Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for (...) a physically different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

For decades Darwinian processes were framed in the form of the Lewontin conditions: reproduction, variation and differential reproductive success were taken to be sufficient and necessary. Since Buss and the work of Maynard Smith and Szathmary biologists were eager to explain the major transitions from individuals to groups forming new individuals subject to Darwinian mechanisms themselves. Explanations that seek to explain the emergence of a new level of selection, however, cannot employ properties that would already have to exist on that (...) level for selection to take place. Recently, Hammerschmidt et al. provided a ‘bottom-up’ experiment corroborating much of the theoretical work Paul Rainey has done since 2003 on how cheats can play an important role in the emergence of new Darwinian individuals on a multicellular level. The aims of this paper are twofold. First, I argue for a conceptual shift in perspective from seeing cheats as a ‘problem’ that needs to be solved for multi-cellularity to evolve to the very ‘key’ for the evolution of multicellularity. Secondly, I illustrate the consequences of this shift for both theoretical and experimental work, arguing for a more prominent role of ecology and the multi-level selection framework within the debate then they currently occupy. (shrink)

Evolutionary economics often focuses on the comparison between economic competition and the process of natural selection to select the fitter members of a given population. But that neglects the other "half" of an evolutionary process, the mechanism for the generation of new possibilities that is key to dynamic efficiency. My topic is the process of parallel experimentation which I take to be a process of multiple experiments running concurrently with some form of common goal, with some semi-isolation between the experiments, (...) with benchmarking comparisons made between the experiments, and with the "migration" of discoveries between experiments wherever possible to ratchet up the performance of the group. The thesis is that parallel experimentation is a fundamental dynamic efficiency scheme to enhance and accelerate variation, innovation, and learning in contexts of genuine uncertainty or known ignorance. Within evolutionary biology, this type of parallel experimentation scheme was developed in Sewall Wright's shifting balance theory of evolution. It addressed the rather neglected topic of how a population on a low fitness peak might eventually be able to go "downhill" against selective pressures, traverse a valley of low fitness, and then ascend a higher fitness peak. The theme of parallel experimentation is used to recast and pull together dynamic and pluralistic theories in economics, political theory, philosophy of science, and social learning. (shrink)

The intersection of development and evolution has always harbored conceptual issues, but many of these are on display in contemporary evolutionary developmental biology (evo-devo). These issues include: (1) the precise constitution of evo-devo, with its focus on both the evolution of development and the developmental basis of evolution, and how it fits within evolutionary theory; (2) the nature of evo-devo model systems that comprise the material of comparative and experimental research; (3) the puzzle of how to (...) understand the widely used notion of 'conserved mechanisms'; (4) the definition of evolutionary novelties and expectations for how to explain them; and (5) the demand of interdisciplinary collaboration that derives from investigating complex phenomena at key moments in the history of life, such as the fin-limb transition. This Element treats these conceptual issues with close attention to both empirical detail and scientific practice to offer new perspectives on evolution and development. This title is also available as Open Access on Cambridge Core. (shrink)

This paper introduces pragmatic hypotheses and relates this concept to the spiral of scientific evolution. Previous works determined a characterization of logically consistent statistical hypothesis tests and showed that the modal operators obtained from this test can be represented in the hexagon of oppositions. However, despite the importance of precise hypothesis in science, they cannot be accepted by logically consistent tests. Here, we show that this dilemma can be overcome by the use of pragmatic versions of precise hypotheses. These (...) pragmatic versions allow a level of imprecision in the hypothesis that is small relative to other experimental conditions. The introduction of pragmatic hypotheses allows the evolution of scientific theories based on statistical hypothesis testing to be interpreted using the narratological structure of hexagonal spirals, as defined by Pierre Gallais. (shrink)

In this paper we use an experimental approach to investigate how linguistic conventions can emerge in a society without explicit agreement. As a starting point we consider the signaling game introduced by Lewis. We find that in experimental settings, small groups can quickly develop conventions of signal meaning in these games. We also investigate versions of the game where the theoretical literature indicates that meaning will be less likely to arise—when there are more than two states for actors (...) to transfer meaning about and when some states are more likely than others. In these cases, we find that actors are less likely to arrive at strategies where signals have clear conventional meaning. We conclude with a proposal for extending the use of the methodology of experimental economics in experimental philosophy. (shrink)

The evolution of gravitational tests from an epistemological perspective framed in the concept of rational reconstruction of Imre Lakatos, based on his methodology of research programmes. Unlike other works on the same subject, the evaluated period is very extensive, starting with Newton's natural philosophy and up to the quantum gravity theories of today. In order to explain in a more rational way the complex evolution of the gravity concept of the last century, I propose a natural extension of (...) the methodology of the research programmes of Lakatos that I then use during the paper. I believe that this approach offers a new perspective on how evolved over time the concept of gravity and the methods of testing each theory of gravity, through observations and experiments. I argue, based on the methodology of the research programmes and the studies of scientists and philosophers, that the current theories of quantum gravity are degenerative, due to the lack of experimental evidence over a long period of time and of self-immunization against the possibility of falsification. Moreover, a methodological current is being developed that assigns a secondary, unimportant role to verification through observations and/or experiments. For this reason, it will not be possible to have a complete theory of quantum gravity in its current form, which to include to the limit the general relativity, since physical theories have always been adjusted, during their evolution, based on observational or experimental tests, and verified by the predictions made. Also, contrary to a widespread opinion and current active programs regarding the unification of all the fundamental forces of physics in a single final theory, based on string theory, I argue that this unification is generally unlikely, and it is not possible anyway for a unification to be developed based on current theories of quantum gravity, including string theory. In addition, I support the views of some scientists and philosophers that currently too much resources are being consumed on the idea of developing quantum gravity theories, and in particular string theory, to include general relativity and to unify gravity with other forces, as long as science does not impose such research programs. -/- DOI: 10.13140/RG.2.2.35350.70724 . (shrink)

Behavioural flexibility is often treated as the gold standard of evidence for more sophisticated or complex forms of animal cognition, such as planning, metacognition and mindreading. However, the evidential link between behavioural flexibility and complex cognition has not been explicitly or systematically defended. Such a defence is particularly pressing because observed flexible behaviours can frequently be explained by putatively simpler cognitive mechanisms. This leaves complex cognition hypotheses open to ‘deflationary’ challenges that are accorded greater evidential weight precisely because they offer (...) putatively simpler explanations of equal explanatory power. This paper challenges the blanket preference for simpler explanations, and shows that once this preference is dispensed with, and the full spectrum of evidence—including evolutionary, ecological and phylogenetic data—is accorded its proper weight, an argument in support of the prevailing assumption that behavioural flexibility can serve as evidence for complex cognitive mechanisms may begin to take shape. An adaptive model of cognitive-behavioural evolution is proposed, according to which the existence of convergent trait–environment clusters in phylogenetically disparate lineages may serve as evidence for the same trait–environment clusters in other lineages. This, in turn, could permit inferences of cognitive complexity in cases of experimental underdetermination, thereby placing the common view that behavioural flexibility can serve as evidence for complex cognition on firmer grounds. (shrink)

Horizontal gene transfer (HGT) has been a paramount mechanism of interest in recent literature addressing the origins of biological evolution. However, research on lightning-triggered electroporation represents the innovative and still insufficiently grasped approach to HGT (Kotnik, 2013). On the other hand, prebiotic synthesis is a fundamental process for chemical evolution. Recently, the effects of volcanic lightning on nitrogen fixation and phosphate reduction have also been considered (NavarroGonzález and Segura, 2004). This paper aims to present a top-down approach to (...) the question of the origin of life on early Earth. By considering the conditions necessary for the emergence of biological and chemical evolution, emphasizing electrostatic discharges, we will attempt to link previous theoretical and experimental research. Furthermore, we will present a recent endeavor at applying the Drake equation to calculating the probability of volcanic lightning impact on the prebiotic synthesis and derive a similar use in estimating the contribution of lightning to HGT (Weaver, 2013). We will also display that choosing a type of probability appropriate for the context of life sciences is not necessarily a quantitative issue. Finally, we will show that significant conceptual constraints, like determining the relevant factors and sources of uncertainty when considering the origin of life on early Earth, are fundamentally philosophical issues. We hope that the results of our research – deriving Drake’s equation in the domain of chemical evolution and considering Bayesian and counterfactual types as potentially more suitable candidates for calculating probabilities in the evolutionary framework – will contribute to developing new discussions in life sciences. (shrink)

In psychiatry, pharmacological drugs play an important experimental role in attempts to identify the neurobiological causes of mental disorders. Besides being developed in applied contexts as potential treatments for patients with mental disorders, pharmacological drugs play a crucial role in research contexts as experimental instruments that facilitate the formulation and revision of neurobiological theories of psychopathology. This paper examines the various epistemic functions that pharmacological drugs serve in the discovery, refinement, testing, and elaboration of neurobiological theories of mental (...) disorders. I articulate this thesis with reference to the history of antipsychotic drugs and the evolution of the dopamine hypothesis of schizophrenia in the second half of the twentieth century. I argue that interventions with psychiatric patients through the medium of antipsychotic drugs provide researchers with information and evidence about the neurobiological causes of schizophrenia. This analysis highlights the importance of pharmacological drugs as research tools in the generation of psychiatric knowledge and the dynamic relationship between practical and theoretical contexts in psychiatry. (shrink)

The attempt to narrow the general discourse of the problem of error and to focus it on the specific problem of experimental error may be approached from different directions. One possibility is to establish a focusing process from the standpoint of history; such an approach requires a careful scrutiny of the history of science with a view to identifying the juncture when the problem of experimental error was properly understood and accounted for. In a study of this kind (...) one would have to examine the evolution of the method of experimentation and related topics so that clear criteria would underlie the analysis. (shrink)

The scientific status of evolutionary theory seems to be more or less perennially under question. I am not referring here (just) to the silliness of young Earth creation- ism (Pigliucci 2002; Boudry and Braeckman 2010), or even of the barely more intel- lectually sophisticated so-called Intelligent Design theory (Recker 2010; Brigandt this volume), but rather to discussions among scientists and philosophers of science concerning the epistemic status of evolutionary theory (Sober 2010). As we shall see in what follows, this debate (...) has a long history, dating all the way back to Darwin, and it is in great part rooted in the fundamental dichotomy between what French biologist and Nobel laureate Jacques Monod (1971) called chance and necessity—i.e., the inevitable and inextricable interplay of deterministic and stochastic mechanisms operating during the course of evolution. (shrink)

In addition to considerable debate in the recent evolutionary literature about the limits of the Modern Synthesis of the 1930s and 1940s, there has also been theoretical and empirical interest in a variety of new and not so new concepts such as phenotypic plasticity, genetic assimilation and phenotypic accommodation. Here we consider examples of the arguments and counter- arguments that have shaped this discussion. We suggest that much of the controversy hinges on several misunderstandings, including unwarranted fears of a general (...) attempt at overthrowing the Modern Synthesis paradigm, and some fundamental conceptual confusion about the proper roles of phenotypic plasticity and natural selection within evolutionary theory. (shrink)

The enigma of the Emergence of Natural Languages, coupled or not with the closely related problem of their Evolution is perceived today as one of the most important scientific problems. The purpose of the present study is actually to outline such a solution to our problem which is epistemologically consonant with the Big Bang solution of the problem of the Emergence of the Universe}. Such an outline, however, becomes articulable, understandable, and workable only in a drastically extended epistemic and (...) scientific oecumene, where known and habitual approaches to the problem, both theoretical and experimental, become distant, isolated, even if to some degree still hospitable conceptual and methodological islands. The guiding light of our inquiry will be Eugene Paul Wigner's metaphor of ``the unreasonable effectiveness of mathematics in natural sciences'', i.e., the steadily evolving before our eyes, since at least XVIIth century, ``the miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics''. Kurt Goedel's incompleteness and undecidability theory will be our guardian discerner against logical fallacies of otherwise apparently plausible explanations. John Bell's ``unspeakableness'' and the commonplace counterintuitive character of quantum phenomena will be our encouragers. And the radical novelty of the introduced here and adapted to our purposes Big Bang epistemological paradigm will be an appropriate, even if probably shocking response to our equally shocking discovery in the oldest among well preserved linguistic fossils of perfect mathematical structures outdoing the best artifactual Assemblers. (shrink)

Cognitive archaeology is a relatively new interdisciplinary science that uses cognitive and psychological models to explain archaeological artifacts like stone tools, figurines, and art. Edited by cognitive archaeologist Karenleigh A. Overmann and psychologist Frederick L. Coolidge, Squeezing Minds From Stones is a collection of essays, from both early pioneers and 'up and coming' newcomers in the field, that addresses a wide variety of cognitive archaeology topics, including the value of experimental archaeology, primate archaeology, the intent of ancient tool makers, (...) and how they may have lived and thought. (shrink)

Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these days, (...) and to date they have all been equally plausible and equally successful. And, just to be explicit, I do not mean “IQ” by “intelligence.” I am using “intelligence” in the way AI uses it: as a semi-techical term referring to a general property of all intelligent systems, animal (including humans), or machine, alike.). (shrink)

Darwin provided us with a powerful theoretical framework to explain the evolution of living systems. Natural selection alone, however, has sometimes been seen as insufficient to explain the emergence of new levels of selection. The problem is one of “circularity” for evolutionary explanations: how to explain the origins of Darwinian properties without already invoking their presence at the level they emerge. That is, how does evolution by natural selection commence in the first place? Recent results in experimental (...) evolution suggest a way forward: Paul Rainey and his collaborators have shown that Darwinian properties could be exogenously imposed via what they call “ecological scaffolding.” This could solve the “black box” dilemma faced by Darwinian explanations of new levels of organization. Yet, despite “scaffolding” recently becoming a popular term in the study of cognition, culture, and evolution, the concept has suffered from vagueness and ambiguity. This article aims to show that scaffolding can be turned into a proper scientific concept able to do explanatory work within the context of the major evolutionary transitions. Doing so will allow us to once again extend the scope of the Darwinian model of evolution by natural selection. (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)

The year 2009 has been a year of numerous commemorations of both scientific and non-scientific achievements that contributed to the advancement of human kind. Protestants celebrated the 500th anniversary of the birth of Calvin; literary critics celebrated the 200th anniversary of the poet Edgar Allan Poe; and the musical genius Felix Mendelssohn-Bartholdy was also born 200 years ago. 2009 further marked the bicentennial of the birth of Louis Braille, the inventor of Braille; and Abraham Lincoln, the 16th president of the (...) United States, who founded the National Academy of Sciences. Pierre Curie, famous for his work on radioactivity that he conducted together with his wife Marie Curie, was born 150 ago; as was John Dewey, a philosopher and psychologist who is recognized as one of the founding fathers of both pragmatism as well as functional psychology. UNESCO and the International Astronomical Union dubbed 2009 the International Year of Astronomy. By doing so, astronomers celebrated the 400th anniversary of Galileo Galilei’s telescopic observations as well as the publication of Johannes Kepler’s Astronomia nova wherein he formulated the first two laws of planetary motion. 2009 also marked the last of a 3-year-long celebration of Planet Earth, another UNESCO-governed initiative. However, for evolutionary biologists and philosophers of science, 2009 will be largely remembered for its worldwide commemorations of the 200th anniversary of the birth of Charles Darwin, and the 150th anniversary of the publication of his magnum opus On the origin of species by means of natural selection. Footnote1 In order to pay tribute to Darwin’s major contribution to the advancement of evolutionary science, the International Union of Biological Sciences and the International Union of History and Philosophy of Science have called the year 2009 the Darwin Year. Given that so many scientific discoveries were commemorated, COPUS, the Coalition on the Public Understanding on Science, called out 2009 as the Year of Science, in the hope to pay equal tribute to both the field of biology as well as astronomy. 2009 was indeed a year of biology. Somewhat overshadowed by the big Darwin celebrations, smaller-scaled events were held to commemorate the 200th anniversary of the publication of Lamarck’s Philosophie Zoologique; and the 150th anniversary of the death of Alexander von Humboldt, the father of biogeography. In 1910, Constantin Mereschkowsky wrote his article on symbiogenesis entitled ‘The Theory of Two Plasmas as the Basis of Symbiogenesis, a New Study for the Origins of Organisms’. The article was published in the German Biologisches Zentralblatt, the journal that would later evolve into the current Theory in Biosciences. Somewhat forgotten, but equally important for the field of symbiogenesis, was the 200th anniversary of the birth of Pierre-Joseph Van Beneden, a Belgian paleontologist and zoologist famous for distinguishing parasitism from commensalism. Finally, Henry Bergson, known for inventing the currently rejected notion of élan vital, was born 150 years ago. In order to memorialize the important role these biologists played in the advancement of our understanding of the evolutionary process, a 2-day international conference was organized entitled: Evolution today and tomorrow, Darwin evaluated by contemporary evolutionary and philosophical theories. The conference was organized by The Centre for Philosophy of Science of the University of Lisbon (Portugal), in collaboration with the Centre for Environmental Biology of the same university, and the Lisbon Centre for Applied Psychology. The articles presented here are a spin-off of this conference. The current volumes contain the peer-reviewed articles of a selection of the plenary and invited speakers, as well as those of scholars who were additionally invited to contribute to the volumes. (shrink)

Social network structure has been argued to shape the structure of languages, as well as affect the spread of innovations and the formation of conventions in the community. Specifically, theoretical and computational models of language change predict that sparsely connected communities develop more systematic languages, while tightly knit communities can maintain high levels of linguistic complexity and variability. However, the role of social network structure in the cultural evolution of languages has never been tested experimentally. Here, we present results (...) from a behavioral group communication study, in which we examined the formation of new languages created in the lab by micro‐societies that varied in their network structure. We contrasted three types of social networks: fully connected, small‐world, and scale‐free. We examined the artificial languages created by these different networks with respect to their linguistic structure, communicative success, stability, and convergence. Results did not reveal any effect of network structure for any measure, with all languages becoming similarly more systematic, more accurate, more stable, and more shared over time. At the same time, small‐world networks showed the greatest variation in their convergence, stabilization, and emerging structure patterns, indicating that network structure can influence the community's susceptibility to random linguistic changes (i.e., drift). (shrink)

The pace of technological change continues to outstrip the evolution of democratic institutions, creating an urgent need for innovative approaches to democratic reform. However, the experimentation bottleneck - characterized by slow speed, high costs, limited scalability, and ethical risks - has long hindered progress in democracy research. This paper proposes a novel solution: employing generative artificial intelligence (GenAI) to create synthetic data through the simulation of digital homunculi, GenAI-powered entities designed to mimic human behavior in social contexts. By enabling (...) rapid, low-risk experimentation with alternative institutional designs, this approach could significantly accelerate democratic innovation. I examine the potential of GenAI-assisted research to mitigate current limitations in democratic experimentation, including the ability to simulate large-scale societal interactions and test complex institutional mechanisms. While acknowledging potential risks such as algorithmic bias, reproducibility challenges, and AI alignment issues, I argue that the benefits of synthetic data are likely to outweigh their drawbacks if implemented with proper caution. To address existing challenges, I propose a range of technical, methodological, and institutional adaptations. The paper concludes with a call for interdisciplinary collaboration in the development and implementation of GenAI-assisted methods in democracy research, highlighting their potential to bridge the gap between democratic theory and practice in an era of rapid technological change. (shrink)

The so-called “Baldwin Effect” has been studied for years in the fields of Artificial Life, Cognitive Science, and Evolutionary Theory across disciplines. This idea is often conflated with genetic assimilation, and has raised controversy in trans-disciplinary scientific discourse due to the many interpretations it has. This paper revisits the “Baldwin Effect” in Baldwin’s original spirit from a joint historical, theoretical and experimental approach. Social Heredity – the inheritance of cultural knowledge via non-genetic means in Baldwin’s term – is also (...) taken into consideration. I shall argue that the Baldwin Effect can occur via social heredity without necessity for genetic assimilation. Computational experiments are carried out to show that when social heredity is permitted with high fidelity, there is no need for the assimilation of acquired characteristics; instead the Baldwin Effect occurs as promoting more plasticity to facilitate future intelligence. The role of mind and intelligence in evolution and its implications in an extended synthesis of evolution are briefly discussed. (shrink)

Interest in imagination dates back to Plato and Aristotle, but full-length works have been devoted to it only relatively recently by Sartre, McKellar, Furlong, Casey, Johnson, Warnock, Brann, and others. Despite their length and variety, however, these current theories take overly narrow views of this complex phenomenon. Their definitions of “imagination” neglect the multiplicity of its meanings and tend to focus narrowly on the power of imaging alone. But imagination in the fullest, most encompassing sense centers instead on creativity, which (...) involves both imaging and reasoning powers. Current accounts of the operations of imagination narrowly construe it in fixed, immutable terms. But it’s instead a dynamic, evolving synergy of its psychological roots and sociobiological roots. This synergy has transformed the roles of images and symbols in imagination. For example, in the shift from mytheopic to scientific imagination, literacy and formal education fostered abstract symbolic thinking, which differs from mytheopic thinking based on richly concrete associations. The result was “more than cool reason”, but experimental studies show that it’s also more than just dreamy imagery. It’s a dynamic synergy of the two that has transformed both. Current evaluations of imagination’s potentials are also narrow. They tend to focus on its role in mental life while ignoring social and political life. Also, they tend to follow romantic and existentialist customs of extolling imagination’s virtues without soberly critiquing its limitations. Again, they ignore the synergy of psychological, sociological and biological forces that shape mental and social evolution, and promote and constrain imagination in complex ways. For example, Sartre surreally asks us to choose our own nature with an imagination emancipated from institutional and instinctual strictures. Yet making intelligible choices depends on these strictures. In conclusion, current theories define imagination narrowly in terms of imaging, they describe its operations in fixed and immutable terms, and they evaluate its potentials without examining the full interplay of forces shaping it. These shortcomings are remedied by a broader perspective that defines imagination more adequately and comprehensively, and that recognizes it’s complex roots, dynamic operations, and evolving potentials. This paper is based on my 1994 work, The Roots of Imagination, which can be downloaded in full here in PhilPapers. (shrink)

In his new book, Knowledge: The Philosophical Quest in History, Steve Fuller returns to core themes of his program of social epistemology that he first outlined in his 1988 book, Social Epistemology. He develops a new, unorthodox theology and philosophy building upon his testimony in Kitzmiller v. Dover Area School District in defense of intelligent design, leading to a call for maximal human experimentation. Beginning from the theological premise rooted in the Abrahamic religious tradition that we are created in the (...) image of God, Fuller argues that the spark of the divine within us distinguishes us from animals. I argue that Fuller’s recent work takes us away from key insights of his original work. In contrast, I advocate for a program of social epistemology rooted in evolutionary science rather than intelligent design, emphasize a precautionary and ecological approach rather than a proactionary approach that favors risky human experimentation, and attend to our material and sociological embeddedness rather than a transhumanist repudiation of the body. (shrink)

Human rationality develops formal logic and creates mathematics to summarize data into laws of nature that lead to theoretical models covering a wide range of phenomena. However, scientists deal with secondary causes. First causes involve metaphysical (ontological) questions, which regulate science. Without the ontological, neither the generalizations nor the historical propositions of the experimental sciences would be possible.

Mismatch is a prominent concept in evolutionary medicine, and a number of philosophers have published analyses of this concept. The word ‘mismatch’ has been used in a diversity of ways across a range of sciences, leading these authors to regard it as a vague concept in need of philosophical clarification. Here, in contrast, we concentrate on the use of mismatch in modelling and experimentation in evolutionary medicine. This reveals a rigorous theory of mismatch within which the term ‘mismatch’ is indeed (...) used in several ways, not because it is ill defined but because different forms of mismatch are distinguished within the theory. Contemporary evolutionary medicine has unified the idea of ‘evolutionary mismatch’, derived from the older idea of ‘adaptive lag’ in evolution, with ideas about mismatch in development and physiology derived from the developmental origins of health and disease (DOHaD) paradigm. A number of publications in evolutionary medicine have tried to make this theoretical framework explicit. We build on these to present the theory in as simple and general a form as possible. We introduce terminology, largely drawn from the existing literature, to distinguish the different forms of mismatch. This integrative theory of mismatch captures how organisms track environments across space and time on multiple scales in order to maintain an adaptive match to the environment, and how failures of adaptive tracking lead to disease. Mismatch is a productive organizing concept within this theory that helps researchers articulate how physiology, development, and evolution interact with one another and with environmental change to explain health outcomes. (shrink)

The evolutionary emergence of biological processes in organisms with inner, qualitative aspects has not been explained in any sufficient way by neurobiology, nor by the traditional neo-Darwinian paradigm — natural selection would appear to work just as well on insentient zombies (with the right behavioral input-output relations) as on real sentient animals. In consciousness studies one talks about the ‘hard problem’ of qualia. In this paper I sketch a set of principles about sign action, causality and emergent evolution. On (...) the basis of these principles, I characterize a concept of cause that would allow for a naturalistic explanation of the origin of consciousness. The suggested account of causation also turns the ‘hard problem’ of qualia into the easier problem of relating experimental biology to experiential biology. (shrink)

Bacteria do many things as organized populations. We have recently learned much about the molecular basis of intercellular communication among prokaryotes. Colonies display bacterial capacities for multicellular coordination which can be useful in nature where bacteria predominantly grow as films, chains, mats and colonies. E. coli colonies are organized into differentiated non-clonal populations and undergo complex morphogenesis. Multicellularity regulates many aspects of bacterial physiology, including DNA rearrangement systems. In some bacterial species, colony development involves swarming (active migration of cell groups). (...) Swarm colony development displays precise geometrical controls and periodic phenomena. Motile E. coli cells in semi-solid media form organized patterns due to chemotactic autoaggregation. On poor media, B. subtilis forms branched colonies using group motility and long-range chemical signalling. The significances of bacterial colony patterns thus reside in a deeper understanding of prokaryotic biology and evolution and in experimental systems for studying self-organization and morphogenesis. (shrink)

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search (...) for a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from (...) data sets them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

A general definition of consciousness is: ‘consciousness is a mental aspect of a system or a process, which is a conscious experience, a conscious function, or both depending on the context’, where the term context refers to metaphysical views, constraints, specific aims, and so on. One of the aspects of visual consciousness is the visual subjective experience (SE) or the first person experience that occurs/emerges in the visual neural-network of thalamocortical system (which includes dorsal and ventral visual pathways and frontal (...) cortex) during dynamic interactions among widely distributed neuronal groups. In this article, however, consciousness and SE are interchangeably used unless noted. Consciousness can be either access (reportable) or phenomenal consciousness. For access consciousness, the interactions are between feed forward stimulus dependent signals and fronto-parietal feedback attentional signals. The necessary ingredients for access (reportable) consciousness are (i) wakefulness, (ii) reentrant interactions among neural populations, (iii) fronto-parietal and thalamic-reticular-nucleus attentional signals that modulate consciousness, (iv) working memory that retains information for consciousness, (v) stimulus at or above threshold level, and (vi) neural-network proto-experiences (PEs) that are superposed SEs embedded in a neural-network. Attention and the ability to report are not necessary for phenomenal consciousness. The neural source for the arousal system is the ascending reticular activating system in the brain stem, which brings the thalamocortical neural networks to wakeful state as a baseline for consciousness to occur. Reentrant interactions among neural populations bind stimulus attributes (such as location and features) and entail consciousness. Attention could be the results of reentry and competitive interactions, and modulates the stimulus related feed forward signal and consciousness. The ‘sources’ of attention may be thalamic reticular nucleus for bottom-up or frontal cortex for top-down direction. The ‘target’ of visual attention is ‘V4/V8/VO’ for Red-Green (R-G) channel. The neural correlates of the psychophysical entity R-G channel appear to be ‘V4/V8/VO’-neural-network (retina → LGN ↔ V1 ↔ V2 ↔ ‘V4/V8/VO’, and areas for attention, memory, and wakefulness). The psychophysical Red-Green Channel, its neurophysiological correlates V4/V8/VO-neural-network, and related experience (such as redness) are integrated. The dual-aspect-dual-mode PE-SE framework (Vimal, J Integr Neurosci 7:49–73, 2008) was used to address the explanatory gap problem of materialism. Neural-network and related SEs are the results of the co-evolution and co-development of the material aspect (mass, charge, spin, force, quanta, and space-time) and the mental aspect of fundamental particles (strings or elementary particles (fermions and bosons)). Their mental aspects are considered as the carriers of superposed multiple possible experiences (SEs/PEs) in unexpressed form. These possibilities are actualized when neural-networks are formed via neural Darwinism, and a specific SE is selected by a matching process when the necessary ingredients of consciousness/SE are satisfied. A simple experimental design is suggested to address the necessary and sufficient attributes of consciousness. (shrink)

The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically motivated. Moreover, the self-taught neural network (...) is the product of the interplay between evolution and learning. We simulate a multi-agent system in which neural networks are used to control autonomous agents. These agents have to forage for resources and compete for their own survival. Experimental results show that the interaction between evolution and the ability to teach oneself in self-taught neural networks outperform evolution and self-teaching alone. More specifically, the emergence of an intelligent foraging strategy is also demonstrated through that interaction. Indications for future work on evolving neural networks are also presented. (shrink)

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal mechanisms that enable cognitive agents (...) to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. -/- The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. -/- Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment. (shrink)

We review some results in the theory of non-relativistic quantum unstable systems. We account for the most important definitions of quantum resonances that we identify with unstable quantum systems. Then, we recall the properties and construction of Gamow states as vectors in some extensions of Hilbert spaces, called Rigged Hilbert Spaces. Gamow states account for the purely exponential decaying part of a resonance; the experimental exponential decay for long periods of time physically characterizes a resonance. We briefly discuss one (...) of the most usual models for resonances: the Friedrichs model. Using an algebraic formalism for states and observables, we show that Gamow states cannot be pure states or mixtures from a standard view point. We discuss some additional properties of Gamow states, such as the possibility of obtaining mean values of certain observables on Gamow states. A modification of the time evolution law for the linear space spanned by Gamow shows that some non-commuting observables on this space become commuting for large values of time. We apply Gamow states for a possible explanation of the Loschmidt echo. (shrink)

Advances in Artificial Intelligence (AI) have driven the evolution of reasoning in modern AI models, particularly with the development of Large Language Models (LLMs) and their "Think and Answer" paradigm. This paper explores the influence of human reinforcement on AI reasoning and its potential to enhance decision-making through dynamic human interaction. It analyzes the roots of bias and fairness in AI, arguing that these issues often stem from human data and reflect inherent human biases. The paper is structured as (...) follows: first, it frames reasoning as a mechanism for ethical reflection, grounded in dynamic learning and feedback loops; second, it discusses how scaling laws suggest that reinforcement learning (RL) can mitigate biases and promote fairness; third, it examines how RL allows models to view algorithmic bias and fairness as approximation problems. Through an experimental study, the paper demonstrates how AI models, empowered by RL, have successfully identified biases across various domains, including gender and socio-economic contexts, highlighting how reasoning improves algorithmic fairness. Ultimately, this work emphasizes the role of RL in mitigating algorithmic bias and enhancing fairness in AI systems. (shrink)

The scientific study of consciousness, also referred to as consciousness science, is a young scientific field devoted to understanding how conscious experiences and the brain relate. It comprises a host of theories, experiments, and analyses that aim to investigate the problem of consciousness empirically, theoretically, and conceptually. This thesis addresses some of the questions that arise in these investigations from a formal and mathematical perspective. These questions concern theories of consciousness, experimental paradigms, methodology, and artificial consciousness. -/- Regarding theories (...) of consciousness, the thesis contributes to the understanding of the mathematical structure that some of the formal theories in the field propose. The work presented here targets the theory of consciousness known as Integrated Information Theory (IIT) and the neuroscientific theory known as Predictive Processing Theory or Free Energy Principle in its Active Inference form (AI-PP). The thesis provides axiomatic definitions of the mathematical structures that constitute these theories, and uses these definitions to address some of the open questions surrounding the theories. For AI-PP, this includes a rigorous derivation of the formula for Active Inference via Free Energy minimisation and a proof of compositionality of Free Energy. For IIT, this includes resolutions of some of the criticisms of IIT's formal scope and applications, but also the identification of new issues that concern the formalism and its derivation. When possible, the definitions are provided in the mathematical framework of category theory. -/- Regarding experiments, the thesis addresses the main paradigm for testing and falsifying theories of consciousness currently applied in the field. This paradigm consists of comparing the conscious experience that a theory predicts with the conscious experience that is inferred from behavioural data or report by use of measures of consciousness. The thesis provides a formal model of this paradigm and shows that under a certain condition—if inference and prediction are independent—, any minimally informative theory of consciousness can always be falsified. This is deeply problematic since the field’s reliance on report or behaviour to infer conscious experiences, in conjunction with the general structure of most contemporary theories of consciousness, implies such independence. This observation provides the exact formal underpinning of the well-known unfolding argument. The thesis analyses the origin of the problem and identifies precisely which changes are required to avoid this problem in future research. The thesis furthermore shows that the problem of falsifying theories of consciousness, and of empirical comparisons of theories of consciousness more generally, follows from a pervasive closure paradigm in consciousness science, that consists of taking a neuroscientific account of the brain as input to a theory of consciousness, so as to explain what consciousness is, without allowing for modifications or adaptations of the neuroscientific account that would accommodate consciousness as part of the brain's functioning. As is shown in the thesis, this paradigm has implications that point to a fundamental need of revision. -/- Regarding methodological and conceptual questions, the thesis contributes to the foundations of structural research in consciousness science. Structural research aims to use mathematical structures or mathematical spaces, instead of verbal descriptions or simple categorisations, to represent conscious experiences scientifically, for example when building theories of consciousness, or when exploring new empirical avenues to measure consciousness. Despite considerable advances in this realm, there was, prior to this thesis, no explicit definition of what a mathematical structure of conscious experience should be; that is, how the attribution of mathematical structure to conscious experiences should be systematically understood. Perhaps the most important contribution of this thesis to the field is to propose such a definition. The definition, a structural concept, extends existing approaches wherever available, and provides a basis for developing a common formal language to study consciousness, bridging developments as far apart as psychophysics and phenomenology. In addition, and independently of this proposal, the thesis offers a critical analysis of which metaphysical premises need to be presumed in structural research, whether the use of particular formal tools (such as structure-preserving mappings or homomorphisms) is justified, and how structural theories of consciousness could otherwise be built in the first place. An attempt to expand the results from consciousness to more general problems in philosophy of science is made in the context of the well-known Newman problem. -/- Regarding the question of artificial consciousness—can AI feel?—, the thesis contributes two results that take the form of no-go theorems, as known from physics. The first no-go theorem shows that if consciousness is relevant for the temporal evolution of a system's states—if it is dynamically relevant—, then contemporary AI systems cannot be conscious. That is because AI systems run on CPUs, GPUs, TPUs or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. The second no-go theorem is situated in the context of computational functionalism, a view which posits that consciousness is a computation. The theorem shows that if computational functionalism holds true, consciousness cannot be a Turing computation. Rather, it must be a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation. -/- This thesis is part of a global effort to pioneer a mathematical perspective in consciousness science, now called Mathematical Consciousness Science. The hope behind the research carried out in this PhD is to illustrate the power and usefulness of mathematical approaches in different areas of consciousness science, and in doing so, to lay the foundations for future mathematical work that complements and supports empirical and theoretical work in the further development of this exciting field. (shrink)

Understanding community-level selection using Lewontin’s criteria requires both community-level inheritance and community-level heritability, and in the discipline of community and ecosystem genetics, these are often conflated. While there are existing studies that show the possibility of both, these studies impose community-level inheritance as a product of the experimental design. For this reason, these experiments provide only weak support for the existence of community-level selection in nature. By contrast, treating communities as interactors (in line with Hull’s replicator-interactor framework or Dawkins’s (...) idea of the “extended phenotype”) provides a more plausible and empirically supportable model for the role of ecological communities in the evolutionary process. (shrink)

This volume takes cue from the idea that the thought of no philosopher can be understood without considering it as the result of a constant, lively dialogue with other thinkers, both in its internal evolution as well as in its reception, re-use, and assumption as a starting point in addressing past and present philosophical problems. In doing so, it focuses on a feature that is crucially emerging in the historiography of early modern philosophy and science, namely the complexity in (...) the production of knowledge. The book explores the applicability of this approach to a long-considered armchair philosopher, namely René Descartes, who is now more and more understood as a full-blown scientist, networker, and intellectual éminence grise rather than as the mere philosopher of the cogito, as well as the originator of different ‘Cartesianisms’ which encompassed many ideas and approaches for long captured by dichotomic historiographical categories as rationalism and empiricism, or speculative and experimental philosophy. The essays gathered in the volume aim to address the ways in which Descartes’s philosophy evolved and was progressively understood by scientists, philosophers, and intellectuals from different contexts and eras, either by considering direct interlocutors of Descartes such as Isaac Beeckman and Elisabeth of Bohemia, early modern thinkers who developed upon his ideas and on particular topics as Nicolas Malebranche or Thomas Willis, those who adapted his overall methodology in developing new systems of knowledge as Johannes Clauberg and Pierre-Sylvain Régis, and contemporary thinkers from continental and analytic traditions like Emanuele Severino and Peter Strawson. (shrink)

In Big Gods, Norenzayan (2013) presents the most comprehensive treatment yet of the Big Gods question. The book is a commendable attempt to synthesize the rapidly growing body of survey and experimental research on prosocial effects of religious primes together with cross-cultural data on the distribution of Big Gods. There are, however, a number of problems with the current cross-cultural evidence that weaken support for a causal link between big societies and certain types of Big Gods. Here we attempt (...) to clarify these problems and, in so doing, correct any potential misinterpretation of the cross-cultural findings, provide new insight into the processes generating the patterns observed, and flag directions for future research. (shrink)

Abstract -/- This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. -/- Key Contributions -/- • Resolution of General Relativity & Quantum Mechanics Paradox -/- CODES introduces structured intelligence fields that reconcile relativistic and quantum-scale physics by (...) incorporating oscillatory chiral dynamics. -/- • Reformulation of Dark Energy & Dark Matter -/- Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. -/- • Predictive Framework for Large-Scale Structures -/- The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. -/- • Resonance-Driven Model of Cosmic Evolution -/- By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. -/- By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. -/- Version Note -/- V6 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. -/- Discussion & Next Steps -/- This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)

This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. Key Contributions • Resolution of General Relativity & Quantum Mechanics Paradox CODES introduces structured intelligence fields that reconcile relativistic and quantum-scale physics by incorporating oscillatory chiral dynamics. • (...) Reformulation of Dark Energy & Dark Matter Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. • Predictive Framework for Large-Scale Structures The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. • Resonance-Driven Model of Cosmic Evolution By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. Version Note V6 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. Discussion & Next Steps This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)

Although epistasis is at the center of the Fisher-Wright debate, biologists not involved in the controversy are often unaware that there are actually two different formal definitions of epistasis. We compare concepts of genetic independence in the two theoretical traditions of evolutionary genetics, population genetics and quantitative genetics, and show how independence of gene action (represented by the multiplicative model of population genetics) can be different from the absence of gene interaction (represented by the linear additive model of quantitative genetics). (...) The two formulations converge with weak selection but not with strong selection or, for multiple loci, when the aggregated interaction terms are not negligible. As a result of the different formulations of gene interaction, the presence or absence of linkage disequilibrium,/D/, does not necessarily indicate the presence or absence of fitness epistasis. Indeed, linkage disequilibrium is generated in ‘additive’ models in quantitative genetics whenever two (or more) loci experience simultaneous selection. As a research strategy, it is often practical, for theoretical or experimental reasons, to minimize gene interaction by assuming independence of gene action in regard to fitness, or by assuming linear additive effects of multiple loci on a phenotype. However, minimizing the role of epistasis in theoretical investigations hinders our understanding of the origins of diversity and the evolution of complex phenotypes. (shrink)

This article had its start with another article, concerned with measuring the speed of gravitational waves - "The Measurement of the Light Deflection from Jupiter: Experimental Results" by Ed Fomalont and Sergei Kopeikin (2003) - The Astrophysical Journal 598 (1): 704–711. This starting-point led to many other topics that required explanation or naturally seemed to follow on – Unification of gravity with electromagnetism and the 2 nuclear forces, Speed of electromagnetic waves, Energy of cosmic rays and UHECRs, Digital string (...) theory, Dark energy+gravity+binary digits, Cosmic strings and wormholes from Figure-8 Klein bottles, Massless and massive photons and gravitons, Inverse square+quantum entanglement = God+evolution, Binary digits projected to make Prof. Greene’s cosmic holographic movie, Renormalization of infinity, Colliding subuniverses, Unifying cosmic inflation, TOE (emphasizing “EVERYthing”) = Bose-Einstein renormalized. The text also addresses (in a nonmathematical way) the wavelength of electromagnetic waves, the frequency of gravitational waves, gravitational and electromagnetic waves having identical speed, the gamma-ray burst designated GRB 090510, the smoothness of space, and includes these words – “Gravity produces electromagnetism. Retrocausally (by means of humans travelling into the past of this subuniverse with their electronics); this “Cosmic EM Background” produces base-2 mathematics, which produces gravity. EM interacts with gravity to produce particles, mass – gravity/EM could be termed “the Higgs field” - and the nuclear forces associated with those particles. It makes gravity using BITS that copy the principle of magnetism attracting and repelling, before pasting it into what we call the strong force and dark energy.” . (shrink)

The following Introduction briefly traces, albeit in jarring cuts, the evolution of caste question and its relationship with Indian cinema. It also tries to point out some aspects of Indian film theory, its lacunae and hopes that some of the questions raised here may give rise to future works by other (better) theorists. Pre-Independence cinema in India rarely addressed caste question, and if it did, then it was through an abstract global humanist lens. This tendency to address caste through (...) a hollow and empty shell of a theoretical model unfortunately has stuck around even in these times, and only found newer ways to reinvent itself in Neoliberal times. To understand the reason of Indian cinema’s lack of addressing caste more directly and pointedly, it has to be seen as part of a historical process. Only then can we see the history of ideology that is “outside of itself”, that is, in the material conditions that made possible Indian caste-society as well as its cine-culture. It also tries to raise questions about the film form, and its many possibilities of experimentation with the caste question (i.e. both in ideological and experiential possibilities). Lastly, it introduces some of the key works in this issue. Of course, with the hope that the readers will forgive and give respite to the many lacuna of the issue, as well as the Editor himself. (shrink)

What are and where are the ethical limits of neuroeducation? The article reflects on a necessary question for the evolution of cognitive processes through critical deliberation, the delimitation of boundaries and the estimation of progress. On the one hand, it argues that the experimental turn could call into question the ethical and humanistic goal of education; on the other hand, it argues that a systematic renunciation of neuroscientific advances would also mean abandoning the quest for human flourishing. The (...) humanities alone do not provide the biopsychosocial approach from which we must understand our self-realisation. Thus, the first of the limits that is the origin of all the others arises from a scientific-humanist dilemma. The new boundaries to be delimited are the neuroscientific implications in themselves and how these are translated into educational, if they were to be valid in this field. Here neuromyths play an important role. It is precisely neuroethics as an applied ethics or branch of bioethics that takes up these aspects through neuroeducational ethics and educational neuroethics. In its fundamental branch, this discipline opens up the debate on moral neuroeducation. But the possibility of reducing morality and all that we are to our neural bases leads to new limits. To overcome them, he highlights the potential of a sociocultural and biological symbiosis with the notions of 'neuroculture' and 'proactive epigenesis'. Finally, the essay deliberates on the more speculative boundaries between what we are and our possibilities for understanding it on the basis of transhumanism. ____________________________________________________________________________________________________ ______________________________________________________________________________________________¿Cuále s son y dónde están los límites éticos de la neuroeducación? El artículo reflexiona sobre una cuestión necesaria para el devenir de los procesos cognitivos mediante la deliberación crítica, la delimitación de fronteras y la estimación del progreso. Su hilo argumental proyecta, por un lado, que el giro experimental podría poner en entredicho el objetivo ético y humanista de la educación; por otro lado, que una renuncia sistemática a los avances de las neurociencias supondría, igualmente, abandonar la búsqueda del florecimiento humano. Las humanidades solo no brindan el enfoque biopsicosocial desde el que hemos de entender nuestra autorrealización. Por ende, el primero de los límites que es origen de todos los demás surge dada una disyuntiva científico-humanista. Los nuevos confines a delimitar subyacen de las implicaciones neurocientíficas en sí mismas y de cómo estas se trasladan a la praxis escolar, si es que tuviesen validez en este campo. Aquí los neuromitos juegan un papel importante. Precisamente, la neuroética como ética aplicada o rama de la bioética recoge estos aspectos mediante la ética neuroeducativa y la neuroética educativa. En su rama fundamental, dicha disciplina abre el debate sobre la neuroeducación moral. Pero la posibilidad de reducir lo moral y todo lo que somos a nuestras bases neurales deriva en nuevos límites. Para superarlos, destaca el potencial de una simbiosis sociocultural y biológica con las nociones de ‘neurocultura’ y de ‘epigénesis proactiva’. Finalmente, el ensayo delibera sobre los límites más especulativos entre lo que somos y nuestras posibilidades para entenderlo en base al transhumanismo._____________________________________________________________________________________ ____________________________________________________________________________________________________ _______HOW TO CITE / CÓMO CITAR: Castillo, P. (2023). Los límites éticos de la neuroeducación. Teoría de la Educación. Revista Interuniversitaria, 35(2), 191-208. (shrink)

Les arguments concernant la sagesse de la poursuite des expérimentations génétiques et des effets eugéniques possibles du génie génétique se retrouvent généralement dans trois domaines : l'éthique biomédicale, la moralité, et la religion et le droit. L'utilisation potentielle du génie génétique a mis en discussion l'eugénisme dans le passé dans les litiges de bioéthique. Le séquençage du génome humain peut nous aider dans l'évolution humaine. Le projet sur le génome humain peut nous aider à comprendre les maladies afin d'orienter les (...) traitements appropriés, d'identifier les mutations responsables de diverses maladies et de les corriger. DOI: 10.13140/RG.2.2.20645.86249. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, which (...) has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

The foundations of mathematics and physics no longer start with fundamental entities and their properties like spatial extension, points, lines or the billiard ball like particles of Newtonian physics. Mathematics has abolished these from its foundations in set theory by making all assumptions explicit and structural. Particle physics has become completely mathematical, connecting to physical reality only through experimental technique. Applying the principles guiding the foundations of mathematics and physics to philosophical analysis underscores that only conscious experience has an (...) intrinsic nature. This leads to a version of realistic monism in which the essence and totality of the existence of physical structure is immediate experience in some form. Identifying physical structure with conscious experience allows the application of mathematics to the evolution of consciousness. Some of the implications from Goedel’s Incompleteness Theorem are connected to creativity and ethics. (shrink)

About: P. DUHEM, “Some reflections on the subject of physical theories” P. DUHEM, “Atomic notation and atomistic hypotheses” P. DUHEM, “A new theory of the inorganic world” P. DUHEM, “Physics and metaphysics” P. DUHEM, “The English school and physical theories” P. DUHEM, “Some reflections on the subject of experimental physics” P. DUHEM, “The evolution of physical theories from the 17th century up to the present day”.

Abstract -/- This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. -/- Key Contributions -/- • Resolution of General Relativity & Quantum Mechanics Paradox -/- CODES introduces structured intelligence fields that reconcile relativistic and quantum-scale physics by (...) incorporating oscillatory chiral dynamics. -/- • Reformulation of Dark Energy & Dark Matter -/- Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. -/- • Predictive Framework for Large-Scale Structures -/- The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. -/- • Resonance-Driven Model of Cosmic Evolution -/- By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. -/- By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. -/- Version Note -/- V2 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. -/- Discussion & Next Steps -/- This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)