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Human behavioral assessments in current research of Parkinson's disease

期刊

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
卷 68, 期 -, 页码 741-772

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2016.06.036

关键词

Behavioral assessments; Fine motor; Free-moving counting

资金

  1. Japan Society for the Promotion of Science [20791025, 24592157, 15k10358]
  2. Jiangsu SPMS of China [BL2014035]
  3. 973 Program [2012CB518502]
  4. NSFC of China [81574053]
  5. Memorial Hermann's Foundation
  6. Vivian L Smith Neurologic Foundation
  7. NIH [AT-004422]
  8. Grants-in-Aid for Scientific Research [26293264, 15K10358] Funding Source: KAKEN

向作者/读者索取更多资源

Parkinson's disease (PD) is traditionally classified as a movement disorder because patients mainly complain about motor symptoms. Recently, non-motor symptoms of PD have been recognized by clinicians and scientists as early signs of PD, and they are detrimental factors in the quality of life in advanced PD patients. It is crucial to comprehensively understand the essence of behavioral assessments, from the simplest measurement of certain symptoms to complex neuropsychological tasks. We have recently reviewed behavioral assessments in PD research with animal models (Asakawa et al., 2016). As a companion volume, this article will systematically review the behavioral assessments of motor and non-motor PD symptoms of human patients in current research. The major aims of this article are: (1) promoting a comparative understanding of various behavioral assessments in terms of the principle and measuring indexes; (2) addressing the major strengths and weaknesses of these behavioral assessments for a better selection of tasks/tests in order to avoid biased conclusions due to inappropriate assessments; and (3) presenting new concepts regarding the development of wearable devices and mobile internet in future assessments. In conclusion we emphasize the importance of improving the assessments for non-motor symptoms because of their complex and unique mechanisms in human PD brains. (C) 2016 Elsevier Ltd. All rights reserved.

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