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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

Overton, Willis. Developmental Psychology: Philosophy, Concepts, Methodology. Lerner, Richard, vol. ed. Handbook of Child Psychology. 6th Edition. Vol. 1: Theoretical Models of Human Development. Hoboken, NJ: Wiley, 2006. The past decades of scientific discourse were characterized by a “split metatheory” traceable to a Cartesian atomism. In its stead a “relational dynamic matrix” is proposed which can resolve and join the “identity of opposites” and “opposites of identity” for both personal and social integrity. See also Overton’s significant writings cited herein.

Relational metatheory, emerging from a view of the world as a series of active, ever-changing forms replaces the antinomies with a fluid dynamic holism and associated concepts such as self-organization, system, and the synthesis of wholes. (19)

Overton, Willis. Life-span Development: Concepts and Issues. Lerner, Richard, editor-in-chief. The Handbook of Life-span Development. Hoboken, NJ: Wiley, 2010. The lead essay for this two volume edition sets out its thematic employ of a “relational developmental systems metatheory.” This “organismic” view is advocated so as to move beyond a mechanistic emphasis, sans any context, on objects alone. Its theme of self-organizing complex adaptive systems is then carried through many articles by authors such as Gary Greenberg, Brian McWhinney, Michael Lewis, and Linda Jarvin. See also Advancing Developmental Science (Routledge 2018) for chapters upon Overton's lifetime contribution.

Parlade, Meaghan and Jana Iverson. The Interplay between Language, Gesture, and Affect During Communicative Transition: A Dynamic Systems Approach. Developmental Psychology. 47/3, 2011. University of Pittsburgh psychologists find a child’s vocabulary spurt to express the same self-organizing dynamics of a young person’s bodily and behavioral maturation.

Complex organisms including developing infants, are composed of multiple interacting parts that self-organize to operate collectively. A myriad of behavioral models of cooperative coordinations are possible depending on the relative stability of each component of the system at given time. An important implication of this view is that instability in one component (e.g., the introduction of a new skill or transformation of an existing skill) will engender changes in the way the system as a whole is organized. (820-821)

Perszyk, Danielle and Sandra Waxman. Linking Language and Cognition in Infancy. Annual Review of Psychology. 69/231, 2017. Northwestern University psychologists explain a parallel reciprocity between an infant’s rapidly developing brain and a facile ability to understand and avail an innate linguistic readiness. In regard, the finding shows how vital it is during a child’s first year to hear and be engaged with conversational speech.

Human language, a signature of our species, derives its power from its links to human cognition. For centuries, scholars have been captivated by this link between language and cognition. In this article, we shift this focus. Adopting a developmental lens, we review recent evidence that sheds light on the origin and developmental unfolding of the link between language and cognition in the first year of life. This evidence, which reveals the joint contributions of infants’ innate capacities and their sensitivity to experience, highlights how a precocious link between language and cognition advances infants beyond their initial perceptual and conceptual capacities. The evidence also identifies the conceptual advantages this link brings to human infants. By tracing the emergence of a language–cognition link in infancy, this article reveals a dynamic developmental cascade in infants’ first year, with each developmental advance providing a foundation for subsequent advances. (Abstract)

Pittman-Polletta, Benjamin, et al. The Role of the Circadian System in Fractal Neurophysicological Control. Biological Reviews. 88/4, 2013. In the earlier 20th century, a basic state of human well-being became known as “homeostasis” – a stable equilibrium. Here Brigham and Women’s Hospital, Boston, Harvard Medical School, Oregon Health and Science University, and National Central University, Taiwan, physicians achieve, based on two decades of research studies aided by neuroimaging and computational advances, a robust synthesis that finds that along with steady balances, an organism’s condition is actually a nested intricacy of non-equilibrium, critically poised complex networks. By these insights, a benefit is that a healthy soma can be quantified by the degree of self-similar, invariant topologies. This new capability is seen of especial value for cardiac rhythms, cancer diagnostics and Alzheimer detection, each caused by a decay of such fractality. See also Hu, Kun, et al, and Bashan, Amir, et al, herein for more evidence and references.

Many neurophysiological variables such as heart rate, motor activity, and neural activity are known to exhibit intrinsic fractal fluctuations – similar temporal fluctuation patterns at different time scales. These fractal patterns contain information about health, as many pathological conditions are accompanied by their alteration or absence. In physical systems, such fluctuations are characteristic of critical states on the border between randomness and order, frequently arising from nonlinear feedback interactions between mechanisms operating on multiple scales. Thus, the existence of fractal fluctuations in physiology challenges traditional conceptions of health and disease, suggesting that high levels of integrity and adaptability are marked by complex variability, not constancy, and are properties of a neurophysiological network, not individual components. Despite the subject's theoretical and clinical interest, the neurophysiological mechanisms underlying fractal regulation remain largely unknown. The recent discovery that the circadian pacemaker (suprachiasmatic nucleus) plays a crucial role in generating fractal patterns in motor activity and heart rate sheds an entirely new light on both fractal control networks and the function of this master circadian clock, and builds a bridge between the fields of circadian biology and fractal physiology. In this review, we sketch the emerging picture of the developing interdisciplinary field of fractal neurophysiology by examining the circadian system's role in fractal regulation. (Abstract)

A powerful analogy for fractals in physiology comes from modern statistical physics, where fractal fluctuations have been explained in the context of so-called critical systems – systems undergoing a transition from one stable state to another. (2) A key feature of critical systems is that they are made up of a population of many simple interacting units. The richness of the collective behavior of this population, exemplified by the presence of fractality, cannot be derived from the properties of the individual units. Rather, it emerges from systemwide interactions. (3) What is clear is that the understanding of fractal patterns in physiology cannot be obtained with traditional reductive approaches that focus on individual physiological processes operating at a single timescale. Elucidating the principles governing fractal fluctuations in physiology will require an integrative, holistic, systems-level approach, based on a network view of multiple component processes and their interactions. The mechanism producing fractal patterns are not the simple homeostatic control mechanism of Claude Bernard and Walter Cannon, designed to maintain constant conditions through negative feedback regulation, but new kinds of fractal control and fractal regulatory mechanisms. (3)

Rochat, Philippe. Five Levels of Self-Awareness as They Unfold Early in Life. Consciousness and Cognition. 12/4, 2003. The Emory University psychologist proposes a scale of Differentiation, Situation, Identification, Permanence and Self-consciousness, generally akin to Piaget, as they relate to a child’s degree of recognition in a mirror. As adults, we constantly scroll through this sequential emergence for our conceptual identity.

A natural history of children’s developing self-awareness is proposed as well as a model of adult self-awareness that is informed by the dynamic of early development. Adult self-awareness is viewed as the dynamic flux between basic levels of consciousness that develop chronologically early in life. (717) To end with a garden metaphor, self-awareness develops like onions, layers after layers, in a cumulative consolidation. (730)

Rochat, Philippe. The Infant’s World. Cambridge: Harvard University Press, 2001. A synoptic text considers self-organization principles to be part of the story but traditional conditioning and built-in reward systems need to be factored in.

Rolls, Edmund. Cerebral Cortex: Principles of Operation. Oxford: Oxford University Press, 2016. An Oxford Centre for Computational Neuroscience senior research theorist achieves a 950 page synthesis of the latest advances, see quote next. Some 26 chapters such as Hierarchical Organization, Localization of Function, Recurrent Collateral Connections, Synaptic Learning, Invariant Vision, Evolutionary Trends in Cortical Design, and Genetics and Self-Organization Build the Cortex covers a widest array of features. And once again dual, complementary ventral What (discrete objects) and dorsal Where (spatial context) visual streams are established and contrasted.

The cerebral cortex is the outer layer of neural tissue of the cerebrum of the brain, in humans and other mammals. It is separated into two cortices, by the longitudinal fissure that divides the cerebrum into the left and right cerebral hemispheres. The two hemispheres are joined beneath the cortex by the corpus callosum. The cerebral cortex plays a key role in memory, attention, perception, awareness, thought, language, and consciousness. (Wikipedia)

Sarelsbergh, G., et al, eds. Non-linear Developmental Processes. Amsterdam: Royal Netherlands Academy of Arts and Sciences, 1997. Dynamical approachs to how movement, attention, speech, emotion, behavior and so on forms in infants and children.

Scharff, Constance and Jana Petri. Evo-Devo, Deep Homology and FoxP2: Implications for the Evolution of Speech and Language. Philosophical Transactions of the Royal Society B. 366/2124, 2011. Free University of Berlin ethologists contribute still another example of an ancient lineage of such genetic sources for a wide array of traits, as the Abstract notes, which serve to influence behavioral communications. Again a deep convergence, as if a true embryogenesis is quite implied.

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the ‘evo-devo’ conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this ‘deep homology’. Recently, ‘evo-devo’ has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can ‘descend with modification’. (Abstract)

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)

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