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Biological Relevance of Network Architecture

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GeNeDis 2016

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 988))

Abstract

Mathematical representations of brain networks in neuroscience through the use of graph theory may be very useful for the understanding of neurological diseases and disorders and such an explanatory power is currently under intense investigation. Graph metrics are expected to vary across subjects and are likely to reflect behavioural and cognitive performances. The challenge is to set up a framework that can explain how behaviour, cognition, memory, and other brain properties can emerge through the combined interactions of neurons, ensembles of neurons, and larger-scale brain regions that make information transfer possible. “Hidden” graph theoretic properties in the construction of brain networks may limit or enhance brain functionality and may be representative of aspects of human psychology. As theorems emerge from simple mathematical properties of graphs, similarly, cognition and behaviour may emerge from the molecular, cellular and brain region substrate interactions. In this review report, we identify some studies in the current literature that have used graph theoretical metrics to extract neurobiological conclusions, we briefly discuss the link with the human connectome project as an effort to integrate human data that may aid the study of emergent patterns and we suggest a way to start categorizing diseases according to their brain network pathologies as these are measured by graph theory.

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Notes

  1. 1.

    Luis Joshua Salés, “Maximos and Neurobiology: A Neurotheological Investigation of Asceticism as Erosion of the Passions and the Gnomic Will,“Holodny Prize Recipient for most outstanding pre-professorial presentation, Sophia Institute Conference: New York, NY (December, 2013).

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Authors and Affiliations

  1. Department of Mathematics, East Carolina University, 124 Austin Building, East Fifth Street, Greenville, NC, 27858-4353, USA

    Ioannis Gkigkitzis

  2. Department of Physics and Computer Science, Wilfrid Laurier University, Science Building, Room N2078, 75 University Ave. W., Waterloo, ON, Canada, N2L 3C5

    Ioannis Haranas & Ilias Kotsireas

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    Panayiotis Vlamos

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Gkigkitzis, I., Haranas, I., Kotsireas, I. (2017). Biological Relevance of Network Architecture. In: Vlamos, P. (eds) GeNeDis 2016. Advances in Experimental Medicine and Biology, vol 988. Springer, Cham. https://doi.org/10.1007/978-3-319-56246-9_1

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