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VII. WumanKinder: An EarthSphere Transition in Individuality

1. Systems Physiology and Psychology: Somatic and Behavioral Development

Schwab, Karin, et al. Nonlinear Analysis and Modeling of Cortical Activation and Deactivation Patterns in the Immature Fetal Electrocorticogram. Chaos. 19/1, 2009. As the abstract and editorial comment convey, Friedrich Schiller University computational neurologists achieve a unique insight and quantification into the mental states of a mammalian fetus. Fetuses are actually asleep until birth when they awake. They are also found to be in a dream mode at times. Of course, the research was done on sheep. See On the Emergence of Consciousness by Lagercrantz and Changeux (search) in the 2010 volume The Newborn Brain for discussion.

An approach combining time-continuous nonlinear stability analysis and a parametric bispectral method was introduced to better describe cortical activation and deactivation patterns in the immature fetal electroencephalogram (EEG). Signal models and data-driven investigations were performed to find optimal parameters of the nonlinear methods and to confirm the occurrence of nonlinear sections in the fetal EEG. The resulting measures were applied to the in utero electrocorticogram (ECoG) of fetal sheep at 0.7 gestation when organized sleep states were not developed and compared to previous results at 0.9 gestation. Cycling of the nonlinear stability of the fetal ECoG occurred already at this early gestational age, suggesting the presence of premature sleep states. This was accompanied by cycling of the time-variant biamplitude which reflected ECoG synchronization effects during premature sleep states associated with nonrapid eye movement sleep later in gestation. Thus, the combined nonlinear and time-variant approach was able to provide important insights into the properties of the immature fetal ECoG. (Abstract)

After about seven months growing in the womb, a human fetus spends most of its time asleep. Its brain cycles back and forth between the frenzied activity of rapid eye movement (REM) sleep and the quiet resting state of non-REM sleep. But whether the brains of younger, immature fetuses cycle with sleep or are simply inactive has remained a mystery, until now. Karin Schwab and a team of neuroscientists at Friedrich Schiller University in Jena, Germany, have discovered that very immature sheep fetuses can enter a dreaming sleep-like state weeks before the first rapid eye movements are seen. Directly measuring the brain activity of a human fetus in the womb is impossible. What we know about our early sleep habits inside our mothers comes mostly from watching muscle and eye movements. Around the seventh month of a fetus' development, the first rapid eye movements are seen. The brain of the developing embryo appears to cycle every 20 to 40 minutes between REM sleep, in which brain activity rivals that of consciousness, and non-REM sleep, in which the brain rests. Schwab studied sheep, an animal that typically carries one or two fetuses similar in size and weight to a human fetus. The course of brain development is also fairly similar in humans and sheep, lasting about 280 days in humans and 150 days in sheep. The team recorded electrical activity in the brain of a 106-day-old developing sheep fetus directly -- something that had never been done before. (Editor)

Seely, Andrew, et al. Fractal Structure and Entropy Production within the Central Nervous System. Entropy. 16/8, 2014. Ottawa Hospital Research Institute systems physicians carefully show how anatomy and physiology are graced by this optimally efficient self-similar geometry, a fine feature that can serve as a measure of one’s well being. The degree to which this natural topology is maintained or deteriorates can then give indications of health or illness. Indeed real cases are given for multiple sclerosis, Alzheimer’s, cancer and more.

Our goal is to explore the relationship between two traditionally unrelated concepts, fractal structure and entropy production, evaluating both within the central nervous system (CNS). Fractals are temporal or spatial structures with self-similarity across scales of measurement; whereas entropy production represents the necessary exportation of entropy to our environment that comes with metabolism and life. Fractals may be measured by their fractal dimension; and human entropy production may be estimated by oxygen and glucose metabolism. In this paper, we observe fractal structures ubiquitously present in the CNS, and explore a hypothetical and unexplored link between fractal structure and entropy production, as measured by oxygen and glucose metabolism.

Rapid increase in both fractal structures and metabolism occur with childhood and adolescent growth, followed by slow decrease during aging. Concomitant increases and decreases in fractal structure and metabolism occur with cancer vs. Alzheimer’s and multiple sclerosis, respectively. In addition to fractals being related to entropy production, we hypothesize that the emergence of fractal structures spontaneously occurs because a fractal is more efficient at dissipating energy gradients, thus maximizing entropy production. (Abstract)

The central nervous system (CNS) is arguably the most complex, remarkable, seemingly impenetrable, not to mention endearing and personal complex system in Nature. The emergent properties of the CNS such as consciousness, memory, coordinated movement, and homeostasis, are as remarkable as the self-organized manner in which they are formed during embryogenesis and childhood. Thus, the CNS is fertile ground to explore concepts regarding the origin of self-organized structure and function in complex systems. (4498)

Silbereis, John, et al. The Cellular and Molecular Landscapes of the Developing Human Central Nervous System. Neuron. 89/2, 2016. Yale University School of Medicine neuroscientists provide a latest review from our worldwise vantage of how we peoples came to be able to individually learn and collectively achieve this.

The human CNS follows a pattern of development typical of all mammals, but certain neurodevelopmental features are highly derived. Building the human CNS requires the precise orchestration and coordination of myriad molecular and cellular processes across a staggering array of cell types and over a long period of time. Dysregulation of these processes affects the structure and function of the CNS and can lead to neurological or psychiatric disorders. Recent technological advances and increased focus on human neurodevelopment have enabled a more comprehensive characterization of the human CNS and its development in both health and disease. The aim of this review is to highlight recent advancements in our understanding of the molecular and cellular landscapes of the developing human CNS, with focus on the cerebral neocortex, and the insights these findings provide into human neural evolution, function, and dysfunction. (Abstract)

Skonkoff, Jack and Deborah Phillips, eds. From Neurons to Neighborhoods: The Science of Early Childhood Development. Washington, DC: National Academy Press, 2000. A major public effort involving the Board on Children, Youth, and Families of the National Research Council to properly consider an infant and child’s contextual, familial environment along with their individual medical and behavioral concerns. A prime finding is that these settings have an immense positive or negative influence, which then carries over into personal and local responsibility.

Smith, Linda and Esther Thelen. Development as a Dynamic System. Trends in Cognitive Sciences. 7/8, 2003. A recent review which contends that the fluid, multicausal formation of behavior from infant to adult can be understood through the principles of nonlinear self-organization. A nested fractal-like scale is inferred by a comparison of the large and small self-similarity of coastlines to one’s emotional growth from momentary states to moods to a stable personality.

Smith, Linda and Michael Gasser. The Development of Embodied Cognition. Artificial Life. 11/1-2, 2005. Infants learn by a multimodal, incremental interaction with and exploration of their physical and social environment, which leads to language-based, symbolic communication. This study is a good example of what Suzanne Kirschner (noted in A Symbiotic Self) advocates as a new relational and context-sensitive method for psychology.

The central idea behind the embodiment hypothesis is that intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity. (13)

Soanwane, Abjijeet, et al. Network Medicine in the Age of Biomedical Big Data. arXiv:1903.05449. Brigham and Women’s Hospital, Boston systems physicians provide a good example of a novel holistic, systemic approach which takes in not only parts and a whole but internal, vital interconnections as a major factor for diagnosis and treatment

Speelman, Craig and Kim Kirsner. Beyond the Learning Curve: The Construction of Mind. Oxford: Oxford University Press, 2005. Psychologists at the University of Western Australia seek innate principles of knowledge and skill acquisition within a broad evolutionary and dynamic frame. The brain/mind ensemble is conceived as a complex adaptive system because as such it expresses the universality by which nature evolves and develops everywhere else.

Spencer, John and Esther Thelen, eds. Connectionist and Dynamic Systems Approaches to Development. Developmental Science. 6/4, 2003. A special issue looks toward a synthesis of these two methods in the field of child psychology. Connectionism involves a neural basis while the dynamic view deals with a more somatic basis, but are similar in kind and contribute to “a unified emergentist theory of development.”

Spencer, John, et al. Moving Toward a Grand Theory of Development. Child Development. 77/6, 2006. Former doctoral students of the late University of Indiana psychology professor Esther Thelen offer a considerate retrospective of her pioneering innovations in the use of dynamic systems theory (DST) to understand the self-organization of a child’s kinetic and cognitive experience. Learning to walk and to learn via DST involves four aspects – a temporal mode, multiple nonlinear interactions, embodiment, and one’s unique individuality. Upon reflection, might one observe that human and universe organize themselves in the same manner, each on the way to self-realization.

Spencer, John, et al, eds. Toward a Unified Theory of Development. Oxford: Oxford University Press, 2009. By way of a copious convergence of Connectionism, aka Parallel Distributed Processing, generally due to David Rumelhart, and here coeditor James McClelland, and the Dynamic Systems Theory of Esther Thelen and Linda Smith. The first school more involves neural net cognitive processes, while the second is concerned with how a child grows and learns. Now an aim of this website is to gather such various methods, e.g., also complex adaptive systems, autopoiesis, et al, from disparate fields and mentors, and by way of translation to a common lexicon convey how they each and all are trying to explain one and the same phenomena everywhere.

The two approaches conceive of this self-organization differently. For dynamic systems theories, developmental change is an emergent product of interactions among multiple components, occurring on many different timescales. Theories adopting this framework emphasize multicausality and self-organization emerging out of the real-time dynamics of the child’s own activity in a structured environment. For connectionist theories of development, reorganization emerges out of nonlinearities in learning and new structures only emerge from the interaction of the existing structure and environmental input. (269) Central to both connectionist and dynamic systems theories of development, therefore, is the explicit idea that new structures and behaviors are emergent products of multiple, interacting components. (269)

Stella, Massimo, et al. Multiplex Lexical Networks Reveal Patterns in Early Word Acquisition. Nature Scientific Reports. 7/46730, 2017. We cite this entry by systems neuroscientists M. Stella and Markus Brede, University of Southampton, UK, with Nicole Beckage, University of Kansas, as a frontier example of how the latest understandings of network phenomena, namely dynamic multiplex layering, can find apply and veracity in many disparate domains.

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