Philosophy of biology widely acknowledges that taxonomic practice conditions the delimitation of species; however, this impact has remained predominantly theoretical, lacking precise formal quantification. This article presents a mathematical framework utilizing morphospaces to model this influence across three hierarchical levels: the theoretical morphospace ( Ω ), encompassing the combinatorially possible; the ontological morphospace ( Ω _O ), a subset of the theoretical morphospace constrained by biological viability; and the epistemic morphospace ( Ω _E ), a quotient space of the ontological morphospace defined by taxonomic rules. By treating diagnostic criteria as logical constraints, it becomes possible to quantify the impact of taxonomic decisions on both the number of recognized species and the information cost within the system. Furthermore, the necessary conditions for treating systematics as a formal problem are established. Finally, the critical importance of adopting objective and computable diagnostic criteria to ensure greater rigor in biodiversity classification is highlighted.
About one hundred years ago, the law of homologous series, a sweeping generalization proposed by N. I. Vavilov at a plant breeders’ congress, caused a sensation, so much so that the audience thought they had witnessed the unveiling of something as revolutionary as the periodic table of Mendeleev. Vavilov postulated that the enormous diversity observable in plant forms masked an underlying similarity, one revealed in parallel variations among closely or distantly related plants. In the present article, we consider the law of homologous series from a historical viewpoint and conclude that its unveiling deserves to be recognized as a foundational event in evolutionary developmental biology.
Art making, understood as making music, dancing, and producing visual artworks, has a deep evolutionary history. Traces of musical instruments, figurative arts, and rock art, like engravings and cupules, are found all around Europe, Asia, and Africa since the Pleistocene. The debate about the evolution of art making has produced many theories of how arts evolved in humans’ deep past. In this article, I add my contribution to one of the debate’s most influential positions, Ellen Dissanayake’s account of art making, focusing in particular on her explanation of the antecedents of arts, i.e., mother–infant interaction. I first integrate Dissanayake’s account of ape infant behavior with new evidence from comparative studies and develop a new approach to build an account of the hominin suite of behaviors in the context of parental care using evidence from cognitive paleoanthropology and comparative neurobiology. I then propose a novel method to identify, in the fossil record, the evolution of arts as described by Dissanayake. These two lines of research are importantly intertwined: I suggest that changes in hominin parental care may help identify new cognitive skills relevant for tracing the origin and early developments of arts. I conclude that the capacity of art making may have evolved multiple times since the Middle Pliocene (≈4 mya) in different hominin lineages.
Philosophical discussions of the biomedical sciences have attracted considerable interest over the past few decades, with much of the debate focusing on causation, complex systems, and explanatory levels, each understood in different ways. Although a wide range of views has emerged, a small number of notions have played a prominent and cross-cutting role in understanding how biological systems function. These notions, i.e., mechanism, pathway, and network, are especially central in molecular biology, the field we focus on in this contribution. More specifically, we aim to provide a comprehensive analysis of the relations among these notions as they are employed in molecular biology, shedding light on the relationship between description and explanation, which we treat as two distinct epistemic activities.
Proponents of the idea of basal cognition clash with those seeking to restrict the term “cognitive” to systems showing human-like capacities. The impasse over the definition of cognition is unlikely to end soon, but it will surely be helpful to get clearer on what it is about certain things that makes them indisputably noncognitive. Do the arguments for basal cognition inevitably devolve into claims for a kind of panpsychism, or is there a principled standard for what counts as indisputably noncognitive that all parties will adhere to? This article offers a mark of the noncognitive—it characterizes what it is about certain entities and processes that makes them paradigmatically noncognitive. The characterization is not a novel proposal but a clarification of a rare, though implicit, point of consensus in the cognition wars. I argue that opinion converges on the notion of noncognitive processes being those that appear to be the result only of proximal, efficient physical-chemical causes. A system whose activity profile is of this sort will be a simple mechanism and have the passive and inflexible character that is paradigmatically noncognitive. I end the article with a discussion of the metaphysical background. On most understandings of physicalism, including one adhered to by proponents of basal cognition, all properties, processes, and entities are fundamentally noncognitive or nonmental. This means that the claims for basal cognition are less radical than those proponents typically promise. I discuss a neo-Aristotelian ontology which would enable such claims to become metaphysically substantive.
In this reflection article, we present a new theoretical perspective, which we term integrative neurobiology and cultural context (INCC) theory. Traditionally, social scientists have viewed the human brain as a “black box” of behavior. At the same time, advancements in neuroscience tempt us to perceive behavior as a linear extension of brain processes. We advocate for an alternative research structure that explores the integrative dynamics of cultural context, neuroplasticity, learning, memory, neurotransmitters, and emotions as critical components to explicating the multidimensionality of cross-cultural human behavior. Integrative neurobiology and cultural context (INCC) theory specifically challenges contemporary accounts that map organismal behavior in a linear fashion onto genetic makeup as well as molecular or physicochemical brain processes. This essay addresses a fundamental question: how can we link culture, individual experience, neurobiological processes, and inheritance systems? To achieve this goal, we have developed a new conceptual perspective, which we term cultural neurobiological inheritance systems (CNIS), the foundational concept of integrative neurobiology and cultural context (INCC) theory. The significance of this contribution is that it resolves a critical limitation in current cultural and evolutionary theory. Even though existing models, including gene–culture coevolution, dual inheritance, and niche construction theory, have profoundly illuminated the processes of behavioral transmission and environmental modification, none have specified the neurobiological mechanisms by which these effects become stabilized and transmitted across generations. CNIS is inherited vertically and horizontally, and the strength of transference and fidelity is dependent on the intensity of cultural learning and its simultaneous effects on neuroplasticity, neurotransmitters, and the development of emotional systems. We argue that memory and related neurobiological processes shaped by experience are anchored in discrete, physiological substrates of the human brain. In short, CNIS represents the physical trace of memory in the neural architecture, providing an interface between human experience and the functional neurobiological basis of cognition. Recent empirical research into engram and engram assemblage formation, studies of survivors of the Holocaust and their descendants, and theory of mind research provide direct support for proof of concept for integrative neurobiology and cultural context theory and CNIS.
We propose that life is best understood as the manifestation of biological agency—the capacity of a system to initiate, regulate, and sustain its own organization across molecular, organismal, and ecological scales. This activity is viability-oriented: living systems maintain and reestablish the conditions required for their persistence. The agency–process–scale (APS) framework provides a naturalized, operational account of this organization through six biosignatures of agency: homeostasis, adaptive plasticity, selective boundary regulation, goal-directed behavior, recursive self-repair, and cross-scale coordination. These biosignatures describe what living systems do rather than what they are made of, and are empirically tractable across biological, synthetic, and astrobiological contexts. Unlike nonliving self-organizing systems, living systems actively regenerate the constraints that sustain their organization, producing an intrinsic asymmetry between conditions that support persistence and those that undermine it. Framing life in terms of viability-oriented organization clarifies ambiguous cases such as viruses and protocells, recasts evolutionary transitions as reorganizations of agential structure, and grounds biological purposiveness in ongoing activity rather than design or representation. APS does not offer a final definition of life, but a minimal, testable framework for investigating the organization that makes living systems possible. By foregrounding agency while clarifying its organizational basis, APS integrates functional, processual, and scale-sensitive perspectives into a coherent account of life’s distinctive dynamics.
Model makers often find themselves in the following situation: in order for the model to be able to represent the dynamics of the target system, they have to make certain assumptions that pertain to the system. The problem with these assumptions is not that they are wrong, but that they cannot be derived from observations and experiments. Thus, alternative modeling assumptions can also be used, and the data does not adjudicate between the sets of assumptions. Since a decision must be made, the decision derives from considerations such as the theoretical commitments of the modeler. Focusing on assumptions of this sort, the article examines the assumptions of evolutionary game theory (EGT). Following previous authors who noticed that there were in fact two strands of EGT, the current work compares the set of modeling assumptions made in each. The attempt here is not to adjudicate between the two sets, but to demonstrate that for each strand of EGT, an alternative set of assumptions was available. My hope is that the examination of the chosen assumptions will reveal the theoretical commitments that motivated the choice. Focusing on the latter strand of EGT, the article addresses the following question: What assumptions about evolution did EGT embody that align this modeling tradition with sociobiology? By demonstrating these similarities, I hope to support a broader argument, namely, that models are not neutral structures with respect to their target system.
Are biological objects the same kind of thing? To address the problem posed by their striking diversity, from molecules to organisms, ecosystems, and species, we conducted a comparative descriptive analysis across levels of organization. The results suggest that aggregated and distributed forms share a common biological object status (COBOS), defined by a small set of organizational dimensions: the mixity and distribution of their n – 1 elements, their stratification across levels, and their uptake–process–release coupling of energy, matter, and information through time. COBOS accounts for both within-tier structuring and tier stacking, from molecules to the biosphere, independently of morphological or phylogenetic interpretation. It may provide a basis for relating biological transformations across scales in developmental and evolutionary terms.
During the late 20th century, evolutionary biology contributed to the notion that much of the genome is nonfunctional. This particularly applied to endogenous retroviruses (ERVs), which were seen as parasitic elements. However, growing evidence shows that ERVs play diverse and important roles, especially in gene regulation, development, and immunity. This article examines whether such findings pose a challenge to evolutionary biology, using Imre Lakatos’ model of scientific growth, which judges research programs by their ability to direct fruitful research and anticipate new data. I argue that the current number of known functional ERVs does not significantly contradict the evolutionary program’s low expectations, but that the degree of functionality will rise to anomalous levels if the recent trend of new discoveries continues. Moreover, the evolutionary program has contributed little to the discovery of the functions that have been found so far, except for a few cases where functionality was implied by sequence conservation. Nevertheless, evolutionary biology does possess the theoretical tools to retroactively produce mechanistic explanations for the origin of functional ERVs. The most common type of function—tissue-specific regulation of nearby genes—can be neatly explained in a neo-Darwinian fashion if the newly inserted ERVs immediately exerted a beneficial effect on host gene expression. This model predicts, often successfully, that the relevant transcription factor binding sites are present in the family’s consensus sequence, but has been criticized because ERV insertions with strong regulatory effects are nearly always deleterious. Another notable ERV function is facilitating cell–cell fusion in the placenta. Here, the program is forced to invoke the independent origin of ERV-derived fusion proteins in different mammalian lineages. Taken together, this evaluation yields an ambivalent verdict on the success of the evolutionary research program.
The aim of this article is to paint a big picture of several approaches to explanation and to motivate one of them. The approaches differ in the kind of answer they provide to the question “what is an explanation?” and, derivatively, to questions about what explanations are grounded in and how to assess explanatory quality. The syntactic approach defines explanations as arguments with a particular form. It has well-known problems, dating back to discussions of the covering law model. More recently, semantic approaches have become mainstream, primarily in a causal guise. These approaches treat explanations as defined by their content, particularly causal content. A concise statement of the semantic approach says that to explain a phenomenon is to provide a description of its causal basis. But explanations do not behave like descriptions—as seen by the importance of idealization in explanation. Moreover, recent philosophy has discussed multiple cases of non-causal explanation. Arguably, the semantic approach also provides a scant basis for assessing explanatory power. These problems motivate an alternative, pragmatic approach. I outline a version of the pragmatic approach, which grounds explanation in understanding, and note some of its precedents and inspirations, both in William Bechtel’s work and beyond. I then suggest that the pragmatic approach can readily solve the issues facing the semantic approach. I close by remarking on the considerable work that remains to be done to turn the pragmatic approach into a well-articulated account of scientific explanation.
The persistence of living systems depends on their capacity to sense, distribute, and resolve stress. Across evolution, this pressure shaped increasingly integrated architectures that align local perception with collective regulation, enabling the emergence of multicellular form. Here, I argue that chronic, unresolvable stress exposes a fundamental vulnerability of these architectures and drives the breakdown of tissue-level coordination. Synthesizing perspectives from evolutionary and developmental biology, cancer biology, and trauma psychology, I propose that tumorigenesis represents a morphogenetic trauma response: a stress-induced dissociation in which cells lose access to shared regulatory memory and enact self-reinforcing, anatomically intrusive behaviors. This claim is advanced as a structural analogy rather than a claim of psychological causation, situating trauma as a general biological phenomenon that can manifest across distinct substrates and scales. This view carries therapeutic implications, suggesting a reintegrative approach that seeks to return cancer cells to the homeostatic control of the surrounding tissue.
Arguing about the types and tokens of neuroscience and psychology has provided philosophical sport for decades. Type, or strong identity theory, was the target of Putnam’s original multiple realizability (MR) argument and asserts that because mental types are multiply realized by several different physical types, no lawlike identity relation between mental and physical types exists. Both psychology and neuroscience have made rapid progress in the intervening years, allowing for more empirically-guided ways of exploring their mutual explanatory value to each other. I briefly discuss the historical impact of MR, offer a diagnosis of its endurance, and revisit an earlier position I co-authored with William Bechtel. I then consider MR in light of neuroplasticity and localization, both commonly taken to support the MR argument. I argue that these not only fail in this support, but instead, show the advantage of a more empirically-grounded approach based on structure–function relationships. In this light, MR itself may even be regarded as a kind of neuro-psychological discovery principle; discovering a function that appears to be subserved by multiple neuromechanisms may point us toward interesting commonalities, rather than differences, of neurological structure.
Measurement error is usually construed as the deviation from a true value. But measurement in organismal biology typically is a complex, multi-step process, and living systems are dynamic and spatially heterogeneous, often hindering a unique definition of a measurand. Thus, a single true value of an organismal measurement, independent of a specific measurement process, does not exist, which also invalidates the classic realist notion of measurement error. Instead, I advocate an instrumentalist view of measurement that shifts the focus away from an unmeasurable true value toward the practical question of which biological, technical, and experimental factors influence measurement outcomes. I propose to include non-biological factors, such as different measurement environments and devices, observers, and the sequence of measurement, as technical covariates in biometric models. I present a simple least squares implementation for estimating mean effects and differences in variance while correcting for such “attributable” measurement effects. Repeated measurements are only of limited help in this regard because biological measures typically are not completely repeatable. The variance among partly repeated measures neither reflects the actual replicability of measurements, nor is there any benchmark as to how small this variance should be. Often, a large part of “unattributable” measurement effects is due to definitional uncertainty as well as the temporal and spatial heterogeneity of biological systems. I further demonstrate that averaging repeated measures has only negligible effects on the standard error of statistical estimates; increasing sample size (biological replicates) is generally more efficient than repeating measures (technical replicates).
In the human evolutionary sciences, there is a near-consensus that normative cognition and normative motivation are adaptations, the result of selection for psychological capacities that enable agents to harness cooperation profits more effectively, though specific versions of this idea differ markedly. This article picks up an alternative idea floated in the existing literature but not developed: norms evolved to reduce uncertainty about the social environment. While reducing uncertainty has positive effects on cooperation, by making coordination less problematic, it has positive effects on private, and even antisocial, activities as well. While the evidence is far from decisive, we suggest that it supports the uncertainty-reduction hypothesis more clearly than the normative-guidance-enhances-cooperation hypothesis: it is more consistent with the regulatory breadth of norms, the observed cultural diversity of norms, and the apparent existence of anti-cooperative norms.
Our intuition suggests a trend in biological evolution toward greater complexity. However, defining complexity is challenging. Here, we explore measures of biological complexity that assign low complexity to both highly ordered and highly random systems and high complexity to those in between. Most biological systems are highly complex, falling within this intermediate range, displaying both order and variability. Complexity measures quantify the information an organism stores in its genome or nervous system about its environment. Thereby, they support the idea that evolution increases the “knowledge” an organism accumulates about its niche. This is in line with the conceptual framework of cognitive biology, which views evolution as a progressive accumulation of knowledge or as an increase in epistemic complexity. In this view, evolution resembles a cognitive “ratchet” that pushes the organisms unidirectionally towards higher complexity. A dynamic environment continually creates problems to be solved. To survive means to solve problems posed by the environment, and each solution becomes embodied knowledge. Cognitive biology is closely related to the current measures of biological complexity because it uses concepts of information and entropy from information theory and thermodynamics. We also discuss the link between cognitive biology and complexity measures based on integrated information theory (IIT). When considering humans as conscious beings, it seems necessary to postulate the emergence of a new kind of knowledge—self-aware, self-referential knowledge. The appearance of self-reflection in evolution indicates that the human brain and cognition have reached a new qualitative level in epistemic complexity. In summary, cognitive biology, complemented by complexity measures, offers a unified framework for studying the evolution of biological complexity.
Traditional canon in biology holds that there is a single, universal genetic code. It is common to see the continued use of the language “universal” even in the face of a number of alternative codes found in microbes, mitochondria, chloroplasts, and other plastids. This usage is often justified by appeal to the relative insignificance of nonstandard genetic codes. In this article, I argue that molecular biology often misuses relative significance as a means to resist thinking more deeply about when and how it is justifiable and productive to conceptualize the genetic code as a “universal” feature of the natural world. When used to minimize the challenges a phenomenon represents to popular theories, relative significance debates interfere with the pursuit of more fruitful research questions. This is not to say that all appeals to relative significance are unjustified and unproductive. Following Kovaka (2021) and Deaven (2023), I outline a variety of important relative significance questions that are worth pursuing. Instead of conceptualizing the genetic code as “universal”, I offer a more promising way of thinking about the relative significance of nonstandard genetic codes. For the purposes of molecular biology, I propose conceptualizing a plurality of genetic codes with varying degrees of invariance (Woodward 2003). Doing so has the potential to facilitate greater understanding of genetic code structure and evolution (Potochnik 2017) and provide the conceptual framework necessary for justifying biological practices.
Standard physicalism often renders subjective experience epiphenomenal, while interactionist accounts struggle to reconcile mental causation with energy conservation. We propose the force of experience: a real, physically efficacious force exerted by experience on neural architecture. To address the objection that a fundamental force should act universally, we introduce biological confinement, analogous to the confinement of the strong nuclear interaction. The force of experience acts exclusively on structured biological information—the coherent, meaning-bearing informational patterns sustained within the living brain. Within the brain’s open thermodynamic system, experience supplies the causal influence required to bias activation barriers of neural logic gates, releasing stored metabolic potential in a direction determined by the meaning of the experience and the organism’s prior experiential history. This framework reconceives subjective experience as a confined physical force essential for biological agency and clarifies how meaning-driven interactions can be both constructive and destructive. We situate this proposal within historical perspectives on mental causation, including agential realism, dispositional causation, and nonreductive materialist psychology, while offering a biophysical mechanism absent from prior accounts.
This article examines Rosenblueth, Wiener, and Bigelow’s 1943 article “Behavior, Purpose and Teleology”, which is widely remembered both as the foundational text of cybernetics and a major contribution to 20th-century debates on teleology. Despite the article’s fame, philosophical discussions have tended to abstract it from its argumentative and historical context, treating it as one mechanistic proposal among others for explaining purposive behavior. This article contends that such readings obscure a set of philosophically significant issues that "Behavior, Purpose and Teleology" raises but have received insufficient attention. Chief among these is the question of the appropriate level of description at which purpose and teleology should be located and explained.
