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5.18 - Brain Networks and Dysconnectivity

from 5 - Neural Circuits

Published online by Cambridge University Press:  08 November 2023

Mary-Ellen Lynall
Affiliation:
University of Cambridge
Peter B. Jones
Affiliation:
University of Cambridge
Stephen M. Stahl
Affiliation:
University of California, San Diego
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Summary

The first clear vision of the brain as a network stemmed from the extraordinary work by Ramón y Cajal, the Nobel Laureate (1916) who defined the neuron and conceived of synaptic connections between neurons to form a cellular or microscopic network (see Figure 5.18.1A) on a spatial scale of micrometres to nanometres (i.e. 10−6–10−9 metres). The mammalian brain also has a network organisation at a larger, mesoscopic scale (i.e. 10−4–10−6 m), with cortical areas or subcortical nuclei connecting to each other via bundles or tracts of long-distance axonal projections (see Figure 5.18.1B), and at the macroscopic scale (i.e. centimetres to millimetres, or 10−2–10−4 m), as can be measured using brain MRI (see Figure 5.18.1C). Increasingly detailed maps and technically dazzling images of micro, meso and macro brain network organisation are being produced across a range of species, from the nematode Caenorhabditis elegans, through Drosophila species, to rodents and monkeys. Several books and reviews provide more detail and scope on the flourishing field of connectomics or network neuroscience [1–5]; here we focus on a few high-level principles.

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Publisher: Cambridge University Press
Print publication year: 2023

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References

Sporns, O. Networks of the Brain. MIT Press, 2011.Google Scholar
Fornito, A, Zalesky, A, Bullmore, ET. Fundamentals of Brain Network Analysis. Academic Press, 2016.Google Scholar
Fornito, A, Zalesky, A, Breakspear, M. The connectomics of brain disorders. Nat Rev Neurosci 2015; 16: 159172.CrossRefGoogle ScholarPubMed
Bullmore, E, Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 2009; 10: 186198.CrossRefGoogle ScholarPubMed
Lynn, CW, Bassett, DS. The physics of brain network structure, function and control. Nat Rev Phys 2019; 1: 318332.CrossRefGoogle Scholar
Swanson, LW, Lichtman, JW. From Cajal to connectome and beyond. Annu Rev Neurosci 2016; 39: 197216.CrossRefGoogle ScholarPubMed
Rubinov, M*, Ypma, RJF*, Watson, C, Bullmore, ET. Wiring cost and topological participation of the mouse brain conenctome. Proc Natl Acad Sci 2015; 112: 1003210037.CrossRefGoogle Scholar
Seidlitz, J, Váša, F, Shinn, M et al. Morphometric similarity networks detect microscale cortical organization and predict inter-individual cognitive variation. Neuron 2018; 97: 231247.CrossRefGoogle ScholarPubMed
Crossley, NA, Mechelli, A, Vértes, PE et al. Cognitive relevance of the community structure of the human brain functional coactivation network. Proc Natl Acad Sci USA 2013; 110: 1158311588.CrossRefGoogle ScholarPubMed
Vértes, PE, Bullmore, ET. Annual research review: growth connectomics – the organization and reorganization of brain networks during normal and abnormal development. J Child Psychol Psychiatry 2015; 56: 299320.CrossRefGoogle ScholarPubMed
Bullmore, E, Sporns, O. The economy of brain network organization. Nat Rev Neurosci 2012; 13: 336349.CrossRefGoogle ScholarPubMed
Crossley, NA, Mechelli, A, Scott, J et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain 2014; 137: 23822395.CrossRefGoogle ScholarPubMed
Friston, KJ, Frith, CD. Schizophrenia: a disconnection syndrome? Clin Neurosci 1995; 3: 8997.Google ScholarPubMed
Morgan, SE, Seidlitz, J, Whitaker, KJ et al. Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proc Natl Acad Sci USA 2019; 116: 96049609.CrossRefGoogle ScholarPubMed
Morgan, SE*, Young, J*, Patel, AX et al. Functional MRI connectivity accurately distinguishes cases with psychotic disorders from healthy controls, based on cortical features associated with neurodevelopment. Biol Psychiatry Cogn Neurosci Neuroimag 2021; 6: 11251134.Google Scholar

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