(logo) Natural Genesis (logo text)
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 106 through 120 of 139 found.

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

Earth Life > Nest > Homo Sapiens

Tylen, Kristian, et al. The Evolution of Early Symbolic Behavior in Homo Sapiens.. Proceedings of the National Academy of Sciences. 117/4578, 2020. We cite this entry by Aarhus University, University of Johannesburg, and University of Western Australia archaeologists to convey, along with bodily features, how life’s course to our late cognitive-social phase brought out the first signs of an external depiction and record of their vital environments. Another instance is the finding of earlier cave paintings in Indonesia (Google) of an animal hunt.

Early symbolic behavior of Homo sapiens is challenging to address yet fundamental to the success of our species. We used ancient engravings from the South African Blombos Cave and Diepkloof Rock Shelter in a number of controlled cognitive experiments to qualify discussions about the evolution of early symbolic traditions. We found that the engravings evolved over a period of 30,000 y to become more effective “tools for the mind,” that is, more salient to the human eye, expressive of human intent and identity, and easier to reproduce from memory. Our experiments suggest that the engravings served as decorations and expressions of socially transmitted cultural traditions. (Significance)

Earth Life > Sentience > Brain Anatomy

Burger, Joseph, et al. Toward a Metabolic Theory of Life History. Proceedings of the National Academy of Sciences. 116/26653, 2019. Evolutionary ecologists posted in North Carolina, Missouri and New Mexico (James Brown) can now proceed to visualize and discern broadly applicable patterns and processes across the vast species diorama that past decades have put together.

The life histories of animals reflect the allocation of metabolic energy to traits that determine fitness and the pace of living. Here, we extend metabolic theories to address how demography and mass–energy balance constrain biomass for survival, growth, and reproduction over a life cycle of one generation. Evolution has generated enormous diversity of body sizes, morphologies, physiologies, ecologies, and life histories across the millions of animal, plant, and microbe species, yet simple rules specified by general equations highlight the underlying unity of life. (Abstract excerpt)

Earth Life > Sentience > Brain Anatomy

Melchionna, M., et al. Macroevolutionary Trends of Brain Mass in Primates. Biological Journal of the Linnean Society. 129/1, 2020. In this consummate year, nine evolutionary neuroscientists across Italian universities and institutes confirm life’s advancing cerebral encephalization and resultant cognitive attributes on the way to human acumen. And to reflect on their illustrated report, whomever at present is this worldwise personsphere emerging from homo to Anthropo sapience to gain a retrospective vista and import?

A distinctive trait in primate evolution is the expansion in brain mass. The potential drivers of this encephalization process due diversification dynamics are still debated. We assembled a phylogeny for 317 primate species of both extant and extinct taxa so as to identify trends in brain mass evolution. Our findings show that Primates as a whole follow a macroevolutionary increase in accord with more body mass, relative brain size and speciation rate over time. We also find that hominins, starting with Australopithecus africanus in the Oligocene, stand out for distinctly higher rates. (Abstract excerpt)

Earth Life > Sentience > Brain Anatomy

Pontes, Anselmo, et al. The Evolutionary Origin of Associative Learning. American Naturalist. 195/1, 2020. By way of clever digital simulations in Richard Lenski’s lab, Michigan State University researchers including Christoph Adami test whether this analogic edification, drawn much from Simona Ginsberg and Eva Jablonka (see definitions below), is actually in effect. Indeed, results over many generations show that life does become smarter by a constant, iterative, combinational process of trials, errors and successes for both entities and groups. From 2020, a central developmental trend of “stepwise, modular, complex behaviors” as an open-ended creativity is evidentially traced and oriented.

Learning is a widespread ability among animals and is subject to evolution. But how did learning first arise? What selection pressures and phenotypic preconditions fostered its evolution? Neither the fossil record nor phylogenetic comparative studies provide answers. Here, we study digital organisms in environments that promote the evolution of navigation and associative learning. Starting with a sessile ancestor, we evolve multiple populations in four environments, each with nutrient trails with various layouts. We find that behavior evolves modularly and in a predictable sequence. Environmental patterns that are stable across generations foster the evolution of reflexive behavior, while environmental patterns that vary across generations but remain consistent for periods within an organism’s lifetime foster the evolution of learning behavior. (Abstract excerpt)

Associative learning is a theory that states that ideas reinforce each other and can be linked to one another. Associative learning is a principle that states that ideas and experiences reinforce each other and can be linked to one another, making it a powerful teaching strategy. Associative learning, in animal behaviour, is a process in which a new response becomes associated with a particular stimulus.

Earth Life > Sentience > Bicameral Brain

Forrester, Gillian, et al, eds. Cerebral Lateralization and Cognition: Evolutionary and Developmental Investigations of Behavioral Biases. Progress in Brain Research. Volume 238, 2018. This is a copious collection which proceeds to show how widespread and important bicameral brain asymmetries are across every animal grouping. Most prominent in human beings, an ancient, axial encephalization traced to insect invertebrates consistently makes use of reciprocal detail and image faculties as the best way to survive and evolve. Among the 15 papers are Insights into the Evolution of lateralization from the Insects, Motor Asymmetries in Fishes, Amphibians, and Reptiles, Mother and Offspring Lateralized Social Behavior, and Sensorimotor Lateralization Scaffolds Cognitive Specialization.

Earth Life > Sentience > Evolution Language

Huang, Mingpan, et al. Male Gibbon Loud Morning Calls Conform to Zipf’s Law of Brevity and Menserath’s Law: Insights into the Origin of Human Language. Animal Behavior. January, 2020. This entry by Sun Yat-Sen University linguists is notable because it reports how these lawful features similarly serve to guide these vocal displays amongst primates. Such a result suggests that they commonly apply across all manner of creaturely communications. See also The Speech-like Properties of Nonhuman Primate Vocalizations by Thore Bergman, et al in this journal (151/229, 2019).

The study of vocal communication in nonhuman primates offers critical insight into the origins of human language. Although human language represents a highly derived and complex form of communication, researchers have found that the organization of language follows a series of common statistical patterns, known as ‘linguistic laws’. Zipf's law of brevity and Menzerath's law are pervasive (see below). Here, we provide evidence that the long-distance morning calls of male gibbons follow both laws. Zipf's law of brevity and Menzerath's law. Our findings thus support the generality of these two linguistic laws.. (Abstract)

Zipf's law is an empirical law which uses mathematical statistics to refer to the fact that much data studied in the physical and social sciences can be approximated by a family of related discrete power law probability distributions. Menzerath's law is a linguistic law whence the increase of the size of a linguistic construct results in a decrease of the size of its constituents, and vice versa, e.g., the longer a sentence, the shorter the clauses.

Earth Life > Sentience > Evolution Language

Prieur, Jacques, et al. The Origins of Gestures and Language: History, Current Advances and Proposed Theories. Biological Reviews. Online December, 2019. Free University of Berlin and University of Rennes, CNRS animal ethologists scope out multimodal and multicausal influences for an array of primate forebears to reconstruct how our emergent result came to have such conversational facilities.

Investigating the mechanisms underlying human and non‐human primate communication systems (gestures, vocalisations, facial expressions) can shed light on the evolutionary roots of language. Reports on non‐human primates, particularly great apes, suggest that gestural communication would have been a crucial prerequisite for the emergence of language. We review three processes that can explain great apes' gestural acquisition: phylogenetic ritualisation, ontogenetic ritualisation, and learning via social negotiation. We thus propose a theory of language origins which postulates that primates' communicative signalling is a complex trait shaped by a cost–benefit trade‐off of signal production and processing of interactants in relation to four interlinked categories of evolutionary and life cycle factors: species, individual and context‐related characteristics as well as behavior. (Abstract excerpt)

Earth Life > Genetic Info

Cowen, Lenore, et al. Network Propagation: A Universal Amplifier of Genetic Associations. Nature Review Genetics. 18/551, 2020. Tufts, Princeton, Tel Aviv University, and UC San Diego, systems geneticists including Trey Ideker contribute to growing realizations of how important these connective genomic phenomena are. In regard, they can be seen to have an equally evident, proactive role, maybe more so, than the discrete nucleotide biomolecules.

Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Fundamental to network analysis is the concept that genes underlying the same phenotype tend to interact. This principle can be used to combine and amplify signals from individual genes. Recently, bioinformatic techniques have been proposed for genetic analysis using networks, based on random walks, information diffusion and electrical resistance. In fact, all these approaches are variations of a unifying mathematical basis — network propagation — suggesting that it is a powerful data transformation method of broad utility in genetic research. (Abstract)

Earth Life > Genetic Info

Eraslan, Gokcen, et al. Deep Learning: New Computational Modelling Techniques for Genomics. Nature Reviews Genetics. 20/7, 2019. We review this paper by Technical University of Munich researchers along with Deep Neural Networks for Interpreting RNA-binding Protein Target Preferences by Mahsa Ghanbari and Uwe Ohler in Genome Research (January 2020) as an example of how frontier AI neural net techniques derived from our own cerebral cognition are being readily applied to model and analyze genetic phenomena. By this wide utility, they serve as an archetypal exemplar of self-organizing complexities which are similarly invariant from quantum to social systems. OK

As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the increasing volume of genomics data requires more expressive machine learning models. By leveraging large data sets, deep learning has transformed fields such as computer vision and natural language processing. Now, it is becoming the method of choice for many genomics modelling tasks such as the impact of genetic variation on gene regulatory mechanisms such as DNA accessibility and splicing. (Erasian Abstract excerpt)

Deep learning has become a powerful paradigm to analyze the binding sites of regulatory factors including RNA-binding proteins (RBPs), owing to its strength to learn complex features from multiple sources of raw data. However, the interpretability of these models has not yet been investigated in detail. We have designed a multitask and multimodal deep neural network to characterize in vivo RBP targets. Learning across multiple RBPs at once, we are can avoid experimental biases and identify RNA sequence motifs and transcript context patterns the most important for each individual RBP. (Ghanbari Abstract excerpt)

Earth Life > Integral Persons > Somatic

Dehaene, Stanislav. How We Learn. New York: Viking, 2020. The College of France, Saclay cognitive neuroscientist and author (search) gives exposition to the latest findings about a deep, definitive capacity of human beings from a fetal stage through infancy and youth to form and hold an internal representation of their external environs. Three main parts – What is Learning?, How Our Brain Learns, and The Four Pillars: Attention, Active Engagement, Error Feedback, and Consolidation – are clearly put with an intent that an integrative neuroscience which emphasizes this activity can be availed for more appropriate teachings and schools. This knowledge-gaining process is seen to so distinguish our curious species that a new Homo Docens name is proposed as we ever educate ourselves.

Cortical folds in the fetus’s brain owe their spontaneous formation to a biochemical self-organization process that depends on both the genes and the chemical environment of the cells, requiring extremely little genetic information and no learning at all. Such self-organization isn’t nearly as paradoxical as it sounds – in fact, it is omnipresent on earth. (74)

Earth Life > Integral Persons > Cerebral Form

Betzel, Richard. Organizing Principles of Whole-Brain Functional Connectivity in Zebrafish Larvae. Network Neuroscience. 4/1, 2020. An Indiana University neuropsychologist extends and applies the research advances that this MIT journal conveys about overall brain anatomy and physiology to this aquatic scale so as to find the same, analogous cognitive formations in effect across this middle meso-scale domain.

Network science has begun to reveal the fundamental principles by which large-scale brain networks are organized such as geometric constraints, a balance between segregative and integrative features, and functionally flexible brain areas. However, it remains unknown whether whole-brain networks imaged at the cellular level are organized according to similar principles. Here, we study whole-brain networks recorded in larval zebrafish which show that connections are distance-dependent and that networks exhibit a hierarchical modularity. Spontaneous network structure is also found to constrain stimulus-evoked net reconfigurations which are highly consistent across individuals. Thus, basic organizing principles of whole-brain functional brain networks are in effect at the mesoscale. (Abstract excerpt)

Earth Life > Integral Persons > Complementary Brain

Albouy, Philippe, et al. Distinct Sensitivity to Spectrotemporal Modulation Supports Brain Asymmetry for Speech and Melody. Science. 367/1043, 2020. In a paper that merited an issue highlight, McGill University, Laval University and Aix Marseille University neuropsychologists including Robert Zatorre describe sophisticated experiments which reveal how our cerebral faculty proceeds to comport discrete wordy (digital) discourse to the left hemisphere, and continuous, meaningful (analog) content to the right side. Once again, these complementary modes are found to distinguish a whole, script + song = knowledge, microcosmic brain.

Does brain asymmetry for speech and music emerge from acoustical cues or from domain-specific neural networks? We filtered temporal or spectral modulations in sung speech stimuli for which verbal and melodic content was crossed and balanced. Functional magnetic resonance imaging data showed that the neural decoding of speech and melodies depends on activity patterns in left and right auditory regions, respectively. This asymmetry is supported by specific sensitivity to spectrotemporal modulation rates within each region. Our results suggest a match between acoustical properties of communicative signals and neural specializations adapted to that purpose. (Abstract excerpt)

To what extent does the perception of speech and music depend on different mechanisms in the human brain? What is the anatomical basis underlying this specialization? Albouy et al. created a corpus of a cappella songs that contain both speech (semantic) and music (melodic) information and degraded each stimulus in either the temporal or spectral domain. Brain scanning revealed a right-left asymmetry for speech and music. Classification of speech content occurred exclusively in the left auditory cortex, whereas classification of melodic content occurred only in the right auditory cortex. (Editor)

Earth Life > Integral Persons > Conscious Knowledge

Models of Consciousness Conference. models-of-consciousness.org. A site for a September 2019 meeting at Oxford University on formal approaches to the mind-matter relation. A full book of Abstracts is available here. As the Summary says, it has become evident that studies of human sentience have gained a valid, brain-based, mathematic trace and credibility so they should rightly be a subject for academic erudition. A premier cadre such as Roger Penrose, Adam Barrett, Adrian Kent, Ian Durham, Peter Grindrod, and Tim Palmer (search for paper review) out of 37 presenters covered across a wide expanse. A leading topic and basis was Integrated Information Theory, see W. Marshall below, along with statistical physics, quantum phenomena, cognitive aspects and more.

Consciousness and its place in nature has been a great mystery for human beings and has been the focus of philosophical and religious investigations for millennia. Lately the subject has generated a worldwide interest among mathematicians, physicists, and others who aim to translate the results of quantifiable investigations into forma models. To date, a good part of this work has been pursued in isolation and outside of the academic mainstream. The aim of this conference is to begin to foster broad collaborations and the exchange of ideas between diverse researchers and theories. (Summary)

Integrated Information Theory: From Phenomenal to Physical: The dominant approach in consciousness science is to identify the neural activity which correlates with specific experiences. However, many have argued that its subjective nature makes it difficult to do this. Integrated information theory takes a different approach, starting from consciousness itself to identify essential properties, and then postulate what sort of physical substrate could support it. (William Marshall, Brock University, UK)

Earth Life > Integral Persons > Conscious Knowledge

Cleeremans, Axel, et al. Learning to be Conscious. Trends in Cognitive Sciences. December, 2019. As the abstract cites, a “meta-representation” is a “second-order” stage of a brain’s conceptual content so that a person can know that they know. Eight Free University of Brussels cognitive psychologists conceive a synthesis akin to integrated information theory such that the more someone gains vital knowledge, the more actively aware s/he becomes. In regard, by a mega-historic view we might refer to the “Great Learning” of Chinese tradition (Sterckx, Roel) and our 21st century sapiensphere to get a retrospective upon our grand Earthly and cosmic endeavor of sentient self-realization.

Different theories of consciousness have proposed many mechanisms to account for phenomenal experience. Here, appealing to aspects of global workspace theory, higher-order theories, social theories, and predictive processing, we introduce a novel framework: the self-organizing meta-representational account (SOMA), in which consciousness is viewed as something that the brain learns to do. By this account, the brain continuously and unconsciously learns to redescribe its own activity to itself, so developing systems of first-order representations. In this sense, consciousness is the brain’s (unconscious, embodied, enactive, nonconceptual) theory about itself. (Abstract)

Earth Life > Integral Persons > Conscious Knowledge

Kleiner, Johannes and Sean Tull. The Mathematical Structure of Integrated Information Theory. arXiv:2002.07655. As another example of how these malleable IIT insights have gained much employ, University of Munich and Oxford University postdoc computational scholars scope out a generalization so as to give it even broader veracity. See also a companion paper Integrated Information in Process Theories at 2002.07654.

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution, we propound the mathematical structure of the theory, separating the essentials from auxiliary formal tools. We provide a definition of a generalized IIT which has IIT 3.0 of Tononi et al, as well as the Quantum IIT introduced by Zanardi et. al. as special cases. This provides an axiomatic definition of the theory which may serve as the starting point for future investigations and as an introduction for new researchers. (Abstract)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next