Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Small-World Human Brain Networks: Perspectives and Challenges
National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University.
2017 (English)In: Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, E-ISSN 1873-7528, Vol. 77, 286-300 p.Article in journal (Refereed) Published
Abstract [en]

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and aging and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field.

Place, publisher, year, edition, pages
2017. Vol. 77, 286-300 p.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-62939DOI: 10.1016/j.neubiorev.2017.03.018PubMedID: 28389343ScopusID: 2-s2.0-85017202239OAI: oai:DiVA.org:ltu-62939DiVA: diva2:1087515
Note

Validerad; 2017; Nivå 2; 2017-04-24 (andbra)

Available from: 2017-04-07 Created: 2017-04-07 Last updated: 2017-04-24Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Vasilakos, Athanasios
By organisation
Computer Science
In the same journal
Neuroscience and Biobehavioral Reviews
Media and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf