title: Association of brain network efficiency with aging, depression, and cognition.
abstract: OBJECTIVE
  Newly developed techniques for understanding brain connectivity have emerged with the application of graph theory-based measures to neuroimaging modalities. However, the cognitive correlates of these measures, particularly in the context of clinical diagnoses like major depression, are still poorly understood. The purpose of this study was to compare four measures of network efficiency derived from novel techniques for understanding white matter connectivity on their associations with aging, depression, and cognition.
  
  
  METHODS
  In a cross-sectional neuroimaging study, we recruited from the general community 43 healthy comparison subjects and 40 subjects with major depressive disorder who volunteered in response to advertisements. Brain network efficiency measures were generated from diffusion tensor imaging-derived structural connectivity matrices using the Brain Connectivity Toolbox. Information processing speed and decision making were assessed with the Trail Making Test and the Object Alternation task, respectively.
  
  
  RESULTS
  All four network efficiency measures correlated negatively with age. In the depressed group, normalized global efficiency was negatively correlated with depression severity, whereas increasing global efficiency was associated with poorer performance on Object Alternation.
  
  
  CONCLUSIONS
  Brain network efficiency measures may represent different aspects of underlying network organization depending on the population and behaviors in question.
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL. Electronic address: oajilore@psych.uic.edu.
authors.forename: Olusola
authors.initials: O
authors.lastname: Ajilore
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Melissa
authors.initials: M
authors.lastname: Lamar
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology* / Q000523:psychology*; D001921:Brain / Q000473:pathology*; D016022:Case-Control Studies; D003071:Cognition; D003865:Major Depressive Disorder / Q000473:pathology* / Q000523:psychology*; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D008875:Middle Aged; D009434:Neural Pathways / Q000473:pathology; D059906:Neuroimaging; D009483:Neuropsychological Tests
keywords: Aging; cognition; connectivity; depression; network analysis