Structure and function of brain networks

  • Rok Berlot Department of Neurology, Division of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
  • Grega Repovš Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
Keywords: brain networks, connectivity, graph theory, neuroimaging, magnetic resonance imaging


In recent years, the so-called network perspective has led to better understanding of the functioning of the brain in health and disease. The development of non-invasive imaging methods and the use of mathematical tools from graph theory allowed for investigating the structure and function of brain networks. Connections within structural networks can be reconstructed using diffusion magnetic resonance imaging, while functional imaging methods allow for investigating functional networks. The capabilities of the brain are based on network topology, which allows both functional segregation and integrative processing of information. This review represents an accessible introduction to the basic principles of graph theory and network neuroscience. We introduce measures of network topology and basic properties of human brain networks. We explain how neurological and psychiatric disorders affect the functioning of the brain as a network and illustrate the relevance of these findings for clinical practice. We also highlight some limitations of the network approach and future challenges to be addressed in this rapidly developing field of neuroscience.


Download data is not yet available.


Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A. Modeling the worldwide spread of pandemic influenza: baselinca case and containment interventions. PloS Med, 2007;4(1):e13. doi: 10.1371/journal.pmed.0040013

Zachary WW. An information flow model for conflict and fission in small groups. J Anthropol Res. 1977;33(4):452-73.

Žerdin AH, Mrvar A. Spremembe v notranjem krogu omrežja slovenske ekonomske elite v letih 2004-2006. Družboslovne razprave. 2007;55:7-25.

Knuth DE. The Stanford GraphBase: a platform for combinatorial computing. New York, USA: ACM Press; 1994.

Berlot R. Integriteta bele možganovine pri zdravem staranju in blagi kognitivni motnji: povezava s porazdeljenimi možganskimi omrežji [PhD Thesis]. Ljubljana: R. Berlot; 2016.

Leskovec J, Kleinberg J, Faloutsos C. Graphs over time: densification laws, shrinking diameters and possible explanations. Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2005;177-87.

Stožer A, Dolenšek J, Rupnik MS. Glucose-stimulated calcium dynamics in islets of Langerhans in acute mouse pancreas tissue slices. PLoS One. 2013;8(1):e54638. doi: 10.1371/journal.pone.0054638.

Batagelj M, Mrvar A. Pajek – program for large network analysis. Connections. 1998;21:47-57.

Euler L. Solutio problematis ad geometriam situs pertinentis. Comment Acad Sci U Petrop. 173;8:128-40.

Hopkins B, Wilson RJ. The truth about Königsberg. The College Mathematics Journal. 2004;35(3):198-207.

Sporns O. Networks of the brain. Cambridge, USA: MIT Press; 2011.

Travers J, Milgram S. An experimental study of the small world problem. Sociometry. 1969;32:425-43.

Watts DJ, Strogatz SH. Collective dynamics of 'small-world' networks. Nature. 1998;393(6684):440-2.

Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage. 2010;52(3):1059-69.

Latora V, Marchiori M. Efficient behavior of small-world networks. Phys Rev Lett. 2001;87(19):198701. doi: 10.1103/PhysRevLett.87.198701.

Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009;10(3):186-98.

White JG, Southgate E, Thomson JN, Brenner S. The structure of the nervous system of the nematode Caenorhabditis elegans. Philos Trans R Soc Lond B Biol Sci.1986;314(1165):1-340.

Scannell JW, Young MP. The connectional organization of neural systems in the cat cerebral cortex. Curr Biol. 1993;3(4):191-200.

Stephan KE, Kamper L, Bozkurt A, Burns GA, Young MP, Kötter R. Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). Philos Trans R Soc Lond B Biol Sci. 2001;356(1412):1159-86.

Felleman DJ, Van Essen DC. Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex. 1991;1(1):1-47.

Berlot R. Difuzijsko magnetnoresonančno slikanje: orodje za oceno mikro- in makrostrukture možganov. eSinapsa 2015; 10. [cited 2018 Mar 31]. Available from:

Logothetis NK, Wandell BA. Interpreting the BOLD signal. Annu Rev Physiol. 2004;66:735-69.

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

Van Essen DC, Ugurbil K, Auerbach E, Barch D, Behrens TE, Bucholz R, et al. The Human Connectome Project: a data acquisition perspective. Neuroimage. 2012;62(4):2222-31.

Bullmore E, Sporns O. The economy of brain network organization. Nat Rev Neurosci. 2012;13(5):336-49.

Iturria-Medina Y, Sotero RC, Canales-Rodríguez EJ, Alemán-Gómez Y, Melie-García L. Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. Neuroimage. 2008;40(3):1064-76.

Sporns O. Making sense of brain network data. Nat Methods. 2013;10(6): 491-3.

van den Heuvel MP, Sporns O. An anatomical substrate for integration among functional networks in human cortex. J Neurosci. 2013;33(36):14489-500.

Colizza V, Flammini A, Serrano MA, Vespignani A. Detecting rich-club ordering in complex networks. Nature Phys. 2006;2:110-5.

Griffa A, Baumann PS, Thiran JP, Hagmann P. Structural connectomics in brain diseases. Neuroimage. 2013;80:515-26.

Liang X, Zou Q, He Y, Yang Y. Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proc Natl Acad Sci U S A. 2013;110(5):1929-34.

Tomasi D, Wang GJ, Volkow ND. Energetic cost of brain functional connectivity. Proc Natl Acad Sci U S A. 2013;110(33):13642-7.

van den Heuvel MP, Kahn RS, Goñi J, Sporns O. High-cost, high-capacity backbone for global brain communication. Proc Natl Acad Sci U S A. 2012;109(28):11372-7.

Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62(1):42-52.

Crossley NA, Mechelli A, Scott J, Carletti F, Fox PT, McGuire P, et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain. 2014;137:2382-95.

Cole MW, Reynolds JR, Power JD, Repovš G, Anticevic A, Braver TS. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat Neurosci. 2013;16(9):1348-55.

Cole MW, Repovš G, Anticevic A. The frontoparietal control system: a central role in mental healthy. Neuroscientist. 2014;20(6):652-64.

de Haan W, van der Fliew WM, Koene T, Smits LL, Scheltens P, Stam CJ. Disrupted modular brain dynamics reflects cognitive dysfunction in Alzheimer's disease. Neuroimage. 2012;59(4):3085-93.

Stam CJ. Modern network science of neurological disorders. Nat Rev Neurosci. 2014;15(10):683-95.

Repovš G, Csernansky JG, Barch DM. Brain network connectivity in individuals with schizophrenia and their siblings. Biol Psychiatry. 2011;69(10):967-73.

Repovš G, Barch DM. Working memory related brain network connectivity in individuals with schizophrenia and their siblings. Front Hum Neurosci. 2012;6:137. doi: 10.3389/fnhum.2012.00137.

Sheffield JM, Repovš G, Harms MP, Carter CS, Gold JM, MacDonald AW, et al. Evidence for accelerated decline of functional brain network efficiency in schizophrenia. Schizophrenia Bull. 2016;42(3):753-61.

Anticevic A, Cole MV, Repovš G, Savic A, Driesen NR, Yang G, et al. Connectivity, pharmacology, and computation: toward a mechanistic understanding of neural system dysfunction in schizophrenia. Front Psychiatry. 2013;4:169. doi: 10.3389/fpsyt.2013.00169.

Anticevic A, Gancsos M, Murray JD, Repovš G, Driesen NR, Ennis DJ, et al. NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia. Proc Natl Acad Sci U S A. 2012;109(41):16720-5.

Anticevic A, Corlett PR, Cole MW, Savic A, Gancsos M, Tang Y, et al. N-methyl-D-aspartate receptor antagonist effects on prefrontal cortical connectivity better model early than chronic schizophrenia. Biol Psychiatry. 2015;77(6):569-80.

Anticevic A, Hu X, Xiao Y, Hu J, Li F, Bi F, et al. Early-course unmedicated schizophrenia patients exhibit elevated prefrontal connectivity associated with longitudinal change. J Neurosci. 2015;35(1):267-86.

Cole MW, Anticevic A, Repovš G, Barch DM. Variable global dysconnectivity and individual differences in schizophrenia. Biol Psychiatry. 2011;70(1):43-50.

Anticevic A, Haut K, Murray JD, Repovš G, Yang GJ, Diehl C, et al. Association of thalamic dysconnectivity and conversion to psychosis in youth and young adults at elevated clinical risk. JAMA Psychiatry. 2015;72(9):882-91.

Drysdale AT, Grosenick l, Downar J, Dunlop K, Mansouri F, Meng, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017;23(1):28-38.

Geschwind N. Disconnexion syndromes in animals and man. I. Brain. 1965;88:237-94.

Warrington EK. A disconnection analysis of amnesia. Ann N Y Acad Sci. 1985;444:72-7.

Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82(4):239-59.

Thal DR, Rüb U, Orantes M, Braak H. Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology. 2002;58(12):1791-800.

Scoville WB, Milner B. Loss of recent memory after bilateral hippocampal lesions. J Neurol Neurosurg Psychiatry. 1957;20(1):11-21.

Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, et al. Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry. 1992;55(10):967-72.

Aggleton JP, Brown MW. Interleaving brain systems for episodic and recognition memory. Trends Cogn Sci. 2006;10(10):455-63.

Cole MW, Schneider W. The cognitive control network: integrated cortical regions with dissociable functions. Neuroimage. 2007;37(1):343-60.

Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A. 2004;101(13):4637-42.

Acosta-Cabronero J, Williams GB, Pengas G, Nestor PJ. Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease. Brain. 2010;133(2):529-39.

Agosta F, Pievani M, Sala S, Geroldi C, Galluzzi S, Frisoni GB, et al. White matter damage in Alzheimer disease and its relationship to gray matter atrophy. Radiology. 2011;258(3):853-63.

Berlot R, Metzler-Baddeley C, Jones DK, O'Sullivan MJ. CSF contamination contributes to apparent microstructural alterations in mild cognitive impairment. Neuroimage. 2014;92:27-35.

Lo CY, Wang PN, Chou KH, Wang J, He Y, Lin CP. Diffusion tensor tractography reveals abnormal topological organization in structural cortical networks in Alzheimer's disease. J Neurosci 2010; 30(50): 16876-85.

Berlot R, Metzler-Baddeley C, Ikram MA, Jones DK, O’Sullivan MJ. Global efficiency of structural networks mediates cognitive control in mild cognitive impairment. Front Aging Neurosci. 2016;8:292. doi: 10.3389/fnagi.2016.00292.

Berlot R, O’Sullivan MJ. What can the topology of white matter structural networks tell us about mild cognitive impairment?. Future Neurol. 2017;12(1):35-50.

How to Cite
Berlot R, Repovš G. Structure and function of brain networks. ZdravVestn [Internet]. 18Apr.2019 [cited 18Jun.2019];88(3-4):168-83. Available from:
Professional Article