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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Recent Additions

Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 91 through 105 of 118 found.

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

Earth Life > Integral Persons > Cerebral Form

Bertolero, Max and Danielle Bassett. How Matter Becomes Mind. Scientific American. July, 2019. It is good sign that a research field has reached a robust, credible stage when an article appears in this popular publication, which is a credit to its University of Pennsylvania network neuroscientist authors and collaborators. It reports upon an array of advances over the past decade that altogether reveal and highlight multiplex connectivities (aka graph theory here) between nodal neurons, layered linkages, and modular communities as they give rise to informed thought and response. We log in this week similar evidence from physics (Nottale, Busch), cancer studies (D. Moore), cellular dynamics (Fuchling) and other areas. As a wealth of citations now convey, an iconic, natural system of infinitely iterated, generative node entities and link relations in a triune whole iconic does really seem to exist.

Earth Life > Integral Persons > Cerebral Form

Bertolero, Maxwell, et al. The Network Architecture of the Human Brain is Modularly Encoded in the Genome. arXiv:1905.07606. Eight University of Pennsylvania physicists and psychiatrists including Ted Satterthwaite, Ruben and Raquel Gur, and Danielle Bassett contribute to 2019 perceptions of an iconic, complex mathematical complexity, architecture and process which repeats in kind across many neural and metabolic domains. A further deep affinity is reported between genomic and cerebral instantiations and their resultant active topologies. Once again via a global sapience a genesis nature is found to avail and exemplify one universal pattern and process at each and every instance and stage.

Many complex biological systems—from the musculoskeletal system to protein interactions—can be represented as networks composed of elements (nodes) and their interactions or relations (edges). As a quintessential example, the human brain is composed of large areas interlinked by structural or functional connections. The coarse-grained organization of brain networks is modular, where groups of nodes tend to form tightly interconnected communities. Finally, brain network organization as manifest in both structural and functional connectivity is hereditable, suggesting that brain connectivity is genetically encoded. (2)

Earth Life > Integral Persons > Cerebral Form

Lynn, Christopher, et al. Human Information Processing in Complex Networks. arXiv:1906.00926. University of Pennsylvania neuroengineers including Danielle Bassett contribute to the network revolution by showing how this connectomic feature serves our cognitive performance. See also A Mathematical Theory of Semantic Development in Deep Neural Networks by Andrew Saxe, et al (herein) for a similar concurrent study.

Humans communicate using systems of interconnected stimuli or concepts from language and music to literature and science yet it remains unclear how the structure of these networks supports this process. Here we demonstrate that this perceived information depends on a system's network topology. Applying our framework to several real networks, we find that they communicate a large amount of information (high entropy) and do so efficiently (low divergence from expectations). Moreover, we show that such efficient communication arises in networks that are simultaneously heterogeneous, with high-degree hubs, and clustered, with tightly-connected modules. These results suggest that many real networks are constrained by the pressures of information transmission, and that they select for specific structural features. (Abstract excerpt)

Earth Life > Integral Persons > Cerebral Form

Raghavan, Guruprasad and Matt Thomson. Neural Networks Grown and Self-Organized by Noise. arXiv:1906.01039. We cite this entry by Caltech bioengineers for the way it implies an internal drive and direction that is an intelligence gaining, self-learning, quickening genesis. As these observation grow in breadth and veracity, they suggest a natural presence that seems to require at some far point the achieve its own witness and affirmation.

Living neural networks in the brain perform an array of computational and information processing tasks including sensory input processing, storing and retrieving memory, decision making, and more globally, generate the general phenomena of “intelligence”. In addition to their information processing feats, brains are unique because they are computational devices that actually self-organize their intelligence. In fact brains ultimately grow from single cells during development. Engineering has yet to construct artificial computational systems that can self-organize their intelligence. In this paper, inspired by neural development, we ask how artificial computational devices might build themselves without human intervention. (1)

Earth Life > Integral Persons > Cerebral Form

Sporns, Olaf. Graph Theory Methods: Applications in Brain Networks. Dialogues in Clinical Neuroscience. 20/2, 2018. The Indiana University neuropsychologist (search) is a leading theorist in this enchanted field as it weaves through the 2010s toward epic achievements. This paper is notably cited as a basis for Max Bertolero and Danielle Bassett’s Scientific American (July 2019) popular review (above). As many other realms, mathematic findings of equally real interconnections between previously found discrete objects and entities are fostering a relational revolution from particles and galaxies to persons and societies. See also The Diverse Club by Max Bertolero, et al in Nature Communications (8/1277, 2017).

Network neuroscience is a thriving and rapidly expanding field. Empirical data on brain networks, from molecular to behavioral scales, are increasing in size and complexity. These developments require appropriate tools and methods that model and analyze brain network data, such as those provided by graph theory. This brief review surveys commonly used and neurobiologically apt graph measures and techniques. Among these, the detection of network communities or modules, and of central network elements that facilitate communication and signal transfer are particularly salient. We note a growing use of generative models, temporal and multilayer networks, as well as algebraic topology. (Abstract excerpt)

Earth Life > Integral Persons > Complementary Brain

Elices, Irene, et al. Robust Dynamical Invariants in Sequential Neural Activity. Nature Scientific Reports. 9/9048, 2019. Autonomous University of Madrid neurocomputation researchers add another finesse of the cerebral presence of mutual conservative and creative complements across many network phases. Their active behavior then seeks and becomes poised at an optimum reciprocity.

By studying different sources of temporal variability in central pattern generator (CPG) circuits, we unveil fundamental aspects of the instantaneous balance between flexibility and robustness in sequential dynamics - a property that characterizes many systems that display neural rhythms. Our analysis of the triphasic rhythm of the pyloric CPG (Carcinus maenas) shows strong robustness of transient dynamics in keeping not only the activation sequences but also specific cycle-by-cycle temporal relationships in the form of strong linear correlations between pivotal time intervals, i.e. dynamical invariants. We suggest that invariant temporal sequence relationships could be present in other networks, including those shaping sequences of functional brain rhythms, and underlie rhythm programming and functionality. (Abstract excerpt)

Earth Life > Integral Persons > Complementary Brain

Friederici, Angela. Language in Our Brain: The Origins of a Uniquely Human Capacity. Cambridge: MIT Press, 2017. The MPI Human Cognitive and Brain Sciences neuroscientist director and MPI vice president surveys the past 35 years of her own work from MIT (her mentor/colleague Noam Chomsky writes a preface) and the full literature into 2010s as the cerebral nature of our unique linguistic abilities became clearly evident. Rather than a left side trait, as long held, it is lately realized that both complementary hemispheres are actively involved in speaking and hearing. As Dr. Friederici well conveys, it is now confirmed that an on-going interplay of a left syntactic, lexical, rapid frequency mode and prosodic, semantic, complex pitch right input achieves a whole, fast and slow, brain system. Her studies of infants and children reveal a holistic right side start which later transitions in the second year to a left side emphasis. Ontogeny and phylogeny parallels accrue by way of gestural, melodic evolutionary origins for animal and primate communications.

With the development of new neuroscientific methods, the relation between language and the brain could be observed in living persons while processing language. Today the language network can be described to consist of a number of cortical regions in the left and right hemispheres. These interact in time under the involvement of some subcortical structures that are not specific for language but may serve as a relational systems between the network and its sensory input systems and its output systems. In this book I primarily focus on the cortical regions of the neural language network, which I will discuss with respect to their particular function in the adult brain and the developing brain. (8)

Pitch information is crucial in linguistic prosody and emotional prosody, but also in processing music melody. In this section I reviewed the neuroscientific studies on prodessing prosody during speech perception and of music. The processing of prosodic information during speech comprehension crucially involves the right hemisphere, whereas syntax is processed in the left hemisphere. During speech the left and right hemisphere interact online to assign phrase boundaries as the borders of constituents. They do this via the corpus callosum – a white matter structure that connects the two sides. In sum these studies conclude that although pure pitch may be processed in the right superior temporal gyrus, the localization of higher pitch-related processes is dependent on the particular function that pitch conveys: lexical tone in the left hemisphere, linguistic prosody bilaterally with a leftward lateralization, and music with a rightward path. (81)

Earth Life > Integral Persons > Conscious Knowledge

Grindrod, Peter. On Human Consciousness. Network Neuroscience. 2/1, 2018. The Oxford University mathematician is an authoritative contributor to frontier explanations about why and how we individual and collective human beings are graced with a sentient, informed awareness. If such mindful imaginaries are indeed possible, they must somehow be associated with and arise from a similarly endowed cerebral cosmos.

We consider implications of the mathematical modeling and analysis of large modular neuron-to-neuron networks. We explain how the dynamical behavior of relatively small-scale strongly connected networks leads to nonbinary information processing and thus to multiple hypothesis decision-making. In turn we address some aspects of the hard problem of consciousness, We discuss how a proposed “dual hierarchy model,” made up from externally perceived, physical elements of increasing complexity, and internally experienced, mental elements (feelings), may support a learning and evolving consciousness. We argue that, within our model, the mental elements and thus internal modes (feelings) play a role akin to latent variables in processing and decision-making, and thus confer an evolutionary “fast-thinking” advantage. (Abstract excerpt)

Earth Life > Integral Persons > Conscious Knowledge

Hernandez-Espinosa, Alberto, et al. Estimations of Integrated Information Based on Algorithmic Complexity and Dynamic Querying. arXiv:1904.10393. A H-E, National Autonomous University of Mexico, along with Hector Zenil, Narsis Kiani, and Jesper Tegner, Karolinska Institute, Sweden apply their long experience with computational mathematics to foster understandings and applications of this popular theorey of knowing consciousness. Section headings include Finding Simple Rules in Complex Behavior and The Fractal Distribution of Information.

We establish and build theoretical and numerical connections between the theories and methods of integrated information and algorithmic complexity. We introduce a method for estimating integrated information by way of a programmability test rooted in algorithmic information dynamics. Our method is based on the idea that simple rules of causal dynamical systems can shorten the calculation needed to estimate integrated information. On the basis of the perturbation test, we demonstrate how a system can be regarded as providing explanations for its own behaviour. We expect this approach to contribute toward a better understanding of integrated information and of its connections to other, more established areas of science such as dynamical systems and algorithmic information theory. (Abstract excerpt)

Earth Life > Integral Persons > Gender

Goyal, Manu, et al. Persistent Metabolic Youth in the Aging Female Brain. Proceedings of the National Academy of Sciences. 116/3251, 2019. Washington University School of Medicine, St. Louis neuroimage researchers report results about how women retain this neoteny feature of remaining in a younger state longer than male counterparts.

Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (n = 205) to define their metabolic brain age. We find that throughout the adult life span the female brain has a persistently lower metabolic brain age—relative to their chronological age—compared with the male brain. The persistence of relatively younger metabolic brain age in females throughout adulthood suggests that development might in part influence sex differences in brain aging. (Abstract)

Earth Life > Phenomenon > Human Societies

Christakis, Nicholas. Blueprint: The Evolutionary Origins of a Good Society. New York: Little, Brown, 2019. This opus by the physician and sociologist (bio below) is a prime contribution our current historic synthesis of science and culture. As 500+ pages of theory and example serve to explain and document, the old sway of competition from Darwin’s day can at last be set aside. Rather, an innate propensity for cooperation of benefit to both member and group is now known as nature’s behavioral rule and preference. Moreover, it’s occasion can be seen as deeply rooted and written into our individual and collective genetic heritage. We cite an endorsement among many for this breakthrough accomplishment.

Christakis has found that all human cultures converge on a consistent style of social network, and in Blueprint he explores the reasons why. The answer, he boldly argues, lies in our genes. Digging widely, he shows that a gene-based account does not have to challenge the impact of culture, nor does it commit the analysis to reductionism or determinism. Blueprint stakes a powerful claim for a richer incorporation of biology into the social sciences. (Richard Wrangham)

Nicholas A. Christakis, MD, PhD, MPH, is the Sterling Professor of Social and Natural Science at Yale University, with appointments in the departments of Sociology, Ecology and Evolutionary Biology, Statistics and Data Science, Biomedical Engineering, and Medicine. He has conducted research and taught for many years at Harvard University and at the University of Chicago. He worked as a hospice physician in underserved communities in Chicago and Boston until 2011.

Earth Life > Phenomenon > Human Societies

Gao, Jian, et al. Computational Socioeconomics. Physics Reports. Online June, 2019. The Chinese computer scientist authors JG, Yi-Cheng Zhang and Tao Zhou have multiple postings such as the University of Electronic Science and Technology, MIT Media Lab and University of Fribourg, Switzerland. At 122 pages and 877 references the entry achieves a sophisticated quantification of our intense, electronic, urban, commercial societies. Main sections cover Global development, inequality and complexity; Regional socioeconomic status and urban perception; Individual socioeconomic status and attributes; and Situational awareness and disaster management. These include social psychologies, epidemics, online media, demographics, employment and much more. To reflect, a worldwide retrospective analysis is now possible of our relative human civilizations. By this global vista, a novel mathematical dimension, with scale-free regularities and inherent dynamics, becomes evident as not before.

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies. (Abstract)

Earth Life > Phenomenon > Physiology

Barthelemy, Marc. The Statistical Physics of Cities. arXiv:1905.01953. A Centre d'Analyse et de Mathématique Sociale, Paris systems theorist continues his studies, notably akin to Michael Batty in London, to an extent that urban fractal self-organization dynamics can be traced to and viewed as condensed matter phenomena. Though not so put, our small and large concentrated human habitations appear to spontaneously emerge and exemplify a generative natural source and agency. A hundred plus reference list provides a broad two decade survey.

Challenges due to the rapid urbanization of the world -- especially in emerging countries -- range from an increasing dependence on energy, to air pollution, socio-spatial inequalities, environmental and sustainability issues. Modelling the structure and evolution of cities is critical because policy makers need robust theories and new paradigms for mitigating these problems. Statistical physics plays a major role in this effort by bringing tools and concepts able to bridge theory and empirical results. Here we focus on the distribution of the urban population; segregation phenomena and spin-like models; the polycentric transition of the activity organization; energy considerations about mobility and models inspired by gravity and radiation concepts and scaling that describes how socio-economical and infrastructures evolve when cities grow. (Abstract)

Earth Life > Phenomenon > Macrohistory

Crawford, Ian. Introduction to the Special Issue on Expanding Worldviews: Astrobiology, Big History, and the Social and Intellectual Benefits of the Cosmic Perspective. Journal of Big History. 3/3, 2019. This edition gathers papers from BH conferences and beyond as a collaborative Earthkinder stirs to a visionary sapience of our ancient heritage traced all the way to a singular cosmic origin. As a mainly male endeavor, the scenario remains bereft of any phenomenal nature and significance of its organic own which might explain and provide purpose. Among the entries are The Keen Longing for Unified, All-Embracing Knowledge by David Christian, Cosmic Perspectives and the Myths We Need to Survive by Charles Lineweaver (Abstract below), The Biological Overview Effect by CL and Aditya Chopra, Big History in its Cosmic Context by Joseph Voros, and Is the Universe Enough? by Mark Lupisella. See also a Life in the Universe 2019 conference (search Balbi) for more activities and vistas.

Big history can be defined as the attempt to understand the integrated timeline of the cosmos, Earth, life and humanity. The aim of this paper is to describe a dilemma that such a scientific, Darwinian big history must face: the inevitable incompatibility between an objective scientific search for truth and an evolutionary compulsion for brains to harbor useful fictions — the myths we need to survive. Science supports both sides of this dilemma. New and improved cosmic perspectives can’t just be scientifically accurate. To be of use they must leave room for the myths we humans need to survive. But, what are those myths? I discuss and question whether the following ideas qualify as such myths: a belief in an objective meaning for human life, humanism/speciesism, human free will and stewardship of the Earth. (Lineweaver Abstract)

Earth Life > Phenomenon > major

Bourrat, Pierrick. Evolutionary Transitions in Heritability and Individuality. Theory in Biosciences. Online May, 2019. A Macquarie University, Sydney philosopher of biology (search) continues to finesse and advance understandings of this nested, episodic, accepted model of life’s regnant reciprocity of persons in communities. See also Trait Heritability in Major Transitions by Matthew Herron, et al in BMC Biology (16/145, 2018).

The literature on evolutionary transitions in individuality (ETIs) has mostly focused on the relationships between lower-level (particle-level) and higher-level (collective-level) selection, leaving aside contrasts between particle-level and collective-level inheritance. To that effect, I present a model to study particle-level and collective-level heritability both when a collective-level trait is a linear function and when it is a non-linear function of a particle-level trait. The upshot is that population structure is a driver for ETIs. (Abstract excerpt)

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