Analyzing and shaping human attentional networks

Michael I. Posner, Brad E. Sheese, Yalçin Odludaş, Yi Yuan Tang

Research output: Contribution to journalArticlepeer-review

161 Scopus citations


In this paper we outline a conception of attentional networks arising from imaging studies as connections between activated brain areas carrying out localized mental operations. We consider both the areas of functional activation (nodes) and the structural (DTI) and functional connections (DCM) between them in real time (EEG, frequency analysis) as important tools in analyzing the network. The efficiency of network function involves the time course of activation of nodes and their connectivity to other areas of the network. We outline landmarks in the development of brain networks underlying executive attention from infancy and childhood. We use individual differences in network efficiency to examine genetic alleles that are related to performance. We consider how animal studies might be used to determine the genes that influence network development. Finally we indicate how training may aid in enhancing attentional networks. Our goal is to show the wide range of methods that can be used to suggest and analyze models of network function in the study of attention.

Original languageEnglish (US)
Pages (from-to)1422-1429
Number of pages8
JournalNeural Networks
Issue number9
StatePublished - Nov 2006
Externally publishedYes


  • Alerting
  • DCM (Dynamic causal model for connectivity analysis)
  • DTI (Diffusion tensor imaging)
  • EEG frequency (electroencephalographic)
  • Executive attention
  • fMRI (functional magnetic resonance imaging)
  • Orienting
  • Self-regulation

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence


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