Showing 1–50 of 77 results for author: Kaneko, K

A loser in both environments can survive by switching between them

Authors: Riz Fernando Noronha, Kunihiko Kaneko

Abstract: How can a species persist in an environment where it is always outcompeted? Using a minimal predator-prey model with environment-dependent parameters, we show that a predator driven to extinction in each of two static environments can survive indefinitely once the environment alternates between them fast enough. We derive the critical switching rate above which persistence occurs, and show that ra… ▽ More How can a species persist in an environment where it is always outcompeted? Using a minimal predator-prey model with environment-dependent parameters, we show that a predator driven to extinction in each of two static environments can survive indefinitely once the environment alternates between them fast enough. We derive the critical switching rate above which persistence occurs, and show that random (Poisson) switching needs to be faster than periodic switching in order to offset prolonged spells in the unfavorable environment. We then generalize the mechanism to any two-species system, and can predict persistence solely based on the sign of a single ``switching rescue function" assembled from the two boundary vector fields. This general result has broad reaching consequences: for instance, when applied to a standard model of viral dynamics, it predicts that two drugs which each clear a pathogen on their own can fail when alternated, giving a non-resistance-based explanation for the failure of drug-cycling strategies. Our results demonstrate that the tempo of environment change, as opposed to the environments themselves, can lead to species survival. △ Less

Submitted 5 July, 2026; originally announced July 2026.

Comments: 13 pages, 7 figures

Delayed control driven oscillations in plant roots

Authors: Riz Fernando Noronha, Kunihiko Kaneko, Koichi Fujimoto

Abstract: Arabidopsis roots show oscillatory growth patterns on homogeneous agar surfaces, whereas other plants, such as maize, do not. Although several explanations have been proposed, a simple and general model that makes testable predictions across species has been lacking. Roots sense gravity and correct their growth direction towards the vertical. Motivated by recent evidence for a time delay in this g… ▽ More Arabidopsis roots show oscillatory growth patterns on homogeneous agar surfaces, whereas other plants, such as maize, do not. Although several explanations have been proposed, a simple and general model that makes testable predictions across species has been lacking. Roots sense gravity and correct their growth direction towards the vertical. Motivated by recent evidence for a time delay in this gravitropic correction, we develop a minimal nonlinear model based on the delay hypothesis that predicts whether a root oscillates or grows vertically downwards. The model identifies a fourfold relation between the delay and time period, robust across different response functions. Analysing images of Arabidopsis, we find that the mode of the oscillatory arc length is not significantly different between inclined and vertical growth conditions. The quantitative agreement between the experimentally measured oscillatory arc length and the arc length estimated from estimated root growth speed and response delay supports this fourfold delay-period rule for delay-driven root oscillations. The simplicity of our model allows for a direct comparison with data from diverse plant species. △ Less

Submitted 30 April, 2026; originally announced April 2026.

Comments: 12 pages, 11 figures

Noise-Driven Differentiation via Gene Frustration and Epigenetic Fixation

Authors: Davey Plugers, Kunihiko Kaneko

Abstract: Gene expression in cells is stochastic, yet differentiation can display reproducible timing and stable fate commitment. We develop an analytical theory for a previously identified mechanism in which weakly stable intermediate, or frustrated, gene-expression states are perturbed by stochastic fluctuations and subsequently fixed by slow epigenetic feedback. By eliminating the fast expression dynamic… ▽ More Gene expression in cells is stochastic, yet differentiation can display reproducible timing and stable fate commitment. We develop an analytical theory for a previously identified mechanism in which weakly stable intermediate, or frustrated, gene-expression states are perturbed by stochastic fluctuations and subsequently fixed by slow epigenetic feedback. By eliminating the fast expression dynamics, we show that the differentiation of the slow epigenetic variable is driven by the noise of gene-expression, which can be amplified by regulatory interactions. We derive the logarithmic dependence of onset time for differentiation upon the effective noise intensity, and the input-dependent probability of reaching either fate. We further construct a Waddington-inspired time-dependent probability landscape that visualizes population branching and progressive fate fixation. △ Less

Submitted 5 August, 2026; v1 submitted 20 April, 2026; originally announced April 2026.

Comments: 12 pages, 5 figures

Complex versus Complicated Systems Biology, Universality versus Detailed Modelling

Authors: Kunihiko Kaneko

Abstract: Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects of biological systems. In this case, an appropriate simple model represents a universality class. The extraction of universal properties is supported by evoluti… ▽ More Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects of biological systems. In this case, an appropriate simple model represents a universality class. The extraction of universal properties is supported by evolutionary robustness and the reduction of dimensionality in high-dimensional states. Integrating the data-driven omics approach with the universality approach is an important step in systems biology. △ Less

Submitted 17 March, 2026; originally announced March 2026.

Comments: essay submitted to special issue on "Modeling and dynamics" for Current Opinion in Systems Biology

Self-Organized Bioelectricity via Collective Pump Alignment: Toward a Physical Origin of Chemiosmosis

Authors: Ryosuke Nishide, Kunihiko Kaneko

Abstract: Directional ion transport across membranes maintains living systems in nonequilibrium, which underlies chemiosmotic energy conversion. However, the physical origin of collectively organized ion transport in primitive cellular systems remains unclear. Here, we propose a minimal model in which ion pumps collectively align through feedback between ion transport and electrostatic interactions. In the… ▽ More Directional ion transport across membranes maintains living systems in nonequilibrium, which underlies chemiosmotic energy conversion. However, the physical origin of collectively organized ion transport in primitive cellular systems remains unclear. Here, we propose a minimal model in which ion pumps collectively align through feedback between ion transport and electrostatic interactions. In the model, directional ion transport generates a membrane potential, while the resulting electrochemical potential biases pump orientation, leading to self-organized collective alignment. Numerical simulations and mean-field analysis reveal a nonequilibrium transition from a disordered state without net transport to a pump-alignment state with sustained membrane potentials. The critical behavior is consistent with the mean-field Ising universality class; however, the effective field is generated self-consistently by nonequilibrium ion transport. We further show that protocell asymmetry can bias the polarity of the membrane potential. These results provide a generic self-organizing mechanism for the emergence of bioelectricity and a physical route toward chemiosmotic coupling in protocells. △ Less

Submitted 18 May, 2026; v1 submitted 17 February, 2026; originally announced February 2026.

Cross-feeding yields high-dimensional chaos and coexistence of species beyond exclusion principle

Authors: Takashi Shimada, Kunihiko Kaneko

Abstract: Species interactions through cross-feeding via leakage and uptake of chemicals are important in microbial communities, and play an essential role in the coexistence of diverse species. Here, we study a simple dynamical model of a microbial community in which species interact by competing for the uptake of common metabolites that are leaked by other species. The model includes coupled dynamics of s… ▽ More Species interactions through cross-feeding via leakage and uptake of chemicals are important in microbial communities, and play an essential role in the coexistence of diverse species. Here, we study a simple dynamical model of a microbial community in which species interact by competing for the uptake of common metabolites that are leaked by other species. The model includes coupled dynamics of species populations and chemical concentrations in the medium, allowing for a variety of uptake and leakage networks among species. Depending on the structure of these networks, the system exhibits different attractors, including fixed points, limit cycles, low-dimensional chaos, and high-dimensional chaos. In the fixed-point and limit-cycle cases, the number of coexisting species is bounded by the number of exchangeable chemicals, consistent with the well-known competitive exclusion principle. In contrast, in the low-dimensional chaotic regime, the number of coexisting species exhibits noticeable but limited excess over this limit. Remarkably, in the high-dimensional chaotic regime, a much larger number of species beyond this limit coexist persistently over time. In this case, the rank-abundance distribution is broader than exponential, as often observed in real ecosystems. The population dynamics displays intermittent switching among quasi-stationary states, while the chemical dynamics explore most of the high dimensions. We find that such high-dimensional chaos is ubiquitous when the number of uptake chemicals is moderately larger than the number of leaked chemicals. Our results identify high-dimensional chaos with intermittent switching as a generic dynamical mechanism that stabilizes coexistence in interacting systems. We discuss its relevance to sustaining diverse microbial communities with leak-uptake cross-feeding. △ Less

Submitted 30 January, 2026; originally announced January 2026.

Comments: 32 pages, 15 figures

Omics-scale polymer computational database transferable to real-world artificial intelligence applications

Authors: Ryo Yoshida, Yoshihiro Hayashi, Hidemine Furuya, Ryohei Hosoya, Kazuyoshi Kaneko, Hiroki Sugisawa, Yu Kaneko, Aiko Takahashi, Yoh Noguchi, Shun Nanjo, Keiko Shinoda, Tomu Hamakawa, Mitsuru Ohno, Takuya Kitamura, Misaki Yonekawa, Stephen Wu, Masato Ohnishi, Chang Liu, Teruki Tsurimoto, Arifin, Araki Wakiuchi, Kohei Noda, Junko Morikawa, Teruaki Hayakawa, Junichiro Shiomi , et al. (81 additional authors not shown)

Abstract: Developing large-scale foundational datasets is a critical milestone in advancing artificial intelligence (AI)-driven scientific innovation. However, unlike AI-mature fields such as natural language processing, materials science, particularly polymer research, has significantly lagged in developing extensive open datasets. This lag is primarily due to the high costs of polymer synthesis and proper… ▽ More Developing large-scale foundational datasets is a critical milestone in advancing artificial intelligence (AI)-driven scientific innovation. However, unlike AI-mature fields such as natural language processing, materials science, particularly polymer research, has significantly lagged in developing extensive open datasets. This lag is primarily due to the high costs of polymer synthesis and property measurements, along with the vastness and complexity of the chemical space. This study presents PolyOmics, an omics-scale computational database generated through fully automated molecular dynamics simulation pipelines that provide diverse physical properties for over $10^5$ polymeric materials. The PolyOmics database is collaboratively developed by approximately 260 researchers from 48 institutions to bridge the gap between academia and industry. Machine learning models pretrained on PolyOmics can be efficiently fine-tuned for a wide range of real-world downstream tasks, even when only limited experimental data are available. Notably, the generalisation capability of these simulation-to-real transfer models improve significantly as the size of the PolyOmics database increases, exhibiting power-law scaling. The emergence of scaling laws supports the "more is better" principle, highlighting the significance of ultralarge-scale computational materials data for improving real-world prediction performance. This unprecedented omics-scale database reveals vast unexplored regions of polymer materials, providing a foundation for AI-driven polymer science. △ Less

Submitted 7 November, 2025; originally announced November 2025.

Comments: 65 pages, 11 figures

A Self-Organized Tower of Babel: Diversification through Competition

Authors: Riz Fernando Noronha, Kunihiko Kaneko

Abstract: We introduce a minimal evolutionary model to show how local cooperation and global competition can create a transition to the diversity of communities such as linguistic groups. By using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an agent's local neighborhood and global dissimilarity, clusters of diverse communities with different fitness are o… ▽ More We introduce a minimal evolutionary model to show how local cooperation and global competition can create a transition to the diversity of communities such as linguistic groups. By using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an agent's local neighborhood and global dissimilarity, clusters of diverse communities with different fitness are organized by equalizing the finesses on the boundaries, where their numbers and sizes are robust to parameters. We observe successive transitions over quasi-stationary states, as triggered by the emergence of new communities on the boundaries. Our abstract framework provides a simple mechanism for the diversification of culture. △ Less

Submitted 13 October, 2025; originally announced October 2025.

Comments: Main: 6 pages, 4 figures. Supplement: 7 pages, 9 figures

Journal ref: Phys. Rev. Research 8, 013303 (2026)

Generalising the Central Dogma as a cross-hierarchical principle of biology

Authors: Nobuto Takeuchi, Kunihiko Kaneko

Abstract: The Central Dogma of molecular biology, as originally proposed by Crick, asserts that information passed into protein cannot flow back out. This principle has been interpreted as underpinning modern understandings of heredity and evolution, implying the unidirectionality of information flow from nucleic acids to proteins. Here, we propose a generalisation of the Central Dogma as a division of labo… ▽ More The Central Dogma of molecular biology, as originally proposed by Crick, asserts that information passed into protein cannot flow back out. This principle has been interpreted as underpinning modern understandings of heredity and evolution, implying the unidirectionality of information flow from nucleic acids to proteins. Here, we propose a generalisation of the Central Dogma as a division of labour between the transmission and expression of information: the transmitter (nucleic acids) perpetuates information across generations, whereas the expressor (protein) enacts this information to facilitate the transmitter's function without itself perpetuating information. We argue that this generalisation offers two benefits. First, it provides a unifying perspective for comparing the Central Dogma to analogous divisions of labour observed at vastly different biological scales, including multicellular organisms, eukaryotic cells, organelles, and bacteria. Second, it offers a theoretical framework to explain the Central Dogma as an outcome of evolution. Specifically, we review a mathematical model suggesting that the Central Dogma originates through spontaneous symmetry breaking driven by evolutionary conflicts between different levels of selection. By reframing the Central Dogma as an informational relationship between components of a system, this generalisation underscores its broader relevance across the biological hierarchy and sheds light on its evolutionary origin. △ Less

Submitted 6 August, 2025; originally announced August 2025.

Comments: 38 pages, 2 figures

Anonymous monitoring enables turn-taking and sustainablity in collective resource governance: Multi-player evolutionary dynamical-systems game

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: Sustainable resource use in large societies requires social institutions that specify acceptable behavior and punish violators. Because mutual monitoring becomes prohibitively costly as populations grow, we examine whether sustainability can be maintained when only anonymized information is available. Using the evolutionary dynamical-systems game framework, we model the common-pool resource manage… ▽ More Sustainable resource use in large societies requires social institutions that specify acceptable behavior and punish violators. Because mutual monitoring becomes prohibitively costly as populations grow, we examine whether sustainability can be maintained when only anonymized information is available. Using the evolutionary dynamical-systems game framework, we model the common-pool resource management game. In the model, each player's harvesting decisions shape the resource dynamics and depend on the resource's state, the player's wealth, and the group average wealth. Strategies are encoded as two-parameter decision-making functions that mutate across generations. Evolutionary simulations reveal that players self-organize into clusters that alternate harvesting turns: individuals within a cluster harvest synchronously, while the clusters themselves take turns. The emergent institutional rule is strikingly simple: "wait when rich, harvest when below average." While the majority cluster tends to exploit the minority, moderate diversity in decision parameters of strategies allows "turn-taking of turns" between the majority and minority roles, improving efficiency, equity, and resistance to selfish mutants. We quantify the difficulty of managing institutions as population size increases. When group size is fixed, the minimum number of groups required for cooperation grows exponentially with group size. If, however, groups enlarge gradually, the scaling transitions to a power law, indicating that institutions remain stable when they are first built in small populations and subsequently adapted to larger ones. Our findings provide a theoretical basis for the self-organization of institutions in large societies, illuminating how anonymized information can coordinate behavior and how institutional success depends on its developmental trajectory. △ Less

Submitted 30 July, 2025; originally announced July 2025.

Comments: 15 + 9 pages, 7 + 11 figures, 1 table

Stability Control of Metastable States as a Unified Mechanism for Flexible Temporal Modulation in Cognitive Processing

Authors: Tomoki Kurikawa, Kunihiko Kaneko

Abstract: Flexible modulation of temporal dynamics in neural sequences underlies many cognitive processes. For instance, we can adaptively change the speed of motor sequences and speech. While such flexibility is influenced by various factors such as attention and context, the common neural mechanisms responsible for this modulation remain poorly understood. We developed a biologically plausible neural netw… ▽ More Flexible modulation of temporal dynamics in neural sequences underlies many cognitive processes. For instance, we can adaptively change the speed of motor sequences and speech. While such flexibility is influenced by various factors such as attention and context, the common neural mechanisms responsible for this modulation remain poorly understood. We developed a biologically plausible neural network model that incorporates neurons with multiple timescales and Hebbian learning rules. This model is capable of generating simple sequential patterns as well as performing delayed match-to-sample (DMS) tasks that require the retention of stimulus identity. Fast neural dynamics establish metastable states, while slow neural dynamics maintain task-relevant information and modulate the stability of these states to enable temporal processing. We systematically analyzed how factors such as neuronal gain, external input strength (contextual cues), and task difficulty influence the temporal properties of neural activity sequences - specifically, dwell time within patterns and transition times between successive patterns. We found that these factors flexibly modulate the stability of metastable states. Our findings provide a unified mechanism for understanding various forms of temporal modulation and suggest a novel computational role for neural timescale diversity in dynamically adapting cognitive performance to changing environmental demands. △ Less

Submitted 12 April, 2025; originally announced April 2025.

Evolution of robust cell differentiation under epigenetic feedback

Authors: Davey Plugers, Kunihiko Kaneko

Abstract: In multi-cellular organisms, cells differentiate into multiple types as they divide. States of these cell types, as well as their numbers, are known to be robust to external perturbations; as conceptualized by Waddington's epigenetic landscape where cells embed themselves in valleys corresponding to final cell types. How is such robustness achieved by developmental dynamics and evolution? To addre… ▽ More In multi-cellular organisms, cells differentiate into multiple types as they divide. States of these cell types, as well as their numbers, are known to be robust to external perturbations; as conceptualized by Waddington's epigenetic landscape where cells embed themselves in valleys corresponding to final cell types. How is such robustness achieved by developmental dynamics and evolution? To address this question, we consider a model of cells with gene expression dynamics and epigenetic feedback, governed by a gene regulation network. By evolving the network to achieve more cell types, we identified three major differentiation processes exhibiting different properties regarding their variance, attractors, stability, and robustness. The first of these, type A, exhibits chaos and long-lived oscillatory dynamics that slowly transition until reaching a steady state. The second, type B, follows a channeled annealing process where the epigenetic changes in combination with noise shift the cells towards varying final cell states that increase the stability. Lastly, type C exhibits a quenching process where cell fate is quickly decided by falling into pre-existing fixed points while cell trajectories are separated through periodic attractors or saddle points. We find types A and B to correspond well with Waddington's landscape while being robust. Finally, the dynamics of type B demonstrate a differentiation process that uses a directed shifting of fixed points, visualized through the dimensional reduction of gene-expression states. Correspondence with the experimental data of gene expression variance through differentiation is also discussed. △ Less

Submitted 5 December, 2025; v1 submitted 26 March, 2025; originally announced March 2025.

Comments: 22 pages, 22 figures

Journal ref: Phys. Rev. Research 8, (2026) 013059

Enzyme as Maxwell's Demon: Steady-state Deviation from Chemical Equilibrium by Enhanced Enzyme Diffusion

Authors: Shunsuke Ichii, Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

Abstract: Enhanced enzyme diffusion (EED), in which the diffusion coefficient of an enzyme transiently increases during catalysis, has been extensively reported experimentally. We numerically and analytically demonstrate that such enzymes can act as Maxwell's demons. They use their enhanced diffusion as a memory of the previous catalytic reaction, to gain information and drive steady-state chemical concentr… ▽ More Enhanced enzyme diffusion (EED), in which the diffusion coefficient of an enzyme transiently increases during catalysis, has been extensively reported experimentally. We numerically and analytically demonstrate that such enzymes can act as Maxwell's demons. They use their enhanced diffusion as a memory of the previous catalytic reaction, to gain information and drive steady-state chemical concentrations away from chemical equilibrium. Our theoretical analysis identifies the conditions for this process, highlighting the functional role of EED and its relevance to cellular systems. △ Less

Submitted 17 July, 2025; v1 submitted 21 March, 2025; originally announced March 2025.

Comments: 11 pages, 7 figures

Modelling Soil as a Living System: Feedback between Microbial Activity and Spatial Structure

Authors: Riz Fernando Noronha, Kim Sneppen, Kunihiko Kaneko

Abstract: Soil is a complex, dynamic material, with physical properties that depend on its biological content. We propose a cellular automaton model for self-organizing soil structure, where soil aggregates and serves as food for microbial species. These, in turn, produce nutrients that facilitate self-amplification, establishing a cyclical dynamic of consumption and regeneration. Our model explores the spa… ▽ More Soil is a complex, dynamic material, with physical properties that depend on its biological content. We propose a cellular automaton model for self-organizing soil structure, where soil aggregates and serves as food for microbial species. These, in turn, produce nutrients that facilitate self-amplification, establishing a cyclical dynamic of consumption and regeneration. Our model explores the spatial interactions between these components and their role in sustaining a balanced ecosystem. The main results demonstrate that (1) spatial structure supports a stable living state, preventing population collapse or uncontrolled growth; (2) the spatial model allows for the coexistence of parasitic species, which exploit parts of the system without driving it to extinction; and (3) optimal growth conditions for microbes are associated to diverse length scales in the soil structure, suggesting that heterogeneity is key to ecosystem resilience. These findings highlight the importance of spatio-temporal dynamics of life in soil ecology. △ Less

Submitted 27 February, 2025; originally announced February 2025.

Journal ref: Phys. Rev. Res. 7, 023207 (2025)

Self-organized institutions in evolutionary dynamical-systems game

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: Social institutions are systems of shared norms and rules that regulate people's behaviors, often emerging without external enforcement. They provide criteria to distinguish cooperation from defection and establish rules to sustain cooperation, shaped through long-term trial and error. While principles for successful institutions have been proposed, the mechanisms underlying their emergence remain… ▽ More Social institutions are systems of shared norms and rules that regulate people's behaviors, often emerging without external enforcement. They provide criteria to distinguish cooperation from defection and establish rules to sustain cooperation, shaped through long-term trial and error. While principles for successful institutions have been proposed, the mechanisms underlying their emergence remain poorly understood. Here, we introduce the evolutionary dynamical-systems game, a framework that couples game actions with environmental dynamics and explores the evolution of cognitive frameworks for decision-making. We analyze a minimal model of common-pool resource management, where resources grow naturally and are harvested. Players use decision-making functions to determine whether to harvest at each step, based on environmental and peer monitoring. As these functions evolve, players detect selfish harvesting and punish it by degrading the environment through harvesting. This process leads to the self-organization of norms that classify harvesting actions as cooperative, defective, or punitive. The emergent norms for ``cooperativeness'' and rules of punishment serve as institutions. The environmental and players' states converge to distinct modes characterized by limit-cycles, representing temporal regularities in socio-ecological systems. These modes remain stable despite slight variations in decision-making, illustrating the stability of institutions. The evolutionary robustness of decision-making functions serves as a measure of the evolutionary favorability of institutions, highlighting the role of plasticity in responding to diverse opponents. This work introduces foundational concepts in evolutionary dynamical-systems games and elucidates the mechanisms underlying the self-organization of institutions by modeling the interplay between ecological dynamics and human decision-making. △ Less

Submitted 13 April, 2025; v1 submitted 13 January, 2025; originally announced January 2025.

Comments: 15 + 7pages, 6 + 12 figures, 2 + 1 tables

Dimensional reduction and adaptation-development-evolution relation in evolved biological systems

Authors: Kunihiko Kaneko

Abstract: Life systems are complex and hierarchical, with diverse components at different scales, yet they sustain themselves, grow, and evolve over time. How can a theory of such complex biological states be developed? Here we note that for a hierarchical biological system to be robust, it must achieve consistency between micro-scale (e.g. molecular) and macro-scale (e.g. cellular) phenomena. This allows f… ▽ More Life systems are complex and hierarchical, with diverse components at different scales, yet they sustain themselves, grow, and evolve over time. How can a theory of such complex biological states be developed? Here we note that for a hierarchical biological system to be robust, it must achieve consistency between micro-scale (e.g. molecular) and macro-scale (e.g. cellular) phenomena. This allows for a universal theory of adaptive change in cells based on biological robustness and consistency between cellular growth and molecular replication. Here, we show how adaptive changes in high-dimensional phenotypes (biological states) are constrained to low-dimensional space, leading to the derivation of a macroscopic law for cellular states. The theory is then extended to evolution, leading to proportionality between evolutionary and environmental responses, as well as proportionality between phenotypic variances due to noise and due to genetic changes. The universality of the results across several models and experiments is demonstrated. Then, by further extending the theory of evolutionary dimensional reduction to multicellular systems, the relationship between multicellular development and evolution, in particular the developmental hourglass, is demonstrated. Finally, the possibility of collapse of dimensional reduction under nutrient limitation is discussed. △ Less

Submitted 1 October, 2024; v1 submitted 27 July, 2024; originally announced July 2024.

Comments: Review as a proceeding paper for IUPAB conference

Journal ref: Biophysical Reviews(2024)

Formation of human kinship structures depending on population size and cultural mutation rate

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: How does social complexity depend on population size and cultural transmission? Kinship structures in traditional societies provide a fundamental illustration, where cultural rules between clans determine people's marriage possibilities. Here we propose a simple model of kinship interactions that considers kin and in-law cooperation and sexual rivalry. In this model, multiple societies compete. So… ▽ More How does social complexity depend on population size and cultural transmission? Kinship structures in traditional societies provide a fundamental illustration, where cultural rules between clans determine people's marriage possibilities. Here we propose a simple model of kinship interactions that considers kin and in-law cooperation and sexual rivalry. In this model, multiple societies compete. Societies consist of multiple families with different cultural traits and mating preferences. These values determine interactions and hence the growth rate of families and are transmitted to offspring with mutations. Through a multilevel evolutionary simulation, family traits and preferences are grouped into multiple clans with inter-clan mating preferences. It illustrates the emergence of kinship structures as the spontaneous formation of interdependent cultural associations. Emergent kinship structures are characterized by the cycle length of marriage exchange and the number of cycles in society. We numerically and analytically clarify their parameter dependence. The relative importance of cooperation versus rivalry determines whether attraction or repulsion exists between families. Different structures evolve as locally stable attractors. The probabilities of formation and collapse of complex structures depend on the number of families and the mutation rate, showing characteristic scaling relationships. It is now possible to explore macroscopic kinship structures based on microscopic interactions, together with their environmental dependence and the historical causality of their evolution. We propose the basic causal mechanism of the formation of typical human social structures by referring to ethnographic observations and concepts from statistical physics and multilevel evolution. Such interdisciplinary collaboration will unveil universal features in human societies. △ Less

Submitted 15 July, 2024; originally announced July 2024.

Comments: 9 pages, 6 figures

Constructing universal Phenomenology for biological cellular systems: An idiosyncratic review on evolutionary dimensional reduction

Authors: Kunihiko Kaneko

Abstract: Possibility to establish macroscopic phenomenological theory for biological systems, akin to the akin to the well-established framework of thermodynamics, is briefly reviewed. We introduce the concept of an evolutionary fluctuation-response relationship, which highlights the need for a tight correlation between the variance in phenotypic traits caused by genetic mutations and by internal noise. We… ▽ More Possibility to establish macroscopic phenomenological theory for biological systems, akin to the akin to the well-established framework of thermodynamics, is briefly reviewed. We introduce the concept of an evolutionary fluctuation-response relationship, which highlights the need for a tight correlation between the variance in phenotypic traits caused by genetic mutations and by internal noise. We provide a distribution theory that allows us to derive these relationships, which suggests that the changes in traits resulting from adaptation and evolution are considerably constrained within a lower-dimensional space. We explore the reasons behind this dimensional reduction, focusing on the constraints posed by the requirements for steady growth and robustness achieved through the evolutionary process. We draw support from recent laboratory and numerical experiments to substantiate our claims. Universality of evolutionary dimensional reduction is presented, whereas potential theoretical formulations for it are discussed. We conclude by briefly considering the prospects of establishing a macroscopic framework that characterizes biological robustness and irreversibility in cell differentiation, as well as an ideal cell model. △ Less

Submitted 9 January, 2024; v1 submitted 17 October, 2023; originally announced October 2023.

Comments: 22pages,2 figures, proceeding paper for STATPHYS28, submitted to JSTAT

Dynamical Theory for Adaptive Systems

Authors: Tuan Minh Pham, Kunihiko Kaneko

Abstract: The study of adaptive dynamics, involving many degrees of freedom on two separated timescales, one for fast changes of state variables and another for the slow adaptation of parameters controlling the former's dynamics is crucial for understanding feedback mechanisms underlying evolution and learning. We present a path-integral approach à la Martin-Siggia-Rose-De Dominicis-Janssen (MSRDJ) to analy… ▽ More The study of adaptive dynamics, involving many degrees of freedom on two separated timescales, one for fast changes of state variables and another for the slow adaptation of parameters controlling the former's dynamics is crucial for understanding feedback mechanisms underlying evolution and learning. We present a path-integral approach à la Martin-Siggia-Rose-De Dominicis-Janssen (MSRDJ) to analyse nonequilibrium phase transitions in such dynamical systems. As an illustration, we apply our framework to the adaptation of gene-regulatory networks under a dynamic genotype-phenotype map: phenotypic variations are shaped by the fast stochastic gene-expression dynamics and are coupled to the slowly evolving distribution of genotypes, each encoded by a network structure. We establish that under this map, genotypes corresponding to reciprocal networks of coherent feedback loops are selected within an intermediate range of environmental noise, leading to phenotypic robustness. △ Less

Submitted 5 August, 2024; v1 submitted 2 June, 2023; originally announced June 2023.

Comments: 30 pages and 2 figures

Report number: 113501

Journal ref: Journal of Statistical Mechanics: Theory and Experiment, (2024)

Evolutionary Shaping of Low-Dimensional Path Facilitates Robust and Plastic Switching Between Phenotypes

Authors: Ayaka Sakata, Kunihiko Kaneko

Abstract: Biological systems must be robust for stable function against perturbations, but robustness alone is not sufficient. The ability to switch between appropriate states (phenotypes) in response to different conditions is essential for biological functions. How are robustness and plasticity simultaneously acquired through evolution? We examine the evolution of genotypes that realize plastic switching… ▽ More Biological systems must be robust for stable function against perturbations, but robustness alone is not sufficient. The ability to switch between appropriate states (phenotypes) in response to different conditions is essential for biological functions. How are robustness and plasticity simultaneously acquired through evolution? We examine the evolution of genotypes that realize plastic switching between two phenotypes upon external inputs, as well as stationary expressions of phenotypes. We introduce a statistical physics model consisting of spins, with active and regulatory sites, which are distinct from each other. We represent the phenotype and genotype as spin configurations and the spin-spin interactions, respectively. The fitness for selection is given so that it takes a higher value as more of the active sites take two requested spin configurations depending on the regulation. We numerically evolve the interaction matrix by changing them with mutations and selection of those with higher fitness. Our numerical simulations show that characteristic genotypes evolve slightly above the transition temperature between replica symmetric and replica symmetry breaking phase. These genotypes shape two spin configurations separately depending on the regulation, where the two phenotypes are dominantly represented by the genotypes' first and second eigenmodes, and smooth switching of two phenotypes are achieved by following a one-dimensional path connecting the two phenotypes. Upon changes in regulations, spin configurations are attracted to this path, which allows for robust and plastic switching between the two phenotypes. The statistical-physics analysis show that the free energy landscape has a valley along the switching path. Our finding indicates that the compatibility of the robustness and plasticity is acquired by the evolution of the low-dimensionality in the phenotype space. △ Less

Submitted 22 April, 2023; originally announced April 2023.

Comments: 34 pages, 13 figures

Universal Transitions between Growth and Dormancy via Intermediate Complex Formation

Authors: Jumpei F. Yamagishi, Kunihiko Kaneko

Abstract: A simple cell model consisting of a catalytic reaction network with intermediate complex formation is numerically studied. As nutrients are depleted, the transition from the exponential growth phase to the growth-arrested dormant phase occurs along with hysteresis and a lag time for growth recovery. This transition is caused by the accumulation of intermediate complexes, leading to the jamming of… ▽ More A simple cell model consisting of a catalytic reaction network with intermediate complex formation is numerically studied. As nutrients are depleted, the transition from the exponential growth phase to the growth-arrested dormant phase occurs along with hysteresis and a lag time for growth recovery. This transition is caused by the accumulation of intermediate complexes, leading to the jamming of reactions and the diversification of components. These properties are generic in random reaction networks, as supported by dynamical systems analyses of corresponding mean-field models. △ Less

Submitted 9 April, 2023; originally announced April 2023.

Comments: 6+6 pages, 3+6 figures

Emergence of economic and social disparities through competitive gift-giving

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: Several tiers of social organization with varying economic and social disparities have been observed. However, a quantitative characterization of the types and the causal mechanisms for the transitions have hardly been explained. While anthropologists have emphasized that gift exchange, rather than market exchange, prevails in traditional societies and shapes social relations, few mathematical stu… ▽ More Several tiers of social organization with varying economic and social disparities have been observed. However, a quantitative characterization of the types and the causal mechanisms for the transitions have hardly been explained. While anthropologists have emphasized that gift exchange, rather than market exchange, prevails in traditional societies and shapes social relations, few mathematical studies have explored its consequences for social organizations. In this study, we present a simple model of competitive gift-giving that describes how gifts bring goods to the recipient and honor to the donor, and simulate social change. Numerical simulations and an analysis of the corresponding mean-field theory demonstrate the transitions between the following four phases with different distribution shapes of wealth and social reputation: the band, without economic or social disparities; the tribe, with economic but without social disparities; the chiefdom, with both; and the kingdom, with economic disparity and weak social disparity except for an outlier, namely, the ``monarch''. The emergence of strong disparities is characterized by power law distributions and is attributed to the ``rich get richer'' process. In contrast, the absence of such a process leads to exponential distributions due to random fluctuations. The phases depend on the parameters characterizing the frequency and scale of gift interactions. Our findings provide quantitative criteria for classifying social organizations based on economic and social disparities, consistent with anthropological theory and empirical observations. Thus, we propose empirically measurable explanatory variables and characteristics for the evolution of social organizations. The constructive model, guided by social scientific theory, can provide the basic mechanistic explanation of social evolution and integrate theories of the social sciences. △ Less

Submitted 1 July, 2024; v1 submitted 15 March, 2023; originally announced March 2023.

Comments: 17 pages, 6 figures

Transition of Social Organisations Driven by Gift Relationship

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: Anthropologists have observed gift relationships that establish social relations as well as the transference of goods in many human societies. The totality of such social relations constitutes the network. Social scientists have analysed different types of social organisations with their characteristic networks. However, the factors and mechanisms that cause the transition between these types have… ▽ More Anthropologists have observed gift relationships that establish social relations as well as the transference of goods in many human societies. The totality of such social relations constitutes the network. Social scientists have analysed different types of social organisations with their characteristic networks. However, the factors and mechanisms that cause the transition between these types have hardly been explained. Here, we focus on the gift as the driving force for such changes. We build the model by idealising gift interactions and simulating the consequent social change due to long-term massive interactions. We demonstrate the emergence of disparities and various social organisations depending on the frequency of the gift, consistent with the empirical data. The constructive simulation study, as presented here, explains how people's interactions shape various social structures in response to environmental conditions. Combined with empirical studies, this could contribute to the formulation of a general theory in the social sciences. △ Less

Submitted 8 June, 2022; v1 submitted 23 May, 2022; originally announced May 2022.

Exploitation by asymmetry of information reference in coevolutionary learning in prisoner's dilemma game

Authors: Yuma Fujimoto, Kunihiko Kaneko

Abstract: Mutual relationships, such as cooperation and exploitation, are the basis of human and other biological societies. The foundations of these relationships are rooted in the decision making of individuals, and whether they choose to be selfish or altruistic. How individuals choose their behaviors can be analyzed using a strategy optimization process in the framework of game theory. Previous studies… ▽ More Mutual relationships, such as cooperation and exploitation, are the basis of human and other biological societies. The foundations of these relationships are rooted in the decision making of individuals, and whether they choose to be selfish or altruistic. How individuals choose their behaviors can be analyzed using a strategy optimization process in the framework of game theory. Previous studies have shown that reference to individuals' previous actions plays an important role in their choice of strategies and establishment of social relationships. A fundamental question remains as to whether an individual with more information can exploit another who has less information when learning the choice of strategies. Here we demonstrate that a player using a memory-one strategy, who can refer to their own previous action and that of their opponent, can be exploited by a reactive player, who only has the information of the other player, based on mutual adaptive learning. This is counterintuitive because the former has more choice in strategies and can potentially obtain a higher payoff. We demonstrated this by formulating the learning process of strategy choices to optimize the payoffs in terms of coupled replicator dynamics and applying it to the prisoner's dilemma game. Further, we show that the player using a memory-one strategy, by referring to their previous experience, can sometimes act more generous toward the opponent's defection, thereby accepting the opponent's exploitation. Mainly, we found that through adaptive learning, a player with limited information usually exploits the player with more information, leading to asymmetric exploitation. △ Less

Submitted 28 September, 2021; originally announced September 2021.

Comments: 20pages, 6(mainmanuscript)+3(supplement)figures

Dynamical-systems theory of cellular reprogramming

Authors: Yuuki Matsushita, Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

Abstract: In cellular reprogramming, almost all epigenetic memories of differentiated cells are erased by the overexpression of few genes, regaining pluripotency, potentiality for differentiation. Considering the interplay between oscillatory gene expression and slower epigenetic modifications, such reprogramming is perceived as an unintuitive, global attraction to the unstable manifold of a saddle, which r… ▽ More In cellular reprogramming, almost all epigenetic memories of differentiated cells are erased by the overexpression of few genes, regaining pluripotency, potentiality for differentiation. Considering the interplay between oscillatory gene expression and slower epigenetic modifications, such reprogramming is perceived as an unintuitive, global attraction to the unstable manifold of a saddle, which represents pluripotency. The universality of this scheme is confirmed by the repressilator model, and by gene regulatory networks randomly generated and those extracted from embryonic stem cells. △ Less

Submitted 13 September, 2021; v1 submitted 10 September, 2021; originally announced September 2021.

Comments: 15 pages, 12 figures

Error Catastrophe Can Be Avoided by Proofreading Innate to Template-Directed Polymerization

Authors: Yoshiya J. Matsubara, Nobuto Takeuchi, Kunihiko Kaneko

Abstract: An important issue for the origins of life is ensuring the accurate maintenance of information in replicating polymers in the face of inevitable errors. Here, we investigated how this maintenance depends on reaction kinetics by incorporating the elementary steps of polymerization into the population dynamics of polymers. We found that template-directed polymerization entails an inherent error-corr… ▽ More An important issue for the origins of life is ensuring the accurate maintenance of information in replicating polymers in the face of inevitable errors. Here, we investigated how this maintenance depends on reaction kinetics by incorporating the elementary steps of polymerization into the population dynamics of polymers. We found that template-directed polymerization entails an inherent error-correction mechanism akin to kinetic proofreading, generating long polymers that are more tolerant to an error catastrophe. Because this mechanism does not require enzymes, it is likely to operate under broad prebiotic conditions. △ Less

Submitted 10 May, 2022; v1 submitted 23 August, 2021; originally announced August 2021.

Comments: 15 pages, 13 figures

Mid-infrared dispersion relations in InP based photonic crystal slabs revealed by Fourier-transform angle-resolved reflection spectroscopy

Authors: Siti Chalimah, Yuanzhao Yao, Naoki Ikeda, Kei Kaneko, Rei Hashimoto, Tsutomu Kakuno, Shinji Saito, Takashi Kuroda, Yoshimasa Sugimoto, Kazuaki Sakoda

Abstract: Photonic crystals (PCs) offer unique ways to control light-matter interactions. The measurement of dispersion relations is a fundamental prerequisite if we are to create novel functionalities in PC devices. Angle-resolved spectroscopic techniques are commonly used for characterizing PCs that work in the visible and near-infrared regions. However, the techniques cannot be applied to the mid- and lo… ▽ More Photonic crystals (PCs) offer unique ways to control light-matter interactions. The measurement of dispersion relations is a fundamental prerequisite if we are to create novel functionalities in PC devices. Angle-resolved spectroscopic techniques are commonly used for characterizing PCs that work in the visible and near-infrared regions. However, the techniques cannot be applied to the mid- and long-wavelength infrared regions due to the limited sensitivity of infrared detectors. Here, we propose an alternative approach to measuring infrared dispersion relations. We construct a high-precision angle-resolved setup compatible with a Fourier-transform spectrometer with an angle resolution as high as 0.3 degrees. Hence, the reflection spectra are mapped to the 2D photonic band structures of In(Ga,Al)As/InP based PC slabs, which are designed as mid-infrared PC surface-emitting lasers. We identify complex PC modes with the aid of polarization selection rules derived by the group theory. Spectral analysis makes it possible to evaluate the mode quality (Q) factors. Therefore, angle-resolved reflection is a useful way of optimizing 2D PC parameters for mid-infrared devices. △ Less

Submitted 3 June, 2021; originally announced June 2021.

Comments: 7 pages, 7 figures

Journal ref: Phys. Rev. Applied 15, 064076 (2021), open access

Emergence of Kinship Structures and Descent Systems: Multi-level Evolutionary Simulation and Empirical Data Analysis

Authors: Kenji Itao, Kunihiko kaneko

Abstract: In many indigenous societies, people are categorised into several cultural groups, or clans, within which they believe to share ancestors. Clan attributions provide certain rules for marriage and descent. Such rules between clans constitute kinship structures. Anthropologists have revealed several kinship structures. Here, we propose an agent-based model of indigenous societies to reveal the evolu… ▽ More In many indigenous societies, people are categorised into several cultural groups, or clans, within which they believe to share ancestors. Clan attributions provide certain rules for marriage and descent. Such rules between clans constitute kinship structures. Anthropologists have revealed several kinship structures. Here, we propose an agent-based model of indigenous societies to reveal the evolution of kinship structures. In the model, several societies compete. Societies themselves comprise multiple families with parameters for cultural traits and mate preferences. These values determine with whom each family cooperates and competes and are transmitted to a new generation with mutation. The growth rate of each family is determined by the number of cooperators and competitors. Through this multi-level evolution, family traits and preferences diverge to form clusters that can be regarded as clans. Subsequently, kinship structures emerge, including dual organisation and generalised or restricted exchange, as well as patrilineal, matrilineal, and double descent systems. These structures emerge depending on the necessity of cooperation and the strength of mating competition. Their dependence is also estimated analytically. Finally, statistical analysis using the Standard Cross-Cultural Sample, a global ethnographic database, empirically verified theoretical results. Such collaboration between theoretical and empirical approaches will unveil universal features in anthropology. △ Less

Submitted 5 December, 2021; v1 submitted 17 May, 2021; originally announced May 2021.

Comments: 11 pages, 5 figures

A Linear Reciprocal Relationship Between Robustness and Plasticity in Homeostatic Biological Networks

Authors: Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

Abstract: In physics of living systems, a search for relationships of a few macroscopic variables that emerge from many microscopic elements is a central issue. We evolved gene regulatory networks so that the expression of target genes (partial system) is insensitive to environmental changes. Then, we found the expression levels of the remaining genes autonomously increase as a plastic response. Negative pr… ▽ More In physics of living systems, a search for relationships of a few macroscopic variables that emerge from many microscopic elements is a central issue. We evolved gene regulatory networks so that the expression of target genes (partial system) is insensitive to environmental changes. Then, we found the expression levels of the remaining genes autonomously increase as a plastic response. Negative proportionality was observed between the average changes in target and remnant genes, reflecting reciprocity between the macroscopic robustness of homeostatic genes and plasticity of regulator genes. This reciprocity follows the lever principle, which was satisfied throughout the evolutionary course, imposing an evolutionary constraint. △ Less

Submitted 15 December, 2020; v1 submitted 8 December, 2020; originally announced December 2020.

Comments: 5 pages, 4 figures

Entangled gene regulatory networks with cooperative expression endow robust adaptive responses to unforeseen environmental changes

Authors: Masayo Inoue, Kunihiko Kaneko

Abstract: Living organisms must respond to environmental changes. Generally, accurate and rapid responses are provided by simple, unidirectional networks that connect inputs with outputs. Besides accuracy and speed, biological responses should also be robust to environmental or intracellular noise and mutations. Furthermore, cells must also respond to unforeseen environmental changes that have not previousl… ▽ More Living organisms must respond to environmental changes. Generally, accurate and rapid responses are provided by simple, unidirectional networks that connect inputs with outputs. Besides accuracy and speed, biological responses should also be robust to environmental or intracellular noise and mutations. Furthermore, cells must also respond to unforeseen environmental changes that have not previously been experienced, to avoid extinction prior to the evolutionary rewiring of their networks, which takes numerous generations. We have investigated gene regulatory networks that mutually activate or inhibit, and have demonstrated that complex entangled networks can make appropriate input-output relationships that satisfy the robust and adaptive responses required for unforeseen challenges. Such entangled networks function for sloppy and unreliable responses with low Hill coefficient reactions for the expression of each gene. To compensate for such sloppiness, several detours in the regulatory network exist. By taking advantage of the averaging over such detours, the network shows a higher robustness to environmental and intracellular noise as well as to mutations in the network, when compared to simple unidirectional circuits. Furthermore, the appropriate response to unforeseen challenges, allowing for functional outputs, is achieved as many genes exhibit similar dynamic expression responses, irrespective of inputs, as confirmed by applying dynamic time warping and dynamic mode decomposition. As complex entangled networks are common in gene regulatory networks and global gene expression responses are observed in microbial experiments, the present results provide a novel design principle for cellular networks. △ Less

Submitted 8 December, 2020; originally announced December 2020.

Comments: 10 pages, 7 figures

Journal ref: Phys. Rev. Research 3, 033183 (2021)

Evolution of family systems and resultant socio-economic structures

Authors: Kenji Itao, Kunihiko Kaneko

Abstract: Families form the basis of society, and anthropologists have characterised various family systems. This study developed a multi-level evolutionary model of pre-industrial agricultural societies to simulate the evolution of family systems and determine how each of them adapts to environmental conditions and forms a characteristic socio-economic structure. In the model, competing societies evolve, w… ▽ More Families form the basis of society, and anthropologists have characterised various family systems. This study developed a multi-level evolutionary model of pre-industrial agricultural societies to simulate the evolution of family systems and determine how each of them adapts to environmental conditions and forms a characteristic socio-economic structure. In the model, competing societies evolve, which themselves comprise multiple evolving families that grow through family labour. Each family has two strategy parameters: the time children leave the parental home and the distribution of inheritance among siblings. The evolution of these parameters demonstrates that four basic family systems emerge; families can become either nuclear or extended, and have either an equal or unequal inheritance distribution. Nuclear families emerge where land resources are sufficient, whereas extended families emerge where land resources are limited. Equal inheritance emerges where the amount of wealth required for a family to survive is large, whereas unequal inheritance emerges where the required wealth is small. Analyses on the wealth distribution of families demonstrate a higher level of poverty in extended families, and that the accumulation of wealth is accelerated for unequal inheritance. By comparing wealth distributions in the model with historical data, family systems are associated with characteristic economic structures and modern social ideologies. Empirical data analyses using the cross-cultural ethnographic database verify the theoretical relationship between the environmental conditions, family systems, and socio-economic structures. Theoretical studies by this simple constructive model, as presented here, will integrate the understandings of family systems in evolutionary anthropology, demography, and socioeconomic histories. △ Less

Submitted 1 October, 2021; v1 submitted 23 September, 2020; originally announced September 2020.

Comments: 8 pages, 7 figures

Multiple-timescale Neural Networks: Generation of Context-dependent Sequences and Inference through Autonomous Bifurcations

Authors: Tomoki Kurikawa, Kunihiko Kaneko

Abstract: Sequential transitions between metastable states are ubiquitously observed in the neural system and underlie various cognitive functions. Although a number of studies with asymmetric Hebbian connectivity have investigated how such sequences are generated, the focused sequences are simple Markov ones. On the other hand, supervised machine learning methods can generate complex non-Markov sequences,… ▽ More Sequential transitions between metastable states are ubiquitously observed in the neural system and underlie various cognitive functions. Although a number of studies with asymmetric Hebbian connectivity have investigated how such sequences are generated, the focused sequences are simple Markov ones. On the other hand, supervised machine learning methods can generate complex non-Markov sequences, but these sequences are vulnerable against perturbations. Further, concatenation of newly learned sequence to the already learned one is difficult due to catastrophe forgetting, although concatenation is essential for cognitive functions such as inference. How stable complex sequences are generated still remains unclear. We have developed a neural network with fast and slow dynamics, which are inspired by the experiments. The slow dynamics store history of inputs and outputs and affect the fast dynamics depending on the stored history. We show the learning rule that requires only local information can form the network generating the complex and robust sequences in the fast dynamics. The slow dynamics work as bifurcation parameters for the fast one, wherein they stabilize the next pattern of the sequence before the current pattern is destabilized. This co-existence period leads to the stable transition between the current and the next pattern in the sequence. We further find that timescale balance is critical to this period. Our study provides a novel mechanism generating the robust complex sequences with multiple timescales in neural dynamics. Considering the multiple timescales are widely observed, the mechanism advances our understanding of temporal processing in the neural system. △ Less

Submitted 1 March, 2021; v1 submitted 6 June, 2020; originally announced June 2020.

A scaling law of multilevel evolution: how the balance between within- and among-collective evolution is determined

Authors: Nobuto Takeuchi, Namiko Mitarai, Kunihiko Kaneko

Abstract: Numerous living systems are hierarchically organised, whereby replicating components are grouped into reproducing collectives -- e.g., organelles are grouped into cells, and cells are grouped into multicellular organisms. In such systems, evolution can operate at two levels: evolution among collectives, which tends to promote selfless cooperation among components within collectives (called altruis… ▽ More Numerous living systems are hierarchically organised, whereby replicating components are grouped into reproducing collectives -- e.g., organelles are grouped into cells, and cells are grouped into multicellular organisms. In such systems, evolution can operate at two levels: evolution among collectives, which tends to promote selfless cooperation among components within collectives (called altruism), and evolution within collectives, which tends to promote cheating among components within collectives. The balance between within- and among-collective evolution thus exerts profound impacts on the fitness of these systems. Here, we investigate how this balance depends on the size of a collective (denoted by $N$) and the mutation rate of components ($m$) through mathematical analyses and computer simulations of multiple population genetics models. We first confirm a previous result that increasing $N$ or $m$ accelerates within-collective evolution relative to among-collective evolution, thus promoting the evolution of cheating. Moreover, we show that when within- and among-collective evolution exactly balance each other out, the following scaling relation generally holds: $Nm^α$ is a constant, where scaling exponent $α$ depends on multiple parameters, such as the strength of selection and whether altruism is a binary or quantitative trait. This relation indicates that although $N$ and $m$ have quantitatively distinct impacts on the balance between within- and among-collective evolution, their impacts become identical if $m$ is scaled with a proper exponent. Our results thus provide a novel insight into conditions under which cheating or altruism evolves in hierarchically-organised replicating systems. △ Less

Submitted 15 October, 2021; v1 submitted 9 May, 2020; originally announced May 2020.

Comments: Accepted in Genetics after a minor revision. Revised based on referee reports. Added results on a binary-trait model. Conclusions do not change

Journal ref: Genetics, Volume 220, Issue 2, February 2022, iyab182

Dimensional reduction in evolving spin-glass model: correlation of phenotypic responses to environmental and mutational changes

Authors: Ayaka Sakata, Kunihiko Kaneko

Abstract: The evolution of high-dimensional phenotypes is investigated using a statistical physics model consists of interacting spins, in which genotypes, phenotypes, and environments are represented by spin configurations, interaction matrices, and external fields, respectively. We found that phenotypic changes upon diverse environmental change and genetic variation are highly correlated across all spins,… ▽ More The evolution of high-dimensional phenotypes is investigated using a statistical physics model consists of interacting spins, in which genotypes, phenotypes, and environments are represented by spin configurations, interaction matrices, and external fields, respectively. We found that phenotypic changes upon diverse environmental change and genetic variation are highly correlated across all spins, consistent with recent experimental observations of biological systems. The dimension reduction in phenotypic changes is shown to be a result of the evolution of the robustness to thermal noise, achieved at the replica symmetric phase. △ Less

Submitted 1 May, 2020; v1 submitted 11 January, 2020; originally announced January 2020.

Comments: 5 pages, 3 figures

Homeorhesis in Waddington's Landscape by Epigenetic Feedback Regulation

Authors: Yuuki Matsushita, Kunihiko Kaneko

Abstract: In multicellular organisms, cells differentiate into several distinct types during early development. Determination of each cellular state, along with the ratio of each cell type, as well as the developmental course during cell differentiation are highly regulated processes that are robust to noise and environmental perturbations throughout development. Waddington metaphorically depicted this robu… ▽ More In multicellular organisms, cells differentiate into several distinct types during early development. Determination of each cellular state, along with the ratio of each cell type, as well as the developmental course during cell differentiation are highly regulated processes that are robust to noise and environmental perturbations throughout development. Waddington metaphorically depicted this robustness as the epigenetic landscape in which the robustness of each cellular state is represented by each valley in the landscape. This robustness is now conceptualized as an approach toward an attractor in a gene-expression dynamical system. However, there is still an incomplete understanding of the origin of landscape change, which is accompanied by branching of valleys that corresponds to the differentiation process. Recent progress in developmental biology has unveiled the molecular processes involved in epigenetic modification, which will be a key to understanding the nature of slow landscape change. Nevertheless, the contribution of the interplay between gene expression and epigenetic modification to robust landscape changes, known as homeorhesis, remains elusive. Here, we introduce a theoretical model that combines epigenetic modification with gene expression dynamics driven by a regulatory network. In this model, epigenetic modification changes the feasibility of expression, i.e., the threshold for expression dynamics, and a slow positive-feedback process from expression to the threshold level is introduced. Under such epigenetic feedback, several fixed-point attractors with distinct expression patterns are generated hierarchically shaping the epigenetic landscape with successive branching of valleys. This theory provides a quantitative framework for explaining homeorhesis in development as postulated by Waddington, based on dynamical-system theory with slow feedback reinforcement. △ Less

Submitted 27 December, 2019; originally announced December 2019.

Comments: 10 pages, 7 figures

Journal ref: Phys. Rev. Research 2, 023083 (2020)

Wideband 67-116 GHz receiver development for ALMA Band 2

Authors: P. Yagoubov, T. Mroczkowski, V. Belitsky, D. Cuadrado-Calle, F. Cuttaia, G. A. Fuller, J. -D. Gallego, A. Gonzalez, K. Kaneko, P. Mena, R. Molina, R. Nesti, V. Tapia, F. Villa, M. Beltran, F. Cavaliere, J. Ceru, G. E. Chesmore, K. Coughlin, C. De Breuck, M. Fredrixon, D. George, H. Gibson, J. Golec, A. Josaitis , et al. (21 additional authors not shown)

Abstract: ALMA has been operating since 2011, but has not yet been populated with the full suite of intended frequency bands. In particular, ALMA Band 2 (67-90 GHz) is the final band in the original ALMA band definition to be approved for production. We aim to produce a wideband, tuneable, sideband-separating receiver with 28 GHz of instantaneous bandwidth per polarisation operating in the sky frequency ran… ▽ More ALMA has been operating since 2011, but has not yet been populated with the full suite of intended frequency bands. In particular, ALMA Band 2 (67-90 GHz) is the final band in the original ALMA band definition to be approved for production. We aim to produce a wideband, tuneable, sideband-separating receiver with 28 GHz of instantaneous bandwidth per polarisation operating in the sky frequency range 67-116 GHz. Our design anticipates new ALMA requirements following the recommendations in the 2030 ALMA Development Roadmap. The cryogenic cartridge is designed to be compatible with the ALMA Band 2 cartridge slot, where the coldest components -- the feedhorns, orthomode transducers, and cryogenic low noise amplifiers -- operate at a temperature of 15 K. We use multiple simulation methods and tools to optimise our designs for both the passive optics and the active components. The cryogenic cartridge interfaces with a room temperature cartridge hosting the local oscillator (LO) and the downconverter module. This warm cartridge is largely based on GaAs semiconductor technology and is optimised to match the cryogenic receiver bandwidth with the required instantaneous LO tuning range. Our collaboration has designed, fabricated, and tested multiple technical solutions for each of the components, producing a state-of-the-art receiver covering the full ALMA Band 2 & 3 atmospheric window. The receiver is suitable for deployment on ALMA in the coming years, and is capable of dual-polarisation, sideband-separating observations in intermediate frequency bands spanning 4-18 GHz, for a total of 28 GHz on-sky bandwidth per polarisation channel. We conclude that the 67-116 GHz wideband implementation for ALMA Band 2 is now feasible, and this receiver is a compelling instrumental upgrade that will enhance observational capabilities and scientific reach. △ Less

Submitted 20 February, 2020; v1 submitted 20 December, 2019; originally announced December 2019.

Comments: 23 pages, accepted for publication in A&A on 20 Dec 2019. This version corrects the affiliations of 2 co-authors

Journal ref: A&A 634, A46 (2020)

Water-resistant carbon nanotube based strain sensor for monitoring structural integrity

Authors: Preety Ahuja, Shingo Akiyama, Sanjeev Kumar Ujjain, Radovan Kukobat, Fernando Vallejos-Burgos, Ryusuke Futamura, Takuya Hayashi, Mutsumi Kimura, David Tomanek, Katsumi Kaneko

Abstract: Monitoring structural integrity during and after extreme events such as an earthquake or a tsunami is a mundane yet important task that still awaits a workable solution. Currently available stress sensors are not sufficiently robust and are affected by humidity. Insufficient information about crack formation preceding structural failure increases risk during rescue operations significantly. Design… ▽ More Monitoring structural integrity during and after extreme events such as an earthquake or a tsunami is a mundane yet important task that still awaits a workable solution. Currently available stress sensors are not sufficiently robust and are affected by humidity. Insufficient information about crack formation preceding structural failure increases risk during rescue operations significantly. Designing durable stress sensors that are not affected by harsh and changing environment and do not fail under catastrophic conditions is a fundamental challenge. To address this problem, we developed a stress sensor based on creased single-walled carbon nanotubes (SWCNTs) encapsulated in a non-fluorinated superhydrophobic coating. The creased SWCNT film was fabricated and integrated in polydimethylsiloxane (PDMS) to provide a highly linear response under elastic deformation. The non-fluorinated water-repellent coating was fabricated by spray-coating the film with nanosilica particles, providing water resistance during elastic deformation. The compact design and superior water resistance of the sensor, along with its appealing linearity and large stretchability, demonstrates the scalability of this approach for fabricating efficient strain sensors for applications in infrastructure and robotic safety management as well as advanced wearable sensors. △ Less

Submitted 30 August, 2019; originally announced September 2019.

Journal ref: J. Mater. Chem. A 7, 19996-20005 (2019)

Experimental Study of a Planar-integrated Dual-Polarization Balanced SIS Mixer

Authors: Wenlei Shan, Shohei Ezaki, Keiko Kaneko, Akihira Miyachi, Takafumi Kojima, Yoshinori Uzawa

Abstract: A dual-polarization balanced superconductor-insulator-superconductor mixer operating at 2 mm wavelength is realized in form of a monolithic planar integrated circuit. Planar orthomode transducers and LO couplers are enabled by using silicon membranes that are locally formed on the silicon-on-insulator substrate. The performance of the balanced mixer is experimentally investigated. Over the entire… ▽ More A dual-polarization balanced superconductor-insulator-superconductor mixer operating at 2 mm wavelength is realized in form of a monolithic planar integrated circuit. Planar orthomode transducers and LO couplers are enabled by using silicon membranes that are locally formed on the silicon-on-insulator substrate. The performance of the balanced mixer is experimentally investigated. Over the entire RF band (125-163 GHz), the balanced mixer shows an LO noise rejection ratio about 15 dB, an overall receiver noise about 40 K, and a cross-polarization <-20 dB. The demonstrated compactness and the performance of the integrated circuit indicate that this approach is feasible in developing heterodyne focal plane arrays. △ Less

Submitted 18 August, 2019; originally announced August 2019.

Comments: Accepted for publication in IEEE Transactions on Terahertz Science and Technology

Emergence of Exploitation as Symmetry Breaking in Iterated Prisoner's Dilemma

Authors: Yuma Fujimoto, Kunihiko Kaneko

Abstract: In society, mutual cooperation, defection, and asymmetric exploitative relationships are common. Whereas cooperation and defection are studied extensively in the literature on game theory, asymmetric exploitative relationships between players are little explored. In a recent study, Press and Dyson demonstrate that if only one player can learn about the other, asymmetric exploitation is achieved in… ▽ More In society, mutual cooperation, defection, and asymmetric exploitative relationships are common. Whereas cooperation and defection are studied extensively in the literature on game theory, asymmetric exploitative relationships between players are little explored. In a recent study, Press and Dyson demonstrate that if only one player can learn about the other, asymmetric exploitation is achieved in the prisoner's dilemma game. In contrast, however, it is unknown whether such one-way exploitation is stably established when both players learn about each other symmetrically and try to optimize their payoffs. Here, we first formulate a dynamical system that describes the change in a player's probabilistic strategy with reinforcement learning to obtain greater payoffs, based on the recognition of the other player. By applying this formulation to the standard prisoner's dilemma game, we numerically and analytically demonstrate that an exploitative relationship can be achieved despite symmetric strategy dynamics and symmetric rule of games. This exploitative relationship is stable, even though the exploited player, who receives a lower payoff than the exploiting player, has optimized the own strategy. Whether the final equilibrium state is mutual cooperation, defection, or exploitation, crucially depends on the initial conditions: Punishment against a defector oscillates between the players, and thus a complicated basin structure to the final equilibrium appears. In other words, slight differences in the initial state may lead to drastic changes in the final state. Considering the generality of the result, this study provides a new perspective on the origin of exploitation in society. △ Less

Submitted 16 May, 2019; originally announced May 2019.

Comments: 19 pages, 7 figures, + supplement(8 pages, 2 figures)

Journal ref: Phys. Rev. Research 1, 033077 (2019)

Horizontal transfer between loose compartments stabilizes replication of fragmented ribozymes

Authors: Atsushi Kamimura, Yoshiya J. Matsubara, Kunihiko Kaneko, Nobuto Takeuchi

Abstract: The emergence of replicases that can replicate themselves is a central issue in the origin of life. Recent experiments suggest that such replicases can be realized if an RNA polymerase ribozyme is divided into fragments short enough to be replicable by the ribozyme and if these fragments self-assemble into a functional ribozyme. However, the continued self-replication of such replicases requires t… ▽ More The emergence of replicases that can replicate themselves is a central issue in the origin of life. Recent experiments suggest that such replicases can be realized if an RNA polymerase ribozyme is divided into fragments short enough to be replicable by the ribozyme and if these fragments self-assemble into a functional ribozyme. However, the continued self-replication of such replicases requires that the production of every essential fragment be balanced and sustained. Here, we use mathematical modeling to investigate whether and under what conditions fragmented replicases achieve continued self-replication. We first show that under a simple batch condition, the replicases fail to display continued self-replication owing to positive feedback inherent in these replicases. This positive feedback inevitably biases replication toward a subset of fragments, so that the replicases eventually fail to sustain the production of all essential fragments. We then show that this inherent instability can be resolved by small rates of random content exchange between loose compartments (i.e., horizontal transfer). In this case, the balanced production of all fragments is achieved through negative frequency-dependent selection operating in the population dynamics of compartments. This selection mechanism arises from an interaction mediated by horizontal transfer between intracellular and intercellular symmetry breaking. The horizontal transfer also ensures the presence of all essential fragments in each compartment, sustaining self-replication. Taken together, our results underline compartmentalization and horizontal transfer in the origin of the first self-replicating replicases. △ Less

Submitted 20 January, 2019; originally announced January 2019.

Comments: 14 pages, 4 figures, and supplemental material

The advantage of leakage of essential metabolites and resultant symbiosis of diverse species

Authors: Jumpei F Yamagishi, Nen Saito, Kunihiko Kaneko

Abstract: Microbial communities display extreme diversity. A variety of strains or species coexist even when limited by a single resource. It has been argued that metabolite secretion creates new niches and facilitates such diversity. Nonetheless, it is still a controversial topic why cells secrete even essential metabolites so often; in fact, even under isolation conditions, microbial cells secrete various… ▽ More Microbial communities display extreme diversity. A variety of strains or species coexist even when limited by a single resource. It has been argued that metabolite secretion creates new niches and facilitates such diversity. Nonetheless, it is still a controversial topic why cells secrete even essential metabolites so often; in fact, even under isolation conditions, microbial cells secrete various metabolites, including those essential for their growth. First, we demonstrate that leaking essential metabolites can be advantageous. If the intracellular chemical reactions include multibody reactions like catalytic reactions, this advantageous leakage of essential metabolites is possible and indeed typical for most metabolic networks via "flux control" and "growth-dilution" mechanisms; the later is a result of the balance between synthesis and growth-induced dilution with autocatalytic reactions. Counterintuitively, the mechanisms can work even when the supplied resource is scarce. Next, when such cells are crowded, the presence of another cell type, which consumes the leaked chemicals is beneficial for both cell types, so that their coexistence enhances the growth of both. The latter part of the paper is devoted to the analysis of such unusual form of symbiosis: "consumer" cell types benefit from the uptake of metabolites secreted by "leaker" cell types, and such consumption reduces the concentration of metabolites accumulated in the environment; this environmental change enables further secretion from the leaker cell types. This situation leads to frequency-dependent coexistence of several cell types, as supported by extensive simulations. A new look at the diversity in a microbial ecosystem is thus presented. △ Less

Submitted 4 March, 2019; v1 submitted 25 November, 2018; originally announced November 2018.

Comments: 9 pages, 4 figures

Journal ref: Phys. Rev. Lett. 124, 048101 (2020)

Functional Dynamics by Intention Recognition in Iterated Games

Authors: Yuma Fujimoto, Kunihiko Kaneko

Abstract: Intention recognition is an important characteristic of intelligent agents. In their interactions with others, they try to read others' intentions and make an image of others to choose their actions accordingly. While the way in which players choose their actions depending on such intentions has been investigated in game theory, how dynamic changes in intentions by mutually reading others' intenti… ▽ More Intention recognition is an important characteristic of intelligent agents. In their interactions with others, they try to read others' intentions and make an image of others to choose their actions accordingly. While the way in which players choose their actions depending on such intentions has been investigated in game theory, how dynamic changes in intentions by mutually reading others' intentions are incorporated into game theory has not been explored. We present a novel formulation of game theory in which players read others' intentions and change their own through an iterated game. Here, intention is given as a function of the other's action and the own action to be taken accordingly as the dependent variable, while the mutual recognition of intention is represented as the functional dynamics. It is shown that a player suffers no disadvantage when he/she recognizes the other's intention, whereas the functional dynamics reach equilibria in which both players' intentions are optimized. These cover a classical Nash and Stackelberg equilibria but we extend them in this study: Novel equilibria exist depending on the degree of mutual recognition. Moreover, the degree to which each player recognizes the other can also differ. This formulation is applied to resource competition, duopoly, and prisoner's dilemma games. For example, in the resource competition game with player-dependent capacity on gaining the resource, the superior player's recognition leads to the exploitation of the other, while the inferior player's recognition leads to cooperation through which both players' payoffs increase. △ Less

Submitted 26 September, 2018; originally announced October 2018.

Comments: 20 pages, 6 figures, and supplementary material

Statistical Evolutionary Laws in Music Styles

Authors: Eita Nakamura, Kunihiko Kaneko

Abstract: If a cultural feature is transmitted over generations and exposed to stochastic selection when spreading in a population, its evolution may be governed by statistical laws and be partly predictable, as in the case of genetic evolution. Music exhibits steady changes of styles over time, with new characteristics developing from traditions. Recent studies have found trends in the evolution of music s… ▽ More If a cultural feature is transmitted over generations and exposed to stochastic selection when spreading in a population, its evolution may be governed by statistical laws and be partly predictable, as in the case of genetic evolution. Music exhibits steady changes of styles over time, with new characteristics developing from traditions. Recent studies have found trends in the evolution of music styles, but little is known about their relations to the evolution theory. Here we analyze Western classical music data and find statistical evolutionary laws. For example, distributions of the frequencies of some rare musical events (e.g. dissonant intervals) exhibit steady increase in the mean and standard deviation as well as constancy of their ratio. We then study an evolutionary model where creators learn their data-generation models from past data and generate new data that will be socially selected by evaluators according to the content dissimilarity (novelty) and style conformity (typicality) with respect to the past data. The model reproduces the observed statistical laws and can make non-trivial predictions for the evolution of independent musical features. In addition, the same model with different parameterization can predict the evolution of Japanese enka music, which is developed in a different society and has a qualitatively different tendency of evolution. Our results suggest that the evolution of musical styles can partly be explained and predicted by the evolutionary model incorporating statistical learning, which can be important for other cultures and future music technologies. △ Less

Submitted 5 November, 2019; v1 submitted 16 September, 2018; originally announced September 2018.

Comments: 21 pages, 4 figures, with supplemental material. Minor revisions

Journal ref: Sci. Rep. 9, 15993 (2019)

Transition in relaxation paths in allosteric molecules: enzymatic kinetically constrained model

Authors: Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

Abstract: A hierarchy of timescales is ubiquitous in biological systems, where enzymatic reactions play an important role because they can hasten the relaxation to equilibrium. We introduced a statistical physics model of interacting spins that also incorporates enzymatic reactions to extend the classic model for allosteric regulation. Through Monte Carlo simulations, we found that the relaxation dynamics a… ▽ More A hierarchy of timescales is ubiquitous in biological systems, where enzymatic reactions play an important role because they can hasten the relaxation to equilibrium. We introduced a statistical physics model of interacting spins that also incorporates enzymatic reactions to extend the classic model for allosteric regulation. Through Monte Carlo simulations, we found that the relaxation dynamics are much slower than the elementary reactions and are logarithmic in time with several plateaus, as is commonly observed for glasses. This is because of the kinetic constraints from the cooperativity via the competition for an enzyme, which has different affinity for molecules with different structures. Our model showed symmetry breaking in the relaxation trajectories that led to inherently kinetic transitions without any correspondence to the equilibrium state. In this paper, we discuss the relevance of these results for diverse responses in biology. △ Less

Submitted 19 June, 2019; v1 submitted 15 August, 2018; originally announced August 2018.

Comments: 23 pages, 13 figures

Journal ref: Phys. Rev. Research 2, 012005 (2020)

Epigenetic Ratchet: Spontaneous Adaptation via Stochastic Gene Expression

Authors: Yusuke Himeoka, Kunihiko Kaneko

Abstract: Adaptation mechanism of cells on the basis of stochastic gene expression and epigenetic modification is proposed. From marginally stable states generated by epigenetic modification, a gene expression pattern that achieves greater cell growth is selected, as confirmed by simulations and analysis of several models. The mechanism does not require any design of gene regulation networks and is shown to… ▽ More Adaptation mechanism of cells on the basis of stochastic gene expression and epigenetic modification is proposed. From marginally stable states generated by epigenetic modification, a gene expression pattern that achieves greater cell growth is selected, as confirmed by simulations and analysis of several models. The mechanism does not require any design of gene regulation networks and is shown to be generic in a stochastic system with marginal stability. General relevance of the mechanism to cell biology is also discussed. △ Less

Submitted 17 January, 2019; v1 submitted 25 July, 2018; originally announced July 2018.

Comments: 5 pages, 2 figures, and supplemental document

Cooperative reliable response from sloppy gene-expression dynamics

Authors: Masayo Inoue, Kunihiko Kaneko

Abstract: Gene expression dynamics satisfying given input-output relationships were investigated by evolving the networks for an optimal response. We found three types of networks and corresponding dynamics, depending on the sensitivity of gene expression dynamics: direct response with straight paths, amplified response by a feed-forward network, and cooperative response with a complex network. When the sen… ▽ More Gene expression dynamics satisfying given input-output relationships were investigated by evolving the networks for an optimal response. We found three types of networks and corresponding dynamics, depending on the sensitivity of gene expression dynamics: direct response with straight paths, amplified response by a feed-forward network, and cooperative response with a complex network. When the sensitivity of each gene's response is low and expression dynamics is sloppy, the last type is selected, in which many genes respond collectively to inputs, with local-excitation and global-inhibition structures. The result provides an insight into how a reliable response is achieved with unreliable units, and on why complex networks with many genes are adopted in cells. △ Less

Submitted 3 June, 2018; originally announced June 2018.

Kinetic Selection of Template Polymer with Complex Sequences

Authors: Yoshiya J. Matsubara, Kunihiko Kaneko

Abstract: Emergence and maintenance of polymers with complex sequences is a major question in the study of origins of life. To answer this, we studied a model polymerization reaction, where polymers are synthesized by stepwise ligation from two types of monomers, catalyzed by a long polymer as a template. Direct stochastic simulation and dynamical systems analysis revealed that the most dominant polymer seq… ▽ More Emergence and maintenance of polymers with complex sequences is a major question in the study of origins of life. To answer this, we studied a model polymerization reaction, where polymers are synthesized by stepwise ligation from two types of monomers, catalyzed by a long polymer as a template. Direct stochastic simulation and dynamical systems analysis revealed that the most dominant polymer sequence in a population successively changes against the flow rate of monomer to the system. The slower the flow, the more is the complex sequence selected. We discuss the relevance of this kinetic selection of sequence by the non-equilibrium flow rate to the origin of complex polymers. △ Less

Submitted 11 September, 2018; v1 submitted 29 March, 2018; originally announced March 2018.

Comments: 12 pages, 12 figures

Journal ref: Phys. Rev. Lett. 121, 118101 (2018)

Exponential growth for self-reproduction in a catalytic reaction network: relevance of a minority molecular species and crowdedness

Authors: Atsushi Kamimura, Kunihiko Kaneko

Abstract: Explanation of exponential growth in self-reproduction is an important step toward elucidation of the origins of life because optimization of the growth potential across rounds of selection is necessary for Darwinian evolution. To produce another copy with approximately the same composition, the exponential growth rates for all components have to be equal. How such balanced growth is achieved, how… ▽ More Explanation of exponential growth in self-reproduction is an important step toward elucidation of the origins of life because optimization of the growth potential across rounds of selection is necessary for Darwinian evolution. To produce another copy with approximately the same composition, the exponential growth rates for all components have to be equal. How such balanced growth is achieved, however, is not a trivial question, because this kind of growth requires orchestrated replication of the components in stochastic and nonlinear catalytic reactions. By considering a mutually catalyzing reaction in two- and three-dimensional lattices, as represented by a cellular automaton model, we show that self-reproduction with exponential growth is possible only when the replication and degradation of one molecular species is much slower than those of the others, i.e., when there is a minority molecule. Here, the synergetic effect of molecular discreteness and crowding is necessary to produce the exponential growth. Otherwise, the growth curves show superexponential growth because of nonlinearity of the catalytic reactions or subexponential growth due to replication inhibition by overcrowding of molecules. Our study emphasizes that the minority molecular species in a catalytic reaction network is necessary to acquire evolvability at the primitive stage of life. △ Less

Submitted 24 November, 2017; originally announced November 2017.

Comments: 19 pages, submitted for publication

Stronger selection can slow down evolution driven by recombination on a smooth fitness landscape

Authors: Masahiko Ueda, Nobuto Takeuchi, Kunihiko Kaneko

Abstract: Stronger selection implies faster evolution---that is, the greater the force, the faster the change. This apparently self-evident proposition, however, is derived under the assumption that genetic variation within a population is primarily supplied by mutation (i.e.\ mutation-driven evolution). Here, we show that this proposition does not actually hold for recombination-driven evolution, i.e.\ evo… ▽ More Stronger selection implies faster evolution---that is, the greater the force, the faster the change. This apparently self-evident proposition, however, is derived under the assumption that genetic variation within a population is primarily supplied by mutation (i.e.\ mutation-driven evolution). Here, we show that this proposition does not actually hold for recombination-driven evolution, i.e.\ evolution in which genetic variation is primarily created by recombination rather than mutation. By numerically investigating population genetics models of recombination, migration and selection, we demonstrate that stronger selection can slow down evolution on a perfectly smooth fitness landscape. Through simple analytical calculation, this apparently counter-intuitive result is shown to stem from two opposing effects of natural selection on the rate of evolution. On the one hand, natural selection tends to increase the rate of evolution by increasing the fixation probability of fitter genotypes. On the other hand, natural selection tends to decrease the rate of evolution by decreasing the chance of recombination between immigrants and resident individuals. As a consequence of these opposing effects, there is a finite selection pressure maximizing the rate of evolution. Hence, stronger selection can imply slower evolution if genetic variation is primarily supplied by recombination. △ Less

Submitted 3 August, 2017; v1 submitted 8 March, 2017; originally announced March 2017.

Comments: 12 pages, 2 figures

Journal ref: PLoS ONE 12(8): e0183120 (2017)

Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

Authors: Yuma Fujimoto, Takahiro Sagawa, Kunihiko Kaneko

Abstract: The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games.… ▽ More The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here, the reward received by one group increases with the population, as does the collected cost. In spite of this, we find that there exists an optimal group size that maximizes its payoff. Furthermore, when the population asymmetry between two groups is large, a smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, which leads to the resolution of the prisoner's dilemma between the groups. The relevance of the HPG game to policy selection in society and the optimal size in human or animal groups are discussed accordingly. △ Less

Submitted 19 September, 2016; originally announced September 2016.

Comments: 27 pages, 10 figures