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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 76 through 90 of 115 found.


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

Earth Life > Genetic Info

Miranda-Dominguez, Oscar, et al. Heritability of the Human Connectome. Network Neuroscience. 2/2, 2018. In an issue on New Trends in Connectomics, Oregon Health and Science University and Emory University behavioral neuroscientists propose a familial “connectotype” akin to a bodily phenotype to likewise represent a person’s cerebral endowment. In a similar way, ancestral histories can then be traced.

Earth Life > Genetic Info

Nussimov, Ruth, et al. Protein Ensembles Link Genotype to Phenotype. PLoS Computational Biology. June, 2019. National Cancer Institute researchers contribute a latest insight into how genetic phenomena proceeds to actively inform and array into evolving organisms. Rather than a prior one gene to one trait, now mostly set aside, it is “ensembles” of biochemical generative guidance which are the pathway by which life forms and vivifies itself. See also The Energy Landscapes of Biomolecular Function by Nussimov and Peter Wolynes in Physical Chemistry Chemical Physics (16/6321, 2014) for a setup piece.

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods from genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene actually encodes ensembles of conformations. A dynamic ensemble view can better reveal the linkage between genetic change and observable physical or biochemical features. An ensemble view, rather than the genotype–phenotype paradigm, clarifies how even small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function. (Abstract excerpts)

The terms genotype and phenotype have been in use at least since the turn of the last century. Genotype has been defined as the genetic makeup of an organism or of a specific characteristic. Phenotype has been construed as the composite of the organism’s observable characteristics or traits, such as morphology, development, biochemical, and physiological properties. Classically, the genotype of an organism has been described as the inherited genetic material coding for all processes in the organism’s life. (1)

Earth Life > Genetic Info > DNA word

Eetemadi, Ameen and Ilias Tagkopoulos. Genetic Neural Networks: An Artificial Neural Network Architecture for Capturing Gene Expression Relationships. Bioinformatics. 35/13, 2019. We cite this entry by UC Davis computer scientists to show how readily these popular analytic methods seem to find similar application everywhere, even in this case so as to parse life’s heredity. Could commonality infer that brains and genomes and all else are deeply cerebral, information bearing, relative aware in kind?

Results: We present the Genetic Neural Network (GNN), an artificial neural network for predicting genome-wide gene expression given gene knockouts and master regulator perturbations. In its core, the GNN maps existing gene regulatory information in its architecture and it uses cell nodes that have been specifically designed to capture the dependencies and non-linear dynamics that exist in gene networks. Our results argue that GNNs can become the architecture of choice when building predictors of gene expression from the growing corpus of genome-wide transcriptomics data.

Earth Life > Genetic Info > Genome CS

Verd, Berta, et al. Modularity, Criticality, and Evolvability of a Developmental Gene Regulatory Network. eLife. 8/e43832, 2019. In a highly technical, well referenced, 38 page entry, Barcelona Institute of Science and Technology systems biologists BV, Nick Monk, and Johannes Jaeger (search) identify and describe how these title features are prime functions of dynamic genetic nucleotides and networks. In regard, the presence of genome community modules, along with critically poised responses, offers another instantiation of nature’s archetypal complex cosmome to connectome system.

The existence of discrete phenotypic traits suggests that the complex regulatory processes which produce them are functionally modular and are usually represented by networks. Only modular networks can be partitioned into intelligible subcircuits able to evolve independently. Here we partition an experimentally tractable regulatory network—the gap gene system of dipteran insects. We show that this system, although not structurally modular, is composed of dynamical modules driving different aspects of whole-network behaviour. All these subcircuits share the same regulatory structure, but differ in components and sensitivity to regulatory interactions. Some subcircuits are in a state of criticality, which explains the differential evolvability of the various features in the system. (Abstract excerpt)

Earth Life > Integral Persons > Somatic

Altan-Bonnet, Gregoire, et al. Quantitative Immunology for Physicists. arXiv:1907:03891. G A-B, National Cancer Institute, USA, with Thierry Mora and Aleksandra Walczak, Sorbonne University, Paris post a 78 page, 328 reference advanced synthesis of life’s immune systems by way of generic complex network dynamics. Thus in one more candidate realm, nature’s universal nonlinear self-viabilities are found to be similarly in effect. Search Albert Tauber for prior glimpses of this manifest exemplar.

The adaptive immune system is a dynamical, self-organized multiscale system that protects vertebrates from both pathogens and internal irregularities, such as tumours. For these reason it fascinates physicists, yet the multitude of different cells, molecules and sub-systems is often also petrifying. Despite this complexity, as experiments on different scales of the adaptive immune system become more quantitative, many physicists have made both theoretical and experimental contributions that help predict the behaviour of ensembles of cells and molecules that participate in an immune response. Here we review some recent contributions with an emphasis on quantitative questions and methodologies. We also provide a more general methods section that presents some of the wide array of theoretical tools used in the field. (Abstract)

Earth Life > Integral Persons > Somatic

Bonzanni, Mattia, et al. On the Generalization of Habituation. BioEssays. 41/7, 2019. With a Novel Model of Habituation that is Independent of any Biological System subtitle, Tufts University, Allen Discovery Center, biomedical engineers including Michael Levin offer notices and explanations of how an entity becomes accustomed to their daily environs is a common occurrence across nature and society. A commentary, Describing Atypical Instances of Intelligence by Fred Keijzer in the same issue, appreciates its content.

Habituation, a form of non‐associative learning, is no longer studied exclusively within psychology and neuroscience. Indeed, the same stimulus–response pattern has now been observed at the molecular, cellular, and organismal scales. Hence, a more inclusive theory is required to accommodate aneural forms. Here an abstraction of the habituation process that does not rely upon particular biological pathways or substrates is presented. Its formulation can be applied to interrogate systems as they respond to several stimulation paradigms, providing new insights and supporting existing behavioral data. The results suggest that habituation serves as a general biological strategy that any system can implement to adaptively respond to harmless, repetitive stimuli. (Abstract)

Earth Life > Integral Persons > Somatic

Dahmen, David, et al. Second Type of Criticality in the Brain Uncovers Rich Multiple-Neuron Dynamics. Proceedings of the National Academy of Sciences. 116/13051, 2019. Julich Research Center, Germany neuroresearchers at once confirm a cerebral tendency to settle at this optimum state, while teasing out another neural way that brains avail this productive balance.

Parallel recordings of motor cortex show weak pairwise correlations on average but a wide dispersion across cells. This observation runs counter to the prevailing notion that optimal information processing requires networks to operate at a critical point, entailing strong correlations. We here reconcile this apparent contradiction by showing that the observed structure of correlations is consistent with network models that operate close to a critical point of a different nature than previously considered: dynamics that is dominated by inhibition yet nearly unstable due to heterogeneous connectivity. Our findings provide a different perspective on criticality in neural systems: network topology and heterogeneity endow the brain with two complementary substrates for critical dynamics of largely different complexities. (Significance)

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

Christianson, Nicolas, et al. Architecture and Evolution of Semantic Networks in Mathematics Texts. arXiv:1908.04911. University of Pennsylvania bioneuroengineers NC, Ann Blevins, and Danielle Bassett, with many colleagues, continue to parse the presence of node/link multiplex geometries as they become evident in every natural and social milieu. In this instance, even textual script and its educational content is found to be distinguished. In August 2019, we can report an increasing realization that such a singular, iconic physiology and anatomy is vitally present everywhere. A graphic core-periphery array is depicted with dense inner and sparse outer areas, while another figure cites the same Betti (search) mathematics used to analyze clusters of galaxies. See also The Network Architecture of the Human Brain is Modularly Encoded in the Genome by this team (Bertolero, May 2019). From school books to cerebral faculties and onto to quantome and cosmome phases, a natural genesis is graced by the one, same, ultimately bigender icon.

Knowledge is a network of interconnected concepts. Yet, how the topological structure of knowledge constrains its acquisition remains unknown, hampering the development of learning enhancement strategies. Here we study topological semantic networks reflecting mathematical concepts and their relations in college- linear algebra texts. We find that the networks exhibit strong core-periphery architecture, where a dense core of concepts presented early is complemented with a sparse periphery evenly throughout the exposition. Using tools from applied topology, we find that the expositional evolution of the semantic networks produces and fills knowledge gaps. Broadly, our study lays the groundwork for optimal design principles for textbook teaching in a classroom setting. (Abstract excerpt)

Knowledge has been distilled into formal representations for millennia. Such efforts have sought to explain human reasoning and support artificial reasoning. Semantic networks organize information by detailing concepts (nodes) and their relations (edges), which can be defined by inclusion in the same thesaurus entry, free word association data, or co-occurrence within a corpus of text. Concept maps reflect information in a similar manner, and therefore can be used to evaluate comprehension and identify topics that are most difficult to connect to other concepts. With the capacity to construct semantic networks, and similar formal representations of knowledge comes the challenge of distilling rules and mechanisms of knowledge formalization and acquisition. (1)

Earth Life > Integral Persons > Cerebral Form

Pospelov, Nikita, et al. Spectral Peculiarity and Criticality of a Human Connectome. Physics of Life Reviews. Online June 16, 2019. Six Russian neurotheorists based at Lomonosov Moscow State University describe novel techniques and insights which adds more evidence that our hyperactive brains are truly situated at an optimum critically poised state.

We have performed the comparative spectral analysis of structural connectomes for various organisms using open-access data. We found that the spectral density of adjacency matrices of human connectome has maximal deviation from randomized networks, compared to other organisms. We discovered that for macaque and human connectomes the conservation of local clusterization is crucial, while for primitive organisms the conservation of averaged clusterization is sufficient. We found that the level spacing distribution of the spectrum of human connectome Laplacian matrix corresponds to the critical regime. This observation provides strong support for debated statement of the brain criticality. (Abstract)

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

Tadic, Bosiljka, et al. Functional Geometry of Human Connectomes. Nature Scientific Reports. 9/12060, 2019. Jozef Stefan Institute, Ljubljana, Slovenia systems physicists (search BT) and a Wilfrid Laurier University, Waterloo, Canada mathematician apply sophisticated network theories to cerebral studies via an expansion to and emphasis upon inherent, generative topologies, aka simplical complexes (Bianconi). In regard, they serve to inclusion of previously unnoticed patterns and processes, which in this neural instance reveals a deeper degree of intra- and inter-hemispheric connectivities. Building on a Hungarian brain atlas (Szalkai), neuroimages of equal male and female subjects finds that women’s brains possess a denser intricacy, as the quotes note. See also Hidden Geometries in Networks Arising from Cooperative Self-Assembly by Mulovan Suvakov, et al in this journal (8/1987, 2018).

Mapping brain imaging data to networks, where nodes represent anatomical regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. (Abstract)

To summarise, our study reveals how the functional geometry of human connectome can be expressed by higher-order connectivity, simplicial complexes and induced cycles. This kind of structure is built into the anatomical communities of the brain at the mesoscopic scale in both hemispheres. In this context, new topological measures of the consensus networks quantifies the perceptive differences between connectomes. Specifically, in the studied female and male consensus connectomes, a part of connections is more natural to invoke in the female than in the male brain, where much more fibres need to be launched to identify them. Whereas the other fraction of such connections consists of edges that appear exclusively in the consensus female connectome, they have not been identified in the consensus male connectome. (9)

Earth Life > Integral Persons > Complementary Brain

Vingerhoets, Guy. Phenotypes in Hemispheric Functional Segregation. Physics of Life Reviews. Online June, 2019. A Ghent University neuropsychologist contributes an advanced explanation for life’s cerebral, cognitive allotment into complementary, near/far, below/above, dense/sparse reciprocities. See also a commentary Hemispheric Functional Segregation as By-products of the Evolution of Lateralization Population Structure by Giorgia Vallortigara.

Directional hemispheric dominance has been established for numerous cognitive functions in the human brain. Strong population biases with some functions favoring the left and others the right hemisphere generated the popular idea of an advantageous prototypical division of labor, molded by evolution and genetically blueprinted. As most lateralization studies focused on a single function at a time, little is known about the relation between asymmetric and atypical segregation in healthy individuals. I summarize the literature about behavioral and neural consequences and the evidence for intermediate phenotypes in brain functional segregation that could bridge behavioral and genetic data. (Abstract)

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)

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