Altered small-world brain networks in temporal lobe in patients with schizophrenia performing an auditory oddball task

Qingbao Yu, Jing Sui, Srinivas Rachakonda, Hao He, Godfrey Pearlson, Vince D. Calhoun

Research output: Contribution to journalArticlepeer-review


The functional architecture of the human brain has been extensively described in terms of complex networks characterized by efficient small-world features. Recent functional magnetic resonance imaging (fMRI) studies have found altered small-world topological properties of brain functional networks in patients with schizophrenia (SZ) during the resting state. However, little is known about the small-world properties of brain networks in the context of a task. In this study, we investigated the topological properties of human brain functional networks derived from fMRI during an auditory oddball (AOD) task. Data were obtained from 20 healthy controls and 20 SZ; A left and a right task-related network which consisted of the top activated voxels in temporal lobe of each hemisphere were analyzed separately. All voxels were detected by group independent component analysis. Connectivity of the left and right task-related networks were estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. The small-worldness values were decreased in both hemispheres in SZ. In addition, SZ showed longer shortest path length and lower global efficiency only in the left task-related networks. These results suggested small-world attributes are altered during the AOD task-related networks in SZ which provided further evidences for brain dysfunction of connectivity in SZ.

Original languageEnglish (US)
Article number7
JournalFrontiers in Systems Neuroscience
Issue numberFEBRUARY 2011
StatePublished - Feb 8 2011


  • Auditory oddball
  • ICA
  • Network
  • Schizophrenia
  • Small-world
  • fMRI

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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