VII. Our Earthuman Ascent: A Major Evolutionary Transition in Twndividuality

2. Systems Neuroscience: Multiplex Networks and Critical Function

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.

Bertolero, Maxwell and Danielle Bassett. On the Nature of Explanations Offered by Network Science: A Perspective from and for Neuroscientists. arXiv:1911.05031. In this paper to appear in a special issue of Topics in Cognitive Science, University of Pennsylvania neuroscientists post an illustrated tutorial on the latest research about how our cerebral activities are based on and empowered by myriad, scintillating, multiplex neural nets. What began as patchy rudiments around 2010 has now become a whole-scale theoretical and experimental explanation from nodal neurons to an infinity of relational linkages. Altogether dubbed a connectome, as 2020 nears we human beings are finding ourselves to truly be an exemplary micro-universe. See also Discovering the Computational Relevance of Brain Network Organization by Takuya Ito, et al in Trends in Cognitive Science (online November 2019).

Network neuroscience represents the brain as a collection of regions and inter-regional connections. By this ability, the approach has generated unique explanations of neural function and behavior. Here we complement formal philosophical efforts by providing an applied perspective. In doing so, we rely on philosophical work concerning the role of causality, scale, and mechanisms in scientific explanations. We hope to provide a useful framework in which can be exercised across scales and combined with other fields of neuroscience to gain deeper insights into the brain and behavior. (Abstract excerpt)

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 mathematical complexity, architecture and process which repeats in kind across many neural, metabolic, genetic and communal domains. Herein a deep affinity is reported between genomic and cerebral instantiations and their resultant informative 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)

Betzel, Richard. Network Neuroscience and the Connectomics Revolution. arXiv:2010.01591. An Indiana University neuroscientist (search) provides a concise tutorial for the revolutionary 2010s advance that our cerebral endowment displays an epitome of the nature’s universal multiplex, webby, informative topologies and dynamics. Since this cerebral anatomy and physiology is based on and is akin to genetic systems, it has been given an –omics identity (search S. Seung).

Connectomics and network neuroscience offer quantitative scientific frameworks for modeling and analyzing networks of structurally and functionally interacting neurons, neuronal populations, and macroscopic brain areas. This shift in perspective and emphasis on distributed brain function has provided deep insight into the role played by the brain's network architecture in cognition, disease, development, and aging. In this chapter, we review the core concepts of human connectomics at the macroscale. From the construction of networks using functional and diffusion MRI data, to their analysis using network neuroscience methods, so as to highlight key findings, common procedures, and emerging frontiers. (Abstract)

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)

Betzel, Richard, et al. Multi-Scale Community Organization of the Human Structural Connectome and its Relationship with Resting-State Functional Connectivity. Network Science. 1/3, 2013. As an ascendant planetary progeny proceeds to quantify, explain and discover a genesis universe, in this new Cambridge online journal, a team from Indiana University and the University of Lausanne, including Olaf Sporns, offer a capsule of current progress. The paper opens by citing how a decade of studies of natural network phenomena have led to the distillation of an independent, universally applicable, description. In regard, human brains, via intricate, scintillating connections, can be seen as a premier exemplar. So we peoples do indeed possess an archetypal microcosm of this macro cosmome. Compare with Tognoli, Tononi, Rubinov, many other entries as they verge on a grand synthesis.

The human connectome has been widely studied over the past decade. A principal finding is that it can be decomposed into communities of densely interconnected brain regions. Past studies have often used single-scale modularity measures in order to infer the connectome's community structure, possibly overlooking interesting structure at other organizational scales. In this report, we used the partition stability framework, which defines communities in terms of a Markov process (random walk), to infer the connectome's multi-scale community structure. Comparing the community structure to observed resting-state functional connectivity revealed communities across a broad range of scales that were closely related to functional connectivity. This result suggests a mapping between communities in structural networks, models of influence-spreading and diffusion, and brain function. It further suggests that the spread of influence among brain regions may not be limited to a single characteristic scale. (Abstract)

Bolt, Eric, et al. Fractal Basins as a Mechanism for the Nimble Brain. arXiv:2311.00061. Clarkson University, University of Sau Paolo, and Wake Forest University (Paul Laurenti) provide more quantified reasons by which to perceive our deft, swift cerebral facility as a self-similar, self-organized criticality.

A distinctive feature of the brain is its ability to respond to disparate sensory signals in unique ways depending on the environmental context. In dynamical systems, this is known as a multi-stability which can switch between stable phases of brain activity/connectivity. In this article, we describe chimera states of synchrony and incoherence in brain-inspired networks. We introduce the Vector Pattern State (VPS) as an efficient way of identification and show that coexisting attractors of such states reveal intricately "mingled" fractal basin boundaries. We propose that such conditions could explain the brain's rapidly balance these reciprocal options. (Abstract)

Bota, Mihail, et al. From Gene Networks to Brain Networks. Nature Neuroscience. 6/8, 2003. A proposal to apply similar techniques used in the study of the genome to comprehend neural processes. A prototype Brain Architecture Knowledge Management System is described akin to bioinformatics to help sort out nomenclature issues and to express their dynamic interconnections.

Botvinick, Matthew. Hierarchical Models of Behavior and Prefrontal Function. Trends in Cognitive Sciences. 12/5, 2007. The Princeton psychologist in this article, and others accessible from his website, professes an isomorphic alignment between behavioral scales and their neural representation as mind and active manifestation come to mirror each other.

Breakspear, Michael and Cornelis Stam. Dynamics of a Neural System with a Multiscale Architecture. Philosophical Transactions of the Royal Society B. 360/1051, 2005. Based on extensive neuroimaging studies of cerebral connectivity, the human brain is found to be arranged as a nest of self-similar modules and interactive networks. This composition is said to reflect nature’s newly discovered universal scaling laws. By these advances, one can add that human brains appear to exhibit the same pattern and process as life’s evolutionary genesis and the organic universe from which they emerge. A significant paper.

The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales – neurons, minicolumns, cortical columns, functional brain regions, and so on. (1051) A multiscale hierarchy of such neuronal ensembles – with interdependences between scales – is then constructed using the wavelet transform…this yields a hierarchy of neuronal systems whose spatial scales are geometrically nested… (1052)

Buckner, Randy and Fenna Krienen. The Evolution of Distributed Association Networks in the Human Brain. Trends in Cognitive Sciences. 17/12, 2013. In work noted by the New York Times as “In the Human Brain, Size Really Isn’t Everything” (December 26, 2013), Harvard University and Massachusetts General Hospital neuroscientists propose that as earlier, rudimentary neural architectures became “untethered,” this allowed more complex connective topologies to form in primate and homo sapiens brains. A volumetric increase is not enough, an increasingly intricate “connectome” makes the difference. And of further importance, as per the quote, neural evolution is seen in an embryonic way as a expansive deployment from an original archetypal geometry.

The inherited constraints of development and the general plan, or Bauplan, of the brain are powerful limiters on how neural circuits can evolve across generations. Here we raise the possibility that critical features of the association cortex, linked to size scaling, may contribute to the human brain’s extraordinary capabilities. The central idea is that a distributed form of circuit may have become increasingly prominent when ancient rules of development were expressed in an expanding cortical mantle. The possibility that simple mechanisms play a major role in recent brain evolution is comforting because it demystifies the gap between our brain’s capabilities and those of our ancestors. (661-662)

Bullmore, Edward, et al. Generic Aspects of Complexity in Brain Imaging Data and other Biological Systems. Neuroimage. 47/3, 2009. University of Cambridge, NIH, and University of Melbourne neuroscientists, as the extended quotes aver, contend that after a decade of intensifying progress in endeavors to view neural anatomy and activity as an iterative, emergent self-organization, as every other domain of life and society has done also, that a universality of such similar kind can be admitted and appreciated. Upon reflection, this is huge for we are now invited to realize in our midst an epochal worldwide discovery of an untangled, comprehensible nature, arising from and manifestly representing a true universe to human genesis.

A key challenge for systems neuroscience is the question of how to understand the complex network organization of the brain on the basis of neuroimaging data. Similar challenges exist in other specialist areas of systems biology because complex networks emerging from the interactions between multiple non-trivially interacting agents are found quite ubiquitously in nature, from protein interactomes to ecosystems. We suggest that one way forward for analysis of brain networks will be to quantify aspects of their organization which are likely to be generic properties of a broader class of biological systems. In this introductory review article we will highlight four important aspects of complex systems in general: fractality or scale-invariance; criticality; small-world and related topological attributes; and modularity. (Abstract, 1125)

However, it is becoming increasingly clear that complexity may be a characteristic of biological systems in general; and that some of the same mathematical tools and concepts can appropriately be used to quantify and compare aspects of complexity in substantively very diverse systems. To take a single, illustrative example in brief; many complex systems have been shown to have a modular or nearly-decomposable organization, including systems as different as the human brain transcriptome, the global air transportation network, and ecological or economic networks. (1126)

The important generalization is that one way forward in dealing with the formidable complexity of the human brain may be to recognize that certain key principles of its organization are shared in common with other complex systems in biology and elsewhere. This idea that both brain and biological systems may have generic properties in common is one implication of the more general universality hypothesis: that certain network organizing principles are highly conserved and more-or-less universally instantiated in real-life networks. Studies addressing network organization have proliferated recently in an interdisciplinary research area, which is driven largely by technical developments in statistical physics and has begun to demonstrate a startling degree of commonality in the organization of substantively distinct complex systems. (1126)

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