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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

1. Systems Physiology and Psychology: Somatic and Behavioral Development

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)

Ivanov, Plamen. Focus on Network Physiology and Network Medicine. New Journal of Physics. May, 2014. The Boston University and Harvard Medical School systems physician introduces an ongoing series of papers on these integral appreciations of health and well being. Here is another example of this grand unification of soma and cosmos by way of this ubiquitous phenomena just now gaining its physical basis. Please see Amir Bashin herein for more.

The scope of the (ongoing) issue encompasses both network physiology and network medicine, where new concepts and approaches derived from recent advances in the theory of Complex Networks are applied to provide insights into physiological structure and function in health and disease; from the genetic and sub-cellular level to inter-cellular interactions and communications across integrated organ systems. Of particular interest will be new and little-explored areas of network science including the following. Studies on structural and dynamical aspects of physiological systems that transcend time and space scales.

Ivanov, Plamen, et al. Focus on the Emerging New Fields of Network Physiology and Network Medicine. New Journal of Physics. 18/100201, 2016. In this follow up to a 2014 posting by Ivanov herein announcing the special collection, Boston University and Bar-Ilan University scientists summarize the 26 entries about sub-cellular to organismic phenomena. Some entries are Co-controllability of Drug-Disease-Gene Network, Complexity Matching in Neural Networks, and Spreading of Diseased through Comorbidity Networks Across Life and Gender. Nature’s universal network physics can indeed revolutionize how we understand and care for our own somatic selves in sickness and health.

Despite the vast progress and achievements in systems biology and integrative physiology in the last decades, there is still a significant gap in understanding the mechanisms through which (i) genomic, proteomic and metabolic factors and signaling pathways impact vertical processes across cells, tissues and organs leading to the expression of different disease phenotypes and influence the functional and clinical associations between diseases, and (ii) how diverse physiological systems and organs coordinate their functions over a broad range of space and time scales and horizontally integrate to generate distinct physiologic states at the organism level. Two emerging fields, network medicine and network physiology, aim to address these fundamental questions. Novel concepts and approaches derived from recent advances in network theory, coupled dynamical systems, statistical and computational physics show promise to provide new insights into the complexity of physiological structure and function in health and disease, bridging the genetic and sub-cellular level with inter-cellular interactions and communications among integrated organ systems and sub-systems. (Abstract)

Jirsa, Viktor and J. A. Scott Kelso, eds. Coordination Dynamics. Boca Raton, FL: Springer, 2004. These studies of how the activities of bodies and brains become synchronized lead to theories of a universal “coordinative” tendency in complex systems. By this view, an evolutionary vector is indicated toward individual, goal-directed agency.

A central hypothesis of Coordination Dynamics is that spontaneous self-organizing coordination tendencies give rise to agency; that the most fundamental kind of consciousness, the awareness of self, springs from the ground of spontaneous self-organized activity. (ix)

Kelso, Scott. Principles of Dynamic Pattern Formation and Change for a Science of Human Behavior. Lars Bergman, et al, eds. Developmental Science and the Holistic Approach. Mahwah, NJ: Erlbaum, 2000. Complexity science is applied to functional development to reveal how the perception of a figure/ground, behavior/environmental context reciprocity is crucial to its understanding.

One of the most profound impacts of the ‘new sciences of complexity’….is that the key to understanding ourselves lies in the complementary nature of objective physical description and the no-less-fundamental, apparently subjective context-dependence of living systems. The sciences of life and mind rest on this complementarity. (67)

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