» Articles » PMID: 18267952

Revealing Modular Architecture of Human Brain Structural Networks by Using Cortical Thickness from MRI

Overview
Journal Cereb Cortex
Specialty Neurology
Date 2008 Feb 13
PMID 18267952
Citations 216
Authors
Affiliations
Soon will be listed here.
Abstract

Modularity, presumably shaped by evolutionary constraints, underlies the functionality of most complex networks ranged from social to biological networks. However, it remains largely unknown in human cortical networks. In a previous study, we demonstrated a network of correlations of cortical thickness among specific cortical areas and speculated that these correlations reflected an underlying structural connectivity among those brain regions. Here, we further investigated the intrinsic modular architecture of the human brain network derived from cortical thickness measurement. Modules were defined as groups of cortical regions that are connected morphologically to achieve the maximum network modularity. We show that the human cortical network is organized into 6 topological modules that closely overlap known functional domains such as auditory/language, strategic/executive, sensorimotor, visual, and mnemonic processing. The identified structure-based modular architecture may provide new insights into the functionality of cortical regions and connections between structural brain modules. This study provides the first report of modular architecture of the structural network in the human brain using cortical thickness measurements.

Citing Articles

Integrated information theory reveals the potential role of the posterior parietal cortex in sustaining conditioning responses in classical conditioning tasks.

Phi T, Ishii S, Kondo M, Matsuzaki M, Nakae K Front Neurosci. 2025; 19:1512724.

PMID: 39944891 PMC: 11814451. DOI: 10.3389/fnins.2025.1512724.


A Multivariate and Network Analysis Uncovers a Long-Term Influence of Exclusive Breastfeeding on the Development of Brain Morphology and Structural Connectivity.

Parente F, Pedale T, Rossi-Espagnet C, Longo D, Napolitano A, Gazzellini S Brain Topogr. 2024; 38(1):16.

PMID: 39585450 DOI: 10.1007/s10548-024-01091-x.


Intra-individual structural covariance network in schizophrenia patients with persistent auditory hallucinations.

Shao X, Ren H, Li J, He J, Dai L, Dong M Schizophrenia (Heidelb). 2024; 10(1):92.

PMID: 39402082 PMC: 11473721. DOI: 10.1038/s41537-024-00508-7.


The brain network hub degeneration in Alzheimer's disease.

Jin S, Wang J, He Y Biophys Rep. 2024; 10(4):213-229.

PMID: 39281195 PMC: 11399886. DOI: 10.52601/bpr.2024.230025.


Hierarchical communities in the larval connectome: Links to cellular annotations and network topology.

Betzel R, Puxeddu M, Seguin C Proc Natl Acad Sci U S A. 2024; 121(38):e2320177121.

PMID: 39269775 PMC: 11420166. DOI: 10.1073/pnas.2320177121.


References
1.
Stam C . Functional connectivity patterns of human magnetoencephalographic recordings: a 'small-world' network?. Neurosci Lett. 2004; 355(1-2):25-8. DOI: 10.1016/j.neulet.2003.10.063. View

2.
Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A . Neuroplasticity: changes in grey matter induced by training. Nature. 2004; 427(6972):311-2. DOI: 10.1038/427311a. View

3.
Sporns O, Chialvo D, Kaiser M, Hilgetag C . Organization, development and function of complex brain networks. Trends Cogn Sci. 2004; 8(9):418-25. DOI: 10.1016/j.tics.2004.07.008. View

4.
Sporns O, Tononi G, Kotter R . The human connectome: A structural description of the human brain. PLoS Comput Biol. 2005; 1(4):e42. PMC: 1239902. DOI: 10.1371/journal.pcbi.0010042. View

5.
Sporns O, Tononi G, Edelman G . Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cereb Cortex. 2000; 10(2):127-41. DOI: 10.1093/cercor/10.2.127. View