UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Gene transcription profiles associated with inter-modular hubs and connection distance in human fMRI networks

Vértes, PE; Rittman, T; Whitaker, KJ; Romero-Garcia, R; Váša, F; Kitzbichler, M; Wagstyl, KS; ... Bullmore, ET; + view all (2016) Gene transcription profiles associated with inter-modular hubs and connection distance in human fMRI networks. Philosophical Transactions of the Royal Society of London: Biological Sciences , 371 (1705) , Article 20150362. 10.1098/rstb.2015.0362. Green open access

[img] Text
fonagy_20150362.full.pdf
Available under License : See the attached licence file.

Download (1MB)

Abstract

Graph theoretical methods have been widely used to investigate the topology of large-scale human brain networks constructed from resting state functional magnetic resonance imaging (fMRI). It has been demonstrated that such human functional connectomes have a complex topology comprising integrative components, such as hubs and inter-modular edges, that are associated with proxy markers of greater biological cost. In the absence of secure knowledge of the neurovascular mechanisms linking ensemble oscillations of neuronal populations to low frequency coupling or functional connectivity between regional fMRI time series, it has been challenging to validate fMRI network properties reductionistically. Supportive evidence to date has been mostly provided by analogous results on the relationships between integrative topology and biological cost in other nervous systems. Here, we use microarray data on brain regional expression of 20,737 genes to explore the relationships between fMRI network topology and transcription of genes annotated for biological processes and cellular components. We show that intra-modular degree and inter-modular degree are differently patterned in anatomical space, are differently associated with cytoarchitectonic classes of cortex, and are associated with distinct and statistically independent gene expression profiles. Genes strongly associated with nodes mediating many long-distance and inter-modular connections are significantly enriched for oxidative metabolism and mitochondria as well as for a subset of genes specifically enriched in human supragranular cortical layers. These results are directly supportive of the concept of high cost / high value network hubs in fMRI networks and point to the nascent opportunity to resolve the molecular and cellular substrates of human brain graphs.

Type: Article
Title: Gene transcription profiles associated with inter-modular hubs and connection distance in human fMRI networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rstb.2015.0362
Publisher version: http://dx.doi.org/10.1098/rstb.2015.0362
Language: English
Additional information: Copyright © The Author(s), 2016. All rights reserved. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Keywords: Economy, Graph theory, Hub, Allen Institute for Brain Sciences, Transcriptome, Community structure
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/1496433
Downloads since deposit
61Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item