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VII. WumanKinder: An EarthSphere Transition in Individuality

1. Systems Physiology and Psychology: Somatic and Behavioral Development

Gao, Helena Hong and John Holland. Agent-Based Models of Levels of Consciousness. Santa Fe Institute Working Papers. 08-12-047, 2008. As part of a SFI project on language complexities (search Beckner), a Nanyang Technological University developmental linguist and the University of Michigan founder of complex adaptive systems theory perceive a six stage, infant to child, process by which reflective awareness arises: Unconscious (instinctive) activity, Minimal, Stimulus-response, Simple recursive (ask for food when visible), Extended recursive (I’m hungry), and Self-consciousness. A tacit assumption would seem to be our individual recapitulations of how primates evolved stepwise unto knowing utterances.

This paper is based on recent interdisciplinary experimental studies that emphasize the steps in language acquisition during the first few years of life. These steps are characterized as changes in levels of consciousness. The object is to place successive levels of consciousness in a complex adaptive systems (CAS) framework, a framework that centers on learning agents that interact via exchanges of signals such as gestures and utterances. The CAS framework thus provides a strong emphasis on the social nature of language acquisition and evolution. The models described are exploratory, not predictive. As such, the models are meant to suggest new mechanisms and experiments that will increase our understanding of language. (Abstract)

Gershkoff-Stowe, Lisa and Esther Thelen. U-Shaped Changes in Behavior: A Dynamic Systems Perspective. Journal of Cognition and Development. 5/1, 2004. As everyone is familiar with, we learn things, then forget or regress, and later on become more accomplished. These child psychologist authors find this ubiquitous path can be conceived as a self-organizing complex system which constantly seeks a better organization from a multitude of interacting modular-like influences.

Gervain, Judit. The Role of Prenatal Experience in Language Development. Current Opinion in Behavioral Sciences. 21/62, 2018. This entry by a Laboratoire Psychologie de la Perception, CNRS, Paris linguist is able to report that our human proclivity for linguistic discourse is so strong it can be detected in fetal stages. An infant’s preference for holistic images can be traced back to receptions of rhythmic prosody even in the womb.

Human infants are born linguistic citizens of the world, possessing broad-based, universal perceptual and learning abilities that allow them to start learning any language. After several months of experience, their linguistic system becomes tuned to the sound patterns of their native language(s). Recent results on newborns’ speech perception abilities suggest that this classical view might need to be nuanced, as fetuses seem to learn more from their prenatal experience with speech than previously believed. This paper reviews the growing body of evidence suggesting that newborns are familiar with the prosody of the languages heard in utero, and discusses the implications of this ‘prenatal prosodic bootstrapping’ for subsequent language acquisition. (Abstract)

Ghalati, Pejman, et al. Critical Transitions in Intensive Care Units: A Sepsis Case Study. Nature Scientific Reports. 9/12888, 2019. We cite this contribution by a six person University of Aachen, Joint Research Center for Computational Biomedicine group as another example of how nonlinear physical phenomena can be found in forceful effect even in such physiological, and metabolic traumas. A novel ability to quantify these deep lineaments can then help predict and mitigate.

The progression of complex human diseases is associated with critical transitions across dynamical regimes, which often provide early-warning signals and insights into disease-driving mechanisms. In this paper, we propose a computational method based on surprise loss (SL) to discover data-driven indicators of such transitions in a multivariate time series dataset of septic shock and non-sepsis patient cohorts. The core idea of SL is to train a mathematical model on time series in an unsupervised fashion and to quantify the deterioration of the model’s forecast (out-of-sample) relative to its past (in-sample) performance. Our analysis revealed that critical transitions occurred at a median of over 35 hours before the onset of septic shock, which validates our method as an early-warning indicator. (Abstract excerpt)

Gottlieb, Gilbert, et al. The Significance of Biology for Human development: A Developmental Psychological Systems View. Lerner, Richard, vol. ed. Handbook of Child Psychology. 6th Edition. Vol. 1: Theoretical Models of Human Development. Hoboken, NJ: Wiley, 2006. An historic revision is underway from preformation to epigenesis, from determinism to “probabilistic” organism-environment interaction from fetus to adolescent that serve to self-organize and create a unique person. This life process is said to be, in essence, an equifinality reachable by a variety of pathways.

Grosberg, Anna, et al. Self-Organization of Muscle Cell Structure and Function. PloS Computational Biology. February 24, 2011. Harvard University, Wyss Institute, bioengineers provide sophisticated studies of one more instance of ubiquitous self-organized activities serving the growth and vitality of organismic life.

Muscle morphogenesis is a hierarchal, self-organizing process spanning from nanometer scale conformational changes in proteins to bundled fibers sometimes a meter in length. We reasoned that boundary constraints are a physical signal that is conserved over all of these length scales and spatially organizes this broad range of coupled structures.

The symmetry-breaking can arise from a static, external cue, such as a geometric feature in the boundary conditions imposed on the cell, or from a dynamic internal cue, such as a local overlapping of long fibers. The multiple time scales of these interacting events suggest a hierarchy of post-translational, self-organizational processes that are required for coupling cellular form and function.

Guidolin, Diego, et al. The “Self-Similarity Logic” Applied to the Development of the Vascular System. Developmental Biology. 351/156, 2011. University of Padova, Udine, and Bari medical morphologists here apply this mathematical insight originally posted in 2009 by neuroscientists Luigi Agnati, et al (search) to physiological purposes. We add in 2019 that the presence of such an innately universal repetition in kind has been found and robustly proven from human to universe.

From a structural standpoint, living systems exhibit a hierarchical pattern of organization that is nested within one another. Recently, it has been suggested that some auto similarity prevails at each level or developmental stage and a principle of “self-similarity logic” has been proposed to convey the concept of a multi-level organization in which similar rules (logic) serve at each level. This study suggests that such a principle is likewise apparent in many morphological and developmental aspects of the vascular system. In fact, not only the morphology of the vascular system exhibits a high degree of geometrical self-similarity, but its remodelling processes also seem to be characterized by almost the same rules. (Abstract excerpt)

Hartenstein, Volker and Angelika Stollewerk. The Evolution of Early Neurogenesis. Developmental Cell. 32/4, 2016. As our nascent cerebral humankinder reconstructs how we came to be ourselves, UCLA and Queen Mary University of London evo/devo neuroscientists provide a comparative overview of neural progenitors across the animal kingdom, along with neurogenetic mechanisms which form embryonic brains.

The foundation of the diverse metazoan nervous systems is laid by embryonic patterning mechanisms, involving the generation and movement of neural progenitors and their progeny. Here we divide early neurogenesis into discrete elements, including origin, pattern, proliferation, and movement of neuronal progenitors, which are controlled by conserved gene cassettes. We review these neurogenetic mechanisms in representatives of the different metazoan clades, with the goal to build a conceptual framework in which one can ask specific questions, such as which of these mechanisms potentially formed part of the developmental “toolkit” of the bilaterian ancestor and which evolved later. (Abstract)

Neurogenesis before the Rise of Bilaterian Animals: Cnidaria and Ctenophora are the first metazoan clades with neurons, even though the molecular machinery enabling a cell to sense external stimuli and generate/conduct electric impulses evolved much earlier in single-cell organisms. Accordingly, in the first multicellular animals that lacked a nervous system (e.g., sponges), one can detect different types of cells that already encapsulate many aspects of neurons. (394) During embryonic development, proneural genes and the Notch signaling pathway control the number and pattern of flask cells. This or related cell types could have given rise to the neurons that occurred in the common ancestor of bilaterians and cnidarians. (394)

Hollenstein, Tom. Twenty Years of Dynamic Systems Approaches to Development: Significant Contributions, Challenges, and Future Directions. Child Development Perspectives. 5/4, 2011. An Introduction to a special section on the subject whose articles by John Spencer, Alan Fogel, Paul van Geert, Marc Lewis, David Witherington, and other coauthors, with reference to Esther Thelen and Linda Smith, make this collection a valuable update survey of this nonlinear conceptual revolution for the field, in step with every other domain of universe and human. We offer quotes from select papers.

Recent decades have seen a shift in thinking about development. Instead of characterizing what changes over development, there is a new emphasis on the how of developmental change. The explorations have revealed that simple notions of cause and effect are inadequate to explain development. Rather, change occurs within complex systems with many components that interact over multiple time scales, from the second-to-second unfolding of behavior to the longer time scales of learning, development, and evolution. (Spencer, et al, 260) A central challenge on the horizon for dynamic systems theory is to formally integrate across reciprocally interacting levels from genetic to social and to integrate these levels across multiple time scales from in-the-moment interactions to learning to development. (Spencer, et al, 263)

As development is an example of a complex dynamic system (CDS), the theory of CDS can make important contributions to our understanding of the developmental process. However, mainstream research in developmental psychology uses an empirical paradigm that is at odds with what it is purported to explain, namely, that development is a complex dynamic process. Although the number of studies that focus on a process-oriented and dynamic approach of development is growing, this article argues that the field is in need of a theoretical and methodological paradigm shift. (van Geert, 273) The general idea is that if a system is complex in the sense that it consists of many interacting components, and it has sufficient longevity, it is also very likely that it has properties such as self-organization, emergence, and nonlinearity. (van Geert, 275)

My own view is that the limited progress of the DS paradigm may be forgiven in light of its lofty goals. Unlike other research programs in developmental psychology, the DS program construes itself as a metatheoretical framework destined to transform the entire field. Speaking as one of the converted, it is difficult for me to imagine any other way to conceptualize development except as the self-organization of increasing complex forms, such as schemas, skills, and emotional habits, through the recursive interactions of psychological components. (Lewis, 282) It seems that some of the most important challenges and opportunities for DS approaches to development lie in the fusion of developmental psychology with neuroscience. The human brain is the epitome of a self-organizing system. Fro example, systemically oriented theorists demonstrate that cognition, emotion, developmental change, and consciousness itself are products of patterns emerging at many scales in a self-organizing synaptic architecture. (Lewis, 283)

Howe, Mark and Marc Lewis, eds. Development as Self-organization. Developmental Review. 25/3-4, 2005. A double issue on the importance of dynamic system approaches to fully understand somatic, cerebral and cognitive/social childhood maturation.

Hu, Kun, et al. Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions. PLoS One. 7/11, 2012. We include this paper here by a Harvard Medical School, Leiden University Medical Centre, Netherlands, and Oregon Health & Science University team who have also been engaged in a similar studies of dynamic physiologies. See Pittman-Polletta, Benjamin, et al, below, who is also coauthor, for more reports.

The mammalian central circadian pacemaker (suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of 24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. (Abstract)

In mammals, many physiological and behavioral variables, including heart rate and motor activity, exhibit temporal structures that are similar across widely different time scales, i.e. ‘‘fractal’’ or ‘‘scale-invariant’’ patterns. Fractal patterns of heart rate and motor activity levels are intrinsic system characteristics that are independent of environmental and behavioral stimuli. These fractal controls appear to impart health advantages, including system integrity and adaptability. For instance, fractal cardiac and activity controls are reduced with aging and under pathological conditions, and the degree of reduction in fractal cardiac control can be predictive of survival. (1)

Physiological significances of fractal patterns Many physiological processes and neural dynamics exhibit fractal regulation generating complex fluctuations that display similar, strong correlations across a wide range of time scales. Based on theoretical models in physics, it has been hypothesized that fractal correlations indicate the existence of a system at, or near, a ‘‘critical state.” Theoretically, a system under such a critical state, perched between different stable states, is optimally prepared to respond to intrinsic/extrinsic influences by orchestrating subunits within the system in a coherent manner. This hypothesis is appealing because it bestows upon the fractal phenomenon a physiological meaning related to system integrity and adaptability. (5)

Hunt, Nathaniel, et al. The Influence of Auditory-Motor Coupling on Fractal Dynamics in Human Gait. Nature Scientific Reports. 4/5879, 2014. University of Nebraska, and University College Dublin, biophysicists add novel perceptions that our bodily physiology and daily activity can indeed be described by and functions according to archetypal complex dynamics. As others have noted (search Havlin) these discoveries provide a guide to a person’s health which can be equated with how well one is attuned to critical rhythms between order and chaos.

Fractal patterns observed in biological signals such as heart rate, respiration and walking strides measured over time, indicate that the time intervals between events are not equal, nor are they independent. Rather, there is a relationship between these intervals that extends far forward and backward in time; in other words, exhibiting long-range correlations in the time series, or fractal fluctuations. The presence of these fractal processes in biological systems is theoretically referred to as ‘‘complexity’’, which describes an underlying order or pattern that is contained within a complex, variable system; a system that is capable of sudden and marked change. The multi-scale fractal structure of the relationships between gait events is therefore thought to be ordered and stable, yet variable and flexible. Complexity is recognized as an inherent attribute of healthy biological systems, whereas the loss of complexity with aging and disease is thought to reduce the adaptive capabilities of the individual. A loss of complexity can refer to either an overly constrained, periodic system, or an overly random, incoherent system (1-2)

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