial proposals (including a feedback possibility in case that the suggested remedy is proved to be inadequate) with a view to improving quality and reliability of biosurveillance. The presented tool relies on Fuzzy Fault Tree Analysis (FFTA) to identify, categorise, sort and analyse all possible sources of variation and error in biomonitoring; thereby, an expert system is developed, where the tree (dendritic) structure serves as the Knowledge Base (KB) and the fuzzy rules based decision mechanism is the inference engine. This scheme, relying on a collaborative model building methodology and a systemic modeling formalism by using 2nd order cybernetics in order to include human judgement and reasoning, enables knowledge to be used not only for representation but also for reasoning at functional level.