The similarity of life across the universe

Is the hypothesis correct that if life exists elsewhere in the universe, it would have forms and structures unlike anything we could imagine? From the subatomic level in cellular energy acquisition to the assembly and even behavior of organisms at the scale of populations, life on Earth exhibits characteristics that suggest it is a universal norm for life at all levels of hierarchy. These patterns emerge from physical and biochemical limitations. Their potentially universal nature is supported by recent data on the astrophysical abundance and availability of carbon compounds and water. Within these constraints, biochemical and biological variation is certainly possible, but it is limited. If life exists elsewhere, life on Earth, rather than being a contingent product of one specific experiment in biological evolution, is likely to reflect common patterns for the assembly of living matter.     

The uniqueness of biological self-organization: challenging the Darwinian paradigm

Here we discuss the challenge posed by self-organization to the Darwinian conception of evolution. As we point out, natural selection can only be the major creative agency in evolution if all or most of the adaptive complexity manifest in living organisms is built up over many generations by the cumulative selection of naturally occurring small, random mutations or variants, i.e., additive, incremental steps over an extended period of time. Biological self-organization—witnessed classically in the folding of a protein, or in the formation of the cell membrane—is a fundamentally different means of generating complexity. We agree that self-organizing systems may be fine-tuned by selection and that self-organization may be therefore considered a complementary mechanism to natural selection as a causal agency in the evolution of life. But we argue that if self-organization proves to be a common mechanism for the generation of adaptive order from the molecular to the organismic level, then this will greatly undermine the Darwinian claim that natural selection is the major creative agency in evolution. We also point out that although complex self-organizing systems are easy to create in the electronic realm of cellular automata, to date translating in silico simulations into real material structures that self-organize into complex forms from local interactions between their constituents has not proved easy. This suggests that self-organizing systems analogous to those utilized by biological systems are at least rare and may indeed represent, as pre-Darwinists believed, a unique ascending hierarchy of natural forms. Such a unique adaptive hierarchy would pose another major challenge to the current Darwinian view of evolution, as it would mean the basic forms of life are necessary features of the order of nature and that the major pathways of evolution are determined by physical law, or more specifically by the self-organizing properties of biomatter, rather than natural selection.     

A hierarchical classification of first-order recurrent neural networks

We provide a decidable hierarchical classification of first-order recurrent neural networks made up of McCulloch and Pitts cells. This classification is achieved by proving an equivalence result between such neural networks and deterministic Büuchi automata, and then translating the Wadge classification theory from the abstract machine to the neural network context. The obtained hierarchy of neural networks is proved to have width 2 and height omega + 1, and a decidability procedure of this hierarchy is provided. Notably, this classification is shown to be intimately related to the attractive properties of the considered networks.     

Guest-Editorial Introduction: Converging Evolutionary Patterns in Life and Culture

The natural world demonstrates signs of spatial–temporal order, an order that appears to us through a series of recognizable, recurring and consecutive patterns, i.e. regularities in forms, functions, behaviors, events and processes. These patterns lend insight into the modes and tempos of evolution and thus into the units, levels, and mechanisms that underlie the evolutionary hierarchy. Contributors to this special issue analyze converging patterns in the biological and sociocultural realm across and beyond classic divisions between micro- and macro-evolution; horizontal/reticulate and vertical evolution; phylogeny, ontogeny and ecology; synchronic and diachronic sociocultural and linguistic research; and tree and network diagrams. Explanations are sought in complexity theory, major transitions of evolution, and process and mechanism approaches to change; and consequences for notions such as “life”, “species”, “biological individuality”, “units” and “levels” of evolution are given.     

Three puzzles in hierarchical evolution

The maximum degree of hierarchical structure of organisms hasrisen over the history of life, notably in three transitions:the origin of the eukaryotic cell from symbiotic associationsof prokaryotes; the emergence of the first multicellular individualsfrom clones of eukaryotic cells; and the origin of the firstindividuated colonies from associations of multicellular organisms.The trend is obvious in the fossil record, but documenting itusing a high-resolution hierarchy scale reveals three puzzles:1) the rate of origin of new levels accelerates, at least untilthe early Phanerozoic; 2) after that, the trend may slow oreven stop; and 3) levels may sometimes arise out of order. Thethree puzzles and their implications are discussed; a possibleexplanation is offered for the first.     

A case for spiking neural network simulation based on configurable multiple-FPGA systems

Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.     

Cross-cultural Comparison of Learning in Human Hunting

This paper is a cross-cultural examination of the development of hunting skills and the implications for the debate on the role of learning in the evolution of human life history patterns. While life history theory has proven to be a powerful tool for understanding the evolution of the human life course, other schools, such as cultural transmission and social learning theory, also provide theoretical insights. These disparate theories are reviewed, and alternative and exclusive predictions are identified. This study of cross-cultural regularities in how children learn hunting skills, based on the ethnographic literature on traditional hunters, complements existing empirical work and highlights future areas for investigation.     

Molecular paleontology and complexity in the last eukaryotic common ancestor

Abstract

Eukaryogenesis, the origin of the eukaryotic cell, represents one of the fundamental evolutionary transitions in the history of life on earth. This event, which is estimated to have occurred over one billion years ago, remains rather poorly understood. While some well-validated examples of fossil microbial eukaryotes for this time frame have been described, these can provide only basic morphology and the molecular machinery present in these organisms has remained unknown. Complete and partial genomic information has begun to fill this gap, and is being used to trace proteins and cellular traits to their roots and to provide unprecedented levels of resolution of structures, metabolic pathways and capabilities of organisms at these earliest points within the eukaryotic lineage. This is essentially allowing a molecular paleontology. What has emerged from these studies is spectacular cellular complexity prior to expansion of the eukaryotic lineages. Multiple reconstructed cellular systems indicate a very sophisticated biology, which by implication arose following the initial eukaryogenesis event but prior to eukaryotic radiation and provides a challenge in terms of explaining how these early eukaryotes arose and in understanding how they lived. Here, we provide brief overviews of several cellular systems and the major emerging conclusions, together with predictions for subsequent directions in evolution leading to extant taxa. We also consider what these reconstructions suggest about the life styles and capabilities of these earliest eukaryotes and the period of evolution between the radiation of eukaryotes and the eukaryogenesis event itself.     

Using deep neural networks to model similarity between visual patterns: Application to fish sexual signals

The evolution of visual patterns is a frontier in the theory of sexual selection as we seek to understand the function of complex visual patterning in courtship. Recently, the sensory drive and sensory bias models of sexual selection have been applied to higher-level visual processing. One prediction of this application is that animals' sexual signals will mimic the visual statistics of their habitats. An enduring difficulty of testing predictions of visual pattern evolution is in developing quantitative methods for comparing patterns. Advances in artificial neural networks address this challenge by allowing for the direct comparison of images using both simple and complex features. Here, we use VGG19, an industry‑leading image classification network to test predictions of sensory drive, by comparing visual patterns in darter fish (Etheostoma spp.) to images of their habitats. We find that images of female darters are significantly more similar to images of their habitat than are images of males, supporting a role of camouflage in female patterning. We do not find direct evidence for sensory drive shaping the design of male patterns; however, this work demonstrates the utility of network methods for pattern analysis and suggests future directions for visual pattern research.     

NADPH oxidase: an enzyme for multicellularity?

Multicellularity has evolved several times during the evolution of eukaryotes. One evolutionary pressure that permits multicellularity relates to the division of work, where one group of cells functions as nutrient providers and the other in specialized roles such as defence or reproduction. This requires signalling systems to ensure harmonious development of multicellular structures. Here, we show that NADPH oxidases are specifically present in organisms that differentiate multicellular structures during their life cycle and are absent from unicellular life forms. The biochemical properties of these enzymes make them ideal candidates for a role in intercellular signalling.     

Are ant supercolonies crucibles of a new major transition in evolution?

The biological hierarchy of genes, cells, organisms and societies is a fundamental reality in the living world. This hierarchy of entities did not arise ex nihilo at the origin of life, but rather has been serially generated by a succession of critical events known as ‘evolutionary transitions in individuality’ (ETIs). Given the sequential nature of ETIs, it is natural to look for candidates to form the next hierarchical tier. We analyse claims that these candidates are found among ‘supercolonies’, ant populations in which discrete nests cooperate as part of a wider collective, in ways redolent of cells in a multicellular organism. Examining earlier empirical work and new data within the recently proposed ‘Darwinian space’ framework, we offer a novel analysis of the evolutionary status of supercolonies and show how certain key conditions might be satisfied in any future process transforming these collaborative networks into true Darwinian individuals.     

Neural networks in higher levels of abstraction

 Existing artificial neural network models are not very successful in understanding or generating natural language texts. Therefore it is proposed to design novel neural network structures in higher levels of abstraction. This concept leads to a hierarchy of network layers which extract and store local details in every layer and transfer the remaining nonlocal context information to higher levels. At the same time data compression is provided from layer to layer. The use of the same network elements (meta-words) in higher levels for different word series in the basis level is introduced and discussed for grammatical identity or similarity. Thus text can be compressed to forms which are almost free of redundancy. Possible applications are storage, transmission, understanding, generating and translation of texts. Received: 6 May 1993 / Accepted in revised form: 24 July 1996     

Boundary lines in symbiosis forms

Symbiosis can take different forms (parasitism, mutualism, commensalism, etc.) but boundaries between different types of symbiotic interactions are not well defined. The kinds of symbiotic associations between organisms cannot however be restricted to isolated and distinct categories. These associations are part of a broad continuum in which it is difficult to know where one type of association ends and another begins. Moreover, different scientists use the same term to mean different things or different terms to mean the same thing. This can obscure what is biologically important and what is not. This communication proposes a new classification scheme, which simply and comprehensively illustrates relationships between the various kinds of associations. The scheme illustrates relationships clearly and highlights the continuum between types of associations. It further indicates where modifications to the scheme are possible over time. The classification of the association between two organisms can be reduced to two factors: 1) the impact incurred by the host (benefit or damage) and 2) the relative duration of the association (RDA), i.e. the ratio of the duration of the association to the life expectancy of the symbiont. The conceptual figure provides concrete examples and illustrates some relationships that can change during different life stages. This figure should help teachers and students in the understanding of symbiosis, and could be a starting point for future discussions in the continuously developing research fields studying ecological and evolutionary implications of symbiotic relationships.     

植物生活史型定量划分及其权重配置方法——以四棱豆生活史型划分为例

植物生活史型定量划分方法研究是植物生活史型研究的重要内容。现有的生活史型定量划分方法是基于主成分分析法(PCA)建立起来的,未考虑性状指标之间的相互影响,因此需要探索适用于"网状"结构指标体系的植物生活史型划分新方法。根据植物生活史型划分指标的层次性特点,以攀援型和矮生型四棱豆(Psophocarpus tetragonolobus)为例,分别采用主成分分析法(PCA)、层次分析法(AHP)和网络层次分析法(ANP)对性状指标进行权重配置,计算性状指标的综合得分和生活史型划分参数,结果如下:与ANP相比,PCA计算的V型(营养生长型)参数值偏低(x在0.39以下),S型(有性生殖型)参数值偏高(z在0.453以上);AHP计算的V型参数值偏高(x在0.614以上),S型参数值偏低(z在0.088以下);3种方法计算的生活史型划分参数差异明显。由于PCA、AHP均要求性状指标之间相互独立,不能排除性状指标之间的关联,因此基于PCA、AHP的四棱豆生活史型划分结果均出现了偏差,表明性状指标之间的相关性影响了生活史型划分结果。ANP的指标体系为"网状"结构,其控制层、网络层各个指标之间均存在关联。构建ANP的判断矩阵时提取了性状指标的相关矩阵信息,权重配置反映了性状指标之间的相关关系。基于ANP方法对攀援型和矮生型四棱豆生活史型的划分结果分别为V0.517C0.327S0.156和V0.416C0.43S0.154。当性状指标之间的相关不显著时,可采用PCA和AHP法分配权重;当性状指标之间存在显著相关时,采用ANP法进行权重配置更为恰当。综上所述,基于ANP的植物生活史型划分方法解决了性状指标之间相互影响问题,为植物生活史型定量研究提供了新的有效方法。     

Evolutionary optimization and neural network models of behavior

One of the main challenges to the adaptionist program in general and the use of optimization models in behavioral and evolutionary ecology, in particular, is that organisms are so constrained' by ontogeny and phylogeny that they may not be able to attain optimal solutions, however those are defined. This paper responds to the challenge through the comparison of optimality and neural network models for the behavior of an individual polychaete worm. The evolutionary optimization model is used to compute behaviors (movement in and out of a tube) that maximize a measure of Darwinian fitness based on individual survival and reproduction. The neural network involves motor, sensory, energetic reserve and clock neuronal groups. Ontogeny of the neural network is the change of connections of a single individual in response to its experiences in the environment. Evolution of the neural network is the natural selection of initial values of connections between groups and learning rules for changing connections. Taken together, these can be viewed as design parameters. The best neural networks have fitnesses between 85% and 99% of the fitness of the evolutionary optimization model. More complicated models for polychaete worms are discussed. Formulation of a neural network model for host acceptance decisions by tephritid fruit flies leads to predictions about the neurobiology of the flies. The general conclusion is that neural networks appear to be sufficiently rich and plastic that even weak evolution of design parameters may be sufficient for organisms to achieve behaviors that give fitnesses close to the evolutionary optimal fitness, particularly if the behaviors are relatively simple.     

The ascidian mouth opening is derived from the anterior neuropore: Reassessing the mouth/neural tube relationship in chordate evolution

The relative positions of the brain and mouth are of central importance for models of chordate evolution. The dorsal hollow neural tube and the mouth have often been thought of as developmentally distinct structures that may have followed independent evolutionary paths. In most chordates however, including vertebrates and ascidians, the mouth primordia have been shown to fate to the anterior neural boundary. In ascidians such as Ciona there is a particularly intimate relationship between brain and mouth development, with a thin canal connecting the neural tube lumen to the mouth primordium at larval stages. This so-called neurohypophyseal canal was previously thought to be a secondary connection that formed relatively late, after the independent formation of the mouth primordium and the neural tube. Here we show that the Ciona neurohypophyseal canal is present from the end of neurulation and represents the anteriormost neural tube, and that the future mouth opening is actually derived from the anterior neuropore. The mouth thus forms at the anterior midline transition between neural tube and surface ectoderm. In the vertebrate Xenopus, we find that although the mouth primordium is not topologically continuous with the neural tube lumen, it nonetheless forms at this same transition point. This close association between the mouth primordium and the anterior neural tube in both ascidians and amphibians suggests that the evolution of these two structures may be more closely linked than previously appreciated.     

Did primitive microorganisms use nonhem iron proteins in place of NAD/P?

Nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP) are of universal occurrence in living organisms and play a central role in coupling oxidative with reductive reactions. However, the evidence that the origin and early evolution of life occurred at high temperatures (>95°C) is now strong, and at these temperatures some modern metabolites, including both the reduced and oxidized forms of these coenzymes, are unstable. We believe there is good evidence that indicates that in the most primitive organisms nonhem iron proteins carried out many or all of the functions of NAD/P(H). This has important implications for the way in which investigations of archaebacterial metabolism are conducted.Abbreviations NAD/P(H)a Oxidised and reduced forms of nicotinamide adenine dinucleotide and nicotinamide adenine dinucleotide phosphate     

Viruses, definitions and reality

Viruses are known to be abundant, ubiquitous, and to play a very important role in the health and evolution of life organisms. However, most biologists have considered them as entities separate from the realm of life and acting merely as mechanical artifacts that can exchange genes between different organisms. This article reviews some definitions of life organisms to determine if viruses adjust to them, and additionally, considers new discoveries to challenge the present definition of viruses. Definitions of life organisms have been revised in order to validate how viruses fit into them. Viral factories are discussed since these mini-organelles are a good example of the complexity of viral infection, not as a mechanical usurpation of cell structures, but as a driving force leading to the reorganization and modification of cell structures by viral and cell enzymes. New discoveries such as the Mimivirus, its virophage and viruses that produce filamentous tails when outside of their host cell, have stimulated the scientific community to analyze the current definition of viruses. One way to be free for innovation is to learn from life, without rigid mental structures or tied to the past, in order to understand in an integrated view the new discoveries that will be unfolded in future research. Life processes must be looked from the complexity and trans-disciplinarity perspective that includes and accepts the temporality of the active processes of life organisms, their interdependency and interrelation among them and their environment. New insights must be found to redefine life organisms, especially viruses, which still are defined using the same concepts and knowledge of the fifties.     

The evolutionary origin of the vertebrate neural crest and its developmental gene regulatory network – insights from amphioxus

The neural crest is an embryonic cell population unique to vertebrates. During vertebrate embryogenesis, neural crest cells are first induced from the neural plate border; subsequently, they delaminate from the dorsal neural tube and migrate to their destination, where they differentiate into a wide variety of derivatives. The emergence of the neural crest is thought to be responsible for the evolution of many complex novel structures of vertebrates that are lacking in invertebrate chordates. Despite its central importance in understanding the origin of vertebrates, the evolutionary origin of the neural crest remains elusive. The basal chordate amphioxus (Branchiostoma floridae) occupies an outgroup position that is useful for investigating this question. In this review, I summarize recent genomic and comparative developmental studies between amphioxus and vertebrates and discuss their implications for the evolutionary origin of neural crest cells. I focus mainly on the origin of the gene regulatory network underlying neural crest development, and suggest several hypotheses regarding how this network could have been assembled during early vertebrate evolution.