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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Life’s Cerebral Cognizance Becomes More Complex, Smarter, Informed, Proactive, Self-Aware

B. A Neural Encephalization from Minimal Stirrings to an Earthuman Cognizance

Kaas, Jon, editor-in-chief. Evolution of Nervous Systems. Amsterdam: Elsevier/Academic Press, 2nd edition, 2016. An authoritative encyclopedia with these 4 volumes: Theories, Development, Invertebrates; Non-Mammalian Vertebrates; Mammals; and Primates. Its especial value is to cover, as the publisher avers, every aspect of how life evolved from original sensation through the ramifying Metazoa to our human cerebral neocortex. And one might add, as our humankinder phase views retrospectively from which we all came, the ascendant course well seems as a single cognitive gestation.

Evolution of Nervous Systems, Second Edition is a unique, major reference for evolution and nervous systems. All animals mediate their behaviors, many of them species specific, yet these sensory abilities all evolved from a common, simpler ancestor. In the first edition, over 100 distinguished neuroscientists assembled the current state-of-the-art knowledge on how nervous systems have evolved throughout the animal kingdom. This second edition remains rich in detail and broad in scope, outlining the changes in brain and nervous system organization that occurred from the first invertebrates and vertebrates, to fishes, reptiles, birds, mammals, and primates, including humans. The book also includes fully updated chapters and new content on developments in the field. (Publisher)

Kaas, Jon, editor-in-chief. Evolutionary Neuroscience. Amsterdam: Academic Press, 2009. The 1,000 page compendium could be seen as an evolutionary event in itself as decades of international brain research studies reach a mature confluence. Four parts: An Introduction to History, Theory, Methods and Concepts; The Evolution of Brains in Early Vertebrates, Fishes, Amphibians, Reptile and Birds; and Evolution of Mammalian Brains; and Primate Brain Evolution, explain an ancient developmental enchepalization from pre-Cambrium creatures to regnant human beings. A lead chapter “History of Ideas on Brain Evolution” by Georg Striedter introduces major themes that can now be gleaned from this achievement (search also Cela-Conde herein). Other notable chapters are “The Evolution of Vocal Learning Systems in Birds and Humans” by Erich Jarvis, “How can Fossils Tell us About the Evolution of the Neocortex?” by Harry Jerison, and “The Evolution of Language Systems in the Human Brain” by Terrence Deacon.

A deep homology of characters and forms is thus traced to life’s earliest stirrings, along with a persistent convergence of neural circuits, modules, sensory faculties, and so on. The old scale from simple to complex is again set aside for “stunning” intricacies much in place from the outset. It is also necessary to factor in “developmental constraints” prior to and rather than natural selection alone. A manifold biological diversity abounds, along with and around a generic cerebral anatomy. Later animal kingdoms appear as ramifications of an original “urbilaterian” neural Bauplan. Altogether, as evidence builds, life’s long ascent, now filled in a century on, appears as a singular embryogenesis.

Kaiser, Marcus and Sreedevi Varier. Evolution and Development of Brain Networks: From Caenorhabditis elegans to Homo sapiens. Network: Computation in Neural Systems. 22/1-4, 2011. Within our humankind cerebral and cognitive vista, Newcastle University and Seoul National University neuroscientists fill in and report upon this common, concerted and mosaic, evolutionary development that these collective faculties have arisen from. May one then wonder what kind of a reality seeks to create and accomplish, some billions of years on, its own consciously perceived reconstruction and witness? Whom is learning this and for what great discovery and purpose?

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. ‘Small-world’ topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints. (143)

In conclusion, the network architecture becomes more complex both during development and evolution going from a diffuse lattice organization to hierarchical modular networks. Over time, parts of the network specialize leading to network modules and later to multiple hierarchical levels. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints, like those influencing hub formation, long-distance connections and modular organization. (145)

Kandel, Eric, et al. Principles of Neural Science. New York: Plenum, 2000. An encyclopedic text on every aspect of brain and nervous system structure and function.

Karten, Harvey. Vertebrate Brains and Evolutionary Connectomics: On the Origins of the Mammalian Neocortex. Philosophical Transactions of the Royal Society B. 370/0060.2015, 2015. The veteran UC San Diego neurophysician continues his flow of findings that while animal classes differ, persistent commonalities can be discerned by the latest sophisticated analysis, aka cerebral connectomics over time. See Morphological Evolution of the Vertebrate Forebrain: From Mechanical to Cellular Processes by Francisco Aboitiz and Juan Montiel (herein) in Evolution & Development (21/6, 2019) for similar confirmations.

Kazemian, Majid, et al. Evidence for Deep Regulatory Similarities in Early Developmental Programs across Highly Diverged Insects. Genome Biology and Evolution. 6/9, 2014. In this online Oxford journal, University of Illinois and SUNY Buffalo researchers provide another witness from this arthropod phylum of anatomical features in place from their very onset.

Our results argue strongly that despite extensive binding site turnover and overall sequence divergence, similar regulatory mechanisms govern developmental gene expression even over distances of >350 Myr, and suggest that gene regulatory networks have been directly conserved. (2317)

Kennedy, Henry and Colette Dehay. Self-Organization and Interareal Networks in the Primate Cortex. Hofman, Michel and Dean Falk, eds. Evolution of the Primate Brain: From Neuron to Behavior. Amsterdam: Elsevier Science, 2012. In this chapter, University of Lyon, Stem Cell and Brain Research Institute, neuroscientists open another window on how the brain manages and proceeds to organize its cognitive anatomy. Search Hofman for the whole volume.

Variability of gene expression of cortical precursors may partially reflect the operation of the gene regulatory network and determines the boundaries of the state space within which self-organization of the cortex can unfold. In primates, including humans, the outer subventricular zone (OSVZ), a primate-specific germinal zone, generates a large contingent of the projection neurons participating in the interareal network. The number of projection neurons in individual pathways largely determines the network properties as well as the hierarchical organization of the cortex. Mathematical modeling of cell-cycle kinetics of cortical precursors in the germinal zones reveals how multiple control loops ensure the generation of precise numbers of different categories of projection neurons and allow partial simulation of cortical self-organization. We show that molecular manipulation of the cell-cycle of cortical precursors shifts the trajectory of the cortical precursor within its state space, increases the diversity in the cortical lineage tree and explores changes in phylogenetic complexity. These results explore how self-organization underlies the complexity of the cortex and suggest evolutionary mechanisms. (Abstract)

Kishikawa, Kiisa. Evolutionary Convergence in Nervous Systems: Insights from Comparative Phylogenetic Studies. Brain, Behavior and Evolution. 59/5-6, 2002. A persistently convergent evolution in many anatomical and cerebral domains is now realized to be quite widespread.

Over the past 20 years, cladistic analyses have revolutionized our understanding of brain evolution by demonstrating that many structures, some of which had previously been assumed to be homologous, have evolved many times independently. These and other studies demonstrate that evolutionary convergence in brain anatomy and function is widespread……One reason that convergence is so common in the biological world may be that the evolutionary appearance of novel functions is associated with constraints, for example in the algorithms used for a given neural computation. Convergence in functional organization may thus reveal basic design features of neural circuits in species that possess unique evolutionary histories but use similar algorithms to solve basic computational problems. (240)

Kording, Konrad. Bayesian Statistics: Relevant for the Brain? Current Opinion in Neurobiology. 25/130, 2014. In a special issue on Theoretical and Computational Neuroscience, a Northwestern University biophysicist advocates this approach which is lately coming into use across the sciences for optimal choices from a population of options. A best or sufficient bet is achieved by according new experience and/or responses with prior learned memory. For example, Richard Watson, et al (search 2014) proposes life’s evolution as proceeding this way. See also Automatic Discovery of Cell Types and Microcircuitry from Neural Connectomics by Kording and Eric Jonas at arXiv:1407.4137. The whole issue of some 32 articles, e.g. by Adrienne Fairhall, Stanislav Dehaene, and Leslie Valiant, is a significant entry to an endeavor by worldwise humanity to reveal the creaturely cerebration that brought me and We to be. With “connectome” often cited, the papers seem as if they could equally apply to genomes. Might a better term be a “neurome” equivalent?

Bayesian statistics can be seen as a model of the way we understand things. Our sensors are noisy and ambiguous as several worlds could give rise to the same sensor readings. We therefore have uncertainty in our data and cannot be certain which model or hypothesis we should believe in. However, we can considerably reduce uncertainty about the world using previously acquired knowledge and by interpreting data across sensors and time. As new data comes in, we update our hypotheses. Bayesian statistics is the rigorous way of calculating the probability of a given hypothesis in the presence of such kinds of uncertainty. With Bayesian statistics, previously acquired knowledge is called prior, while newly acquired sensory information is called likelihood. (130)

Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a nonparametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists, including connectivity, cell body location and the spatial distribution of synapses, in a principled and probabilistically-coherent manner. (arXiv Abstract)

Kverkova, Kristina, et al. The Evolution of Brain Neuron Numbers in Amniotes. PNAS. 119/11, 2022. Charles University, Prague paleo-neuroscientists deftly reconstruct the evolution of brain neuron number across an entire range of Metazoa species and found that after fish and reptiles, birds and mammals have much larger quantities in cerebral areas meant for higher cognition. It is noted that several major changes in neuron brain scaling in the past 300 million years indeed appear to be oriented to an increasing degree of intelligence. The group effort has achieved the strongest evidence to date of how life’s emergent sensory stirrings can be known to have this central edification. The paper has vivid illustrations of relative creaturely advances in body and brain anatomies, which well evince a grand learning experience.

A reconstruction of the evolution of brain information-processing capacity is vital to understandings the rise of complex cognition. Comparative studies long used brain size as a proxy. However, to get a better sense of paths leading to high intelligence, power, we need to compare brains by large datasets of computational neurons. We find Amniote brain evolution to be tracked by four major shifts in neuron–brain scaling. The most dramatic increases in brain neurons occurred independently with the appearance of birds and mammals. The other two rises in neuron numbers happened in core land birds and anthropoid primates, known for their cognitive prowess. (Abstract excerpt)

Amniota, a group of limbed vertebrates that includes reptiles, birds, mammals and their extinct ancestors. The amniotes are the evolutionary branch (clade) of the tetrapods in which the embryo develops within a set of protective extra-embryonic membranes—the amnion, chorion, and allantois.

Lacalli, Thurston. An Evolutionary Perspective on Chordate Brain Organization and Function. Philosophical Transactions of the Royal Society B. December, 2021. In this Systems Neuroscience and Evolutionary Theory issue, a veteran University of Victoria, BC neurobiologist (see website) posts a definitive retrospect to date of how a group social sapience can now be consistently traced all the way back to its earliest invertebrate rudiments. But by a unique turn from that origin, the author traces an advent and advance of relative sentience and consciousness as it stirs and knows through vertebrate forms and scales. Contrary to random models, we want to record that a central axis, a vectorial progression, to our people selves in community does in fact exist. In regard, when warlords “think with tanks,” such collective findings of a long walk and talk course need gain wider appreciation. Isaac Newton found this oldest journal in the 1660s, has anything at last been learned since to save us?

The similarities between amphioxus and vertebrate brains, in their regional subdivision, cell types and circuitry, can provide a deep relativity over this evolutionary span. Mobility controls were already well developed in basal chordates. But amphioxus did not yet have complex sense organs. Vertebrate development thus involves their progressive improvement in two main aspects: anatomical and neurocircuitry innovations in the sense organs and the occasion of sentient consciousness. (Abstract excerpt)

Chordate possess synapomorphies, or primary characteristics, during their larval or adulthood stages which include a notochord, dorsal hollow nerve cord, endostyle or thyroid, pharyngeal slits, and a post-anal tail. Chordates are bilaterally symmetric, have a circulatory system, and metameric segmentation. Amphioxus consist of species of "fish-like" benthic filter feeding chordates. (Wikipedia)

Laughlin, Simon and Terrence Sejnowski. Communication in Neuronal Networks. Science. 301/1870, 2003. The article reports on a linear relation between cortical white and grey matter for 59 mammalian species expressed by a power law which spans five orders of magnitude from the pygmy shrew to the elephant.

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