Journal of Molecular Neuroscience

, Volume 49, Issue 3, pp 632–638

Associations Between EEG Beta Power Abnormality and Diagnosis in Cognitive Impairment Post Cerebral Infarcts

  • Yanping Wang
  • Xiaoling Zhang
  • Junjun Huang
  • Minchu Zhu
  • Qiaobing Guan
  • Chunfeng Liu
Article

DOI: 10.1007/s12031-012-9918-y

Cite this article as:
Wang, Y., Zhang, X., Huang, J. et al. J Mol Neurosci (2013) 49: 632. doi:10.1007/s12031-012-9918-y

Abstract

Cerebral infarct is a common disease of older adults, which could increase the risk for cognitive impairment and dementia. Electroencephalogram (EEG) characteristics were analyzed to investigate the applied value in the assessment of cognitive impairment of the cerebral infarct patients. One hundred ten subjects with cerebral infarcts (including 65 cases of cognitive impairment patients (CI-CI) and 45 cases of cognitive normality patients (CI-NC)) and 110 normal health persons (NC) were recruited between July 2009 and March 2011 at the Department of Neurology. All of the patients were analyzed by EEG within 1 day they were hospitalized. The EEG analysis results were compared with the Montreal Cognitive Assessment (MoCA) scale (assessed within 2 weeks) with the methods of correlation analysis, clustering analysis, and concordance analysis. The results indicated that CI-CI patients had significantly lower EEG beta power (0.832 ± 0.203 mcV2) relative to the CI-NC group (1.493 ± 0.271 mcV2, P < 0.01) or NC group (1.565 ± 0.345 mcV2, P < 0.01). Significant negative correlation between the beta power and infarct size (as well as infarct number) was discovered (r = −0.88881 and −0.66498, respectively, both P < 0.001). There was a good concordance between K-means clustering algorithm calculating the beta power and MoCA scoring (Kappa = 0.851, P < 0.001). The preliminary findings suggest that the recognition techniques of EEG hold considerable promise for the assessment of cognitive impairment post cerebral infarcts within 2 weeks and which related to the size of infarcts and number of infarcts.

Keywords

Cerebral infarctsCognitive impairmentElectroencephalogramBeta powerClustering analysis

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Yanping Wang
    • 1
    • 2
  • Xiaoling Zhang
    • 1
  • Junjun Huang
    • 1
  • Minchu Zhu
    • 1
  • Qiaobing Guan
    • 1
  • Chunfeng Liu
    • 2
  1. 1.Department of NeurologySecond Affiliated Hospital, Jiaxing College of MedicineJiaxingChina
  2. 2.Department of NeurologySecond Affiliated Hospital of Soochow UniversitySuzhouChina