The identification and clustering analysis of auditory neurons for salicylated-induced rat model.
Salicylate-induced rat model is one of the animal models for tinnitus study. In this study, a radial basis function neural network for automatic identification is firstly developed due to its features of easy training and learning. From the experimental results, the recognition rate is demonstrated to be as high as 98%. Not only the recognition rate is improved, but also it is very objective in analysis. Secondly, a support vector clustering is applied to neurons distribution analysis. Based on the clustering analysis, it is found that the cluster number and distribution area for the Salicylated-induced fos-labeled neurons are very different from those of controlled group.
Cheng
Kuo-Sheng
KS
Institute of Biomedical Engineering, National Cheng Kung University, Tainan, TAIWAN kscheng@mail.ncku.edu.tw
Chen
Li-Hui
LH
Wang
Yi-Jung
YJ