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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

1. Systems Physiology and Psychology: Somatic and Behavioral Development

By a novel “developmental systems theory” approach, cited herein, the same complex dynamics found to self-organize cosmos and evolution seem to be in similar effect to guide an infant’s and child’s advance in bodily maturation, visual perception, kinetic agility, behavior and sequential stages of cognition.

Achim, Kaia and Detlev Arendt. Structural Evolution of Cell Types by Step-Wise Assembly of Cellular Modules. Current Opinion in Genetics & Development. 27/102, 2014. European Molecular Biology Laboratory developmental biologists contribute further evidence about how brain and bodies came to evolve, develop, and diversify by way of cellular and modular repetitions. In essence, deep, constant homologies from anatomies to genes are ascertained. See also Animal Evolution: The Hard Problem of Cartilage Origins by Thibaut Brunet and Arendt in Current Biology (26/14, 2016), along with The Genetic Program for Cartilage Development has Deep Homology Within Bilateria by Oscar Tarazona, et al in Nature (533/86, 2016).

Cell types are composed of cellular modules exerting specific subfunctions. The evolutionary emergence and diversification of these modules can be tracked through the comparative analysis of genomes. Here, we survey recent advances elucidating the origin of neurons, of smooth and striated muscle cells and of the T- and B-cells of the immune system in the diverging lineages of animal evolution. Gene presence and absence analyses in various metazoan genomes allow mapping the step-wise assembly of key modules – such as the postsynaptic density characteristic for neurons or the z-disk characteristic for striated muscle – on the animal evolutionary tree. Using this approach, first insight into the structural evolution of cell types can be gained. (2014 Abstract)

Our skeletons evolved from cartilaginous tissue, but it remains a mystery how cartilage itself first arose in evolution. Characterization of cartilage in cuttlefish and horseshoe crabs reveals surprising commonalities with chordate chondrocytes, suggesting a common evolutionary origin. (2016 Abstract)

Bashan, Amir, et al. Network Physiology Reveals Relations between Network Topology and Physiological Function. Nature Communications. 3/702, 2011. A team of Bashan and Shlomo Havlin, Bar-Ilan University, Israel, Jan Kantelhardt, Martin Luther University, Germany, and Ronny Bartsch and Plamen Ivanov, Harvard Medical School, who also cite the Bulgarian Academy of Sciences, contribute to 21st century realizations that bodily organismic functions, rather than a homeostasis, is actually a non-equilibrium dynamic intricacy of complex network systems. This Systems Soma section tries to document an historic revision and advance, which are here seen to have much promise for health and medicine.

The human organism is an integrated network where complex physiological systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here we develop a framework to probe interactions among diverse systems, and we identify a physiological network. We find that each physiological state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiological states, the network undergoes topological transitions associated with fast reorganization of physiological interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology. (Abstract)

This system-wide integrative approach to individual systems and the network of their interactions may facilitate the emergence of a new dimension to the field of systems physiology that will include not only interactions within but also across physiological systems. In relation to critical clinical care, where multiple organ failure is often the reason for fatal outcome, our framework may have practical utility in assessing whether dynamical links between physiological systems remain substantially altered even when the function of specific systems is restored after treatment. While we demonstrate one specific application, the framework we develop can be applied to a broad range of complex systems where the TDS method can serve as a tool to characterize and understand the dynamics and function of real-world heterogeneous and interdependent networks. The established relationship between dynamical network topology and network function has not only significant medical and clinical implications, but is also of relevance for the general theory of complex networks. (7)

Bergman, Lars, et al, eds. Developmental Science and the Holistic Approach. Mahwah, NJ: Erlbaum, 2000. Many contributions from an integral and dynamic perspective on the formation of vision, personality, and behavior.

Boyer, Denis, et al. Non-Random Walks in Monkeys and Humans. Journal of the Royal Society Interface. 9/842, 2011. Universidad Nacional Autónoma de México, Princeton University, and VaccinApe, Bethesda, MD, researchers find, just as in every other stage and instance, nature’s common dynamical mathematics similarly guides the gracile kinectics of prosimian, hominid, and homo sapiens steps and journeys.

Principles of self-organization play an increasingly central role in models of human activity. Notably, individual human displacements exhibit strongly recurrent patterns that are characterized by scaling laws and can be mechanistically modelled as self-attracting walks. Recurrence is not, however, unique to human displacements. Here we report that the mobility patterns of wild capuchin monkeys are not random walks, and they exhibit recurrence properties similar to those of cell phone users, suggesting spatial cognition mechanisms shared with humans. We also show that the highly uneven visitation patterns within monkey home ranges are not entirely self-generated but are forced by spatio-temporal habitat heterogeneities. If models of human mobility are to become useful tools for predictive purposes, they will need to consider the interaction between memory and environmental heterogeneities. (Abstract)

Bulf, Hermann, et al. Infants Learn Better from Left to Right. Nature Scientific Reports. 7/2437, 2017. University of Milano-Bicocca and Université Paris Descartes cognitive psychologists quantify an innate propensity of babies to visually scan from left to right, which is attributed to an early favoring of the integral right hemisphere. See also Number-Space Mapping in the Newborn Chick Resembles Humans’ Mental Number Line by Rosa Rugani, et al in Science (347/534, 2015) which reports the same proclivity, re second quote.

These early directional cues might shape the direction of infants’ spatial representation of order depending on the dominant direction of their cultural environment. Alternatively, the emergence of a left-to-right spatial organization of ordered dimensions during the first months of life might be rooted in biologically-determined neural constraints in the human brain. Indeed, the right hemisphere is dominant in visuo-spatial task, and it has recently been proposed that early temporal asymmetries in hemispheric maturation, with a temporal advantage for the right over the left hemisphere, may determine a leftward asymmetrical exploration of visual space that would constrain the structure of infant’s representational space. The possibility of a link between a right hemispheric dominance and a left-to-right representation of ordinal information is also suggested by studies with non-human animals. (Bulf 4)

Humans represent numbers along a mental number line (MNL), where smaller values are located on the left and larger on the right. The origin of the MNL and its connections with cultural experience are unclear: Pre-verbal infants and nonhuman species master a variety of numerical abilities, supporting the existence of evolutionary ancient precursor systems. In our experiments, 3-day-old domestic chicks, once familiarized with a target number (5), spontaneously associated a smaller number (2) with the left space and a larger number (8) with the right space. The same number (8), though, was associated with the left space when the target number was 20. Similarly to humans, chicks associate smaller numbers with the left space and larger numbers with the right space. (Rugani Abstract)

Cairns, Robert. The Making of Development Psychology. Richard Lerner, ed. Handbook of Child Psychology, Volume 1. New York: Wiley, 1998. A century-long history of the field of developmental psychology it grew from individual conjectures to humankind’s global collaborative endeavor.

In June 1994, a Nobel Foundation symposium comprised of noted biologists and psychologists called for an integrated unified framework for the study of development. No single source or single investigator can be credited, since it has become an interdisciplinary, international movement. (92)

Cangelosi, Angelo and Matthew Schlesinger. Developmental Robotics: From Babies to Robots. Cambridge: MIT Press, 2015. A Foreword by Linda Smith, cofounder with the late Esther Thelen of dynamical systems theory for infant and child maturation, sets the theme of the work. University of Plymouth, UK, and Southern Illinois University researchers draw upon such features of human learning as self-organization, enaction, multifaceted causes, intrinsic motivation, cognitive bootstrapping, and so on, to achieve similar robotic behaviors. The core concept is the recognition that children teach and guide themselves on a progressive individuation course. An effective robotic entity should be built with open programs capable of similar responses. Another theme is a parallel between self-ontogeny and evolutionary phylogeny. See also Developmental Process Emerges from Extended Brain-Body-Behavior Networks by Lisa Byrge, Olaf Sporns, and Linda Smith in Trends in Cognitive Sciences (18/8, 2014).

Developmental robotics is a collaborative and interdisciplinary approach to robotics that is directly inspired by the developmental principles and mechanisms observed in children's cognitive development. It builds on the idea that the robot, using a set of intrinsic developmental principles regulating the real-time interaction of its body, brain, and environment, can autonomously acquire an increasingly complex set of sensorimotor and mental capabilities. This volume, drawing on insights from psychology, computer science, linguistics, neuroscience, and robotics, offers the first comprehensive overview of a rapidly growing field.

Cao, Miao, et al. Developmental Connectomics from Infancy through Early Childhood. Trends in Neuroscience. 40/8, 2017. Connectome: a complete set of neural elements (neurons, brain regions, etc.) and their interconnections (synapses, fiber pathways, temporal correlations.) National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, and Department of Radiology, Children’s Hospital of Philadelphia researchers scope out a further apply of neural imaging studies such as the Human Connectome Project to this relevant neonate to child life stage. Two salient efforts are the Developing Human Connectome Project and the Baby Connectome Project (Google each). A main intent is to quantify an optimal global balance between information segregation and integration.

The human brain undergoes rapid growth in both structure and function from infancy through early childhood, and this significantly influences cognitive and behavioral development in later life. A newly emerging research framework, developmental connectomics, provides unprecedented opportunities for exploring the developing brain through non-invasive mapping of structural and functional connectivity patterns. Within this framework, we review recent neuroimaging and neurophysiological studies investigating connectome development from 20 postmenstrual weeks to 5 years of age. Specifically, we highlight five fundamental principles of brain network development during the critical first years of life, emphasizing strengthened segregation/integration balance, a remarkable hierarchical order from primary to higher-order regions, unparalleled structural and functional maturations, substantial individual variability, and high vulnerability to risk factors and developmental disorders. (Abstract)

Courage, Mary and Mark Howe. From Infant to Child: The Dynamics of Cognitive Change in the Second Year of Life. Psychological Bulletin. 128/2, 2002. A historical and current review of the field whose studies have ranged from the constructivism of Piaget to new nativism and modularity theories. In this transitional second year occurs self-awareness and the profusion of language.

For example, the development of behavior that appears to be discontinuous or disorderly at the performance level but which arises from underlying processes that are themselves continuous and orderly (e.g., an infant’s vocabulary acquisition or first steps) is consistent with the self-organizing properties that typify non-linear dynamic systems. (268)

Ellis, Bruce and David Bjorklund, eds. Origins of the Social Mind: Evolutionary Psychology and Child Development. New York: Guilford Press, 2005. An impressive volume in support of evolutionary development psychology, which blends Darwinism with epigenetic influences and complex developmental systems theory in the study of children’s behavioral and cognitive maturation. In this way both self-organization and selection can come into play.

Farris, Sarah. Evolution of Brain Elaboration. Philosophical Transactions of the Royal Society B. Vol.370/Iss.1684, 2015. In a special issue on the Origin and Evolution of the Nervous System, in these 2010s when scientific fields are reaching integral confirmations, a West Virginia University neurobiologist perceives life’s encephalization of neural anatomies as a developmental ramification from a common topology present in the earliest rudiments. See also Convergent Evolution of Complex Brains and High Intelligence by Gerhard Roth in this edition (Abstract below). Life’s emergent cerebration again appears to follow a prescribed, expansive trajectory, akin to an embryogeny, toward better cognizance of which such studies are its latest worldwide phase.

Large, complex brains have evolved independently in several lineages of protostomes and deuterostomes. Sensory centres in the brain increase in size and complexity in proportion to the importance of a particular sensory modality, yet often share circuit architecture because of constraints in processing sensory inputs. The selective pressures driving enlargement of higher, integrative brain centres has been more difficult to determine, and may differ across taxa. The capacity for flexible, innovative behaviours, including learning and memory and other cognitive abilities, is commonly observed in animals with large higher brain centres. Despite differences in the exact behaviours under selection, evolutionary increases in brain size tend to derive from common modifications in development and generate common architectural features, even when comparing widely divergent groups such as vertebrates and insects. These similarities may in part be influenced by the deep homology of the brains of all Bilateria, in which shared patterns of developmental gene expression give rise to positionally, and perhaps functionally, homologous domains. Other shared modifications of development appear to be the result of homoplasy, such as the repeated, independent expansion of neuroblast numbers through changes in genes regulating cell division. The common features of large brains in so many groups of animals suggest that given their common ancestry, a limited set of mechanisms exist for increasing structural and functional diversity, resulting in many instances of homoplasy in bilaterian nervous systems. (Farris Abstract)

Within the animal kingdom, complex brains and high intelligence have evolved several to many times independently, e.g. among ecdysozoans in some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g. cichlids), corvid and psittacid birds, and cetaceans, elephants and primates. High levels of intelligence are invariantly bound to multimodal centres such as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium in birds and the cerebral cortex in primates, all of which contain highly ordered associative neuronal networks. The driving forces for high intelligence may vary among the mentioned taxa, e.g. needs for spatial learning and foraging strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental learning in primates. (Roth Abstract)

Fitch, W. Tecumseh, et al. Social Cognition and the Evolution of Language. Neuron. 65/6, 2010. University of Vienna cognitive biologists argue that an expansion over the past decade of the domains and extent of cultural activities from primates across to mammalian and avian species reveals many “homologous and analogous similarities.” So once more nature is found to repeat and recapitulate, in stepwise fashion, the same native, cumulative edification.

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