| Literature DB >> 27026638 |
Tetsuya Asakawa1, Huan Fang2, Kenji Sugiyama3, Takao Nozaki3, Zhen Hong4, Yilin Yang5, Fei Hua5, Guanghong Ding6, Dongman Chao7, Albert J Fenoy7, Sebastian J Villarreal7, Hirotaka Onoe8, Katsuaki Suzuki9, Norio Mori9, Hiroki Namba3, Ying Xia10.
Abstract
Parkinson's disease (PD), a neurodegenerative disorder, is traditionally classified as a movement disorder. Patients typically suffer from many motor dysfunctions. Presently, clinicians and scientists recognize that many non-motor symptoms are associated with PD. There is an increasing interest in both motor and non-motor symptoms in clinical studies on PD patients and laboratory research on animal models that imitate the pathophysiologic features and symptoms of PD patients. Therefore, appropriate behavioral assessments are extremely crucial for correctly understanding the mechanisms of PD and accurately evaluating the efficacy and safety of novel therapies. This article systematically reviews the behavioral assessments, for both motor and non-motor symptoms, in various animal models involved in current PD research. We addressed the strengths and weaknesses of these behavioral tests and their appropriate applications. Moreover, we discussed potential mechanisms behind these behavioral tests and cautioned readers against potential experimental bias. Since most of the behavioral assessments currently used for non-motor symptoms are not particularly designed for animals with PD, it is of the utmost importance to greatly improve experimental design and evaluation in PD research with animal models. Indeed, it is essential to develop specific assessments for non-motor symptoms in PD animals based on their characteristics. We concluded with a prospective view for behavioral assessments with real-time assessment with mobile internet and wearable device in future PD research.Entities:
Keywords: Behavioral assessments; Fine motor; Food reaching movement; Free-moving counting; Locomotion motor symptoms; Neuropsychological tasks; Non-motor symptoms; Parkinsonian model
Mesh:
Year: 2016 PMID: 27026638 DOI: 10.1016/j.neubiorev.2016.03.016
Source DB: PubMed Journal: Neurosci Biobehav Rev ISSN: 0149-7634 Impact factor: 8.989