• DocumentCode
    3767306
  • Title

    Damage to the dorsal attention network and interactions with the control and sensory-motor networks in late-onset depression

  • Author

    Rui Liu;Yingying Yue;Zhenghua Hou;Jian Lu;Yonggui Yuan;Qiao Wang

  • Author_Institution
    School of Information Science and Engineering, Southeast University, Nanjing, China
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Late-onset depression (LOD) is considered as a disconnection syndrome that disrupts brain networks subserving multidomain cognitive and behavioural functions. Interactions between resting-state networks (RSNs) are considered to be important for cognitive control. The present study is to perform resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) to delineate the connectivity patterns of intra- and inter-network in LOD and to examine the altered functional interactions between RSNs. A total of 28 LOD patients and 40 matched healthy controls (HC) were recruited. We investigated rs-fcMRI in the cognitive control network (CON), the dorsal attention network (DAN), and the sensory-motor network (SMN). For intra-network, compared with HC, LOD showed significantly reduced connectivity strengths within DAN, CON, and SMN. For inter-network, compared with HC, LOD exhibited significantly reduced connections in DAN-CON pair and DAN-SMN pair while no difference was found in the CON-SMN pair. The present study provides powerful and novel insights into the functional organization of RSNs, and functional interactions between RSNs in LOD. It further suggests that LOD utilizes an altered model of cognitive control where the altered DAN may mediate the transition stage of the information processing from bottom-up information about sensory-motor inputs to high-level cognition.
  • Publisher
    iet
  • Conference_Titel
    Biomedical Image and Signal Processing (ICBISP 2015), 2015 IET International Conference on
  • Print_ISBN
    978-1-78561-044-8
  • Type

    conf

  • DOI
    10.1049/cp.2015.0787
  • Filename
    7450363