title: Impaired Parahippocampus Connectivity in Mild Cognitive Impairment and Alzheimer's Disease.
abstract: BACKGROUND
  The parahippocampal gyrus (PHG) is an important region of the limbic system that plays an important role in episodic memory. Elucidation of the PHG connectivity pattern will aid in the understanding of memory deficits in neurodegenerative diseases.
  
  
  OBJECTIVE
  To investigate if disease severity associated altered PHG connectivity in Alzheimer's disease (AD) exists.
  
  
  METHODS
  We evaluated resting-state functional magnetic resonance imaging data from 18 patients with amnestic mild cognitive impairment (MCI), 35 patients with AD, and 21 controls. The PHG connectivity pattern was examined by calculating Pearson's correlation coefficients between the bilateral PHG and whole brain. Group comparisons were performed after controlling for the effects of age and gender. The functional connectivity strength in each identified region was correlated with the MMSE score to evaluate the relationship between connectivity and cognitive ability.
  
  
  RESULTS
  Several brain regions of the default mode network showed reduced PHG connectivity in the AD patients, and PHG connectivity was associated with disease severity in the MCI and AD subjects. More importantly, correlation analyses showed that there were positive correlations between the connectivity strengths of the left PHG-PCC/Pcu and left PHG-left MTG and the Mini-Mental State Examination, indicating that with disease progression from MCI to severe AD, damage to the functional connectivity of the PHG becomes increasingly severe.
  
  
  CONCLUSIONS
  These results indicate that disease severity is associated with altered PHG connectivity, contributing to knowledge about the reduction in cognitive ability and impaired brain activity that occur in AD/MCI. These early changes in the functional connectivity of the PHG might provide some potential clues for identification of imaging markers for the early detection of MCI and AD.
authors.affiliation: Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.|Department of Neurology, Cangzhou Central Hospital, Hebei Medical University, Cangzhou, China.
authors.forename: Jieqiong
authors.initials: J
authors.lastname: Liu
authors.affiliation: Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
authors.forename: Xinqing
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China.|Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
authors.forename: Chunshui
authors.initials: C
authors.lastname: Yu
authors.affiliation: Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China.
authors.forename: Yunyun
authors.initials: Y
authors.lastname: Duan
authors.affiliation: Brainnetome Center, Institute of Automation, the Chinese Academy of Sciences, Beijing, China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Zhuo
authors.affiliation: Brainnetome Center, Institute of Automation, the Chinese Academy of Sciences, Beijing, China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Cui
authors.affiliation: Brainnetome Center, Institute of Automation, the Chinese Academy of Sciences, Beijing, China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
authors.forename: Bing
authors.initials: B
authors.lastname: Liu
authors.affiliation: Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China.
authors.forename: Kuncheng
authors.initials: K
authors.lastname: Li
authors.affiliation: Brainnetome Center, Institute of Automation, the Chinese Academy of Sciences, Beijing, China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
authors.forename: Tianzi
authors.initials: T
authors.lastname: Jiang
authors.affiliation: Brainnetome Center, Institute of Automation, the Chinese Academy of Sciences, Beijing, China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000235:genetics / Q000503:physiopathology*; D001057:Apolipoproteins E / Q000235:genetics; D001931:Brain Mapping; D060825:Cognitive Dysfunction / Q000235:genetics / Q000503:physiopathology*; D005260:Female; D006624:Hippocampus / Q000503:physiopathology*; D006801:Humans; D008032:Limbic System / Q000503:physiopathology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008609:Mental Status Schedule; D009434:Neural Pathways / Q000503:physiopathology; D012146:Rest; D012720:Severity of Illness Index
chemical_list: D001057:Apolipoproteins E
keywords: Alzheimer’s disease; functional connectivity; mild cognitive impairment; parahippocampus