TY  - JOUR
AU  - Zhou, Hongbo 
AU  - Cheng, Qiang 
AU  - Yang, Hong-Ju 
AU  - Xu, Haiyun 
PY  - 2011
TI  - Weighted Kernel Density Estimation of the Prepulse Inhibition Test
JF  - Journal of Computer Science
VL  - 7
IS  - 5
DO  - 10.3844/jcssp.2011.611.618
UR  - https://thescipub.com/abstract/jcssp.2011.611.618
AB  - Problem statement: The goal of this study was to devise a more reliable and sensitive
method for analysis of experimental data of the Prepulse Inhibition (PPI), the reduction in startle
reaction towards a startle-eliciting “pulse” stimulus when it is shortly preceded by a sub-threshold “prepulse” stimulus. Approach: Different from the conventional simple averaging-based method, we proposed a probabilistic approach to modeling the PPI data. With this probabilistic description, we reconstructed complete response signals from the PPI data and devised a nonparametric weighted Kernel Density Estimation (KDE) method to tackle two important issues in PPI data related density estimation: instability and limited number of samples. We designed two sets of animal experiments using different medicines and compared the KDE based method with the conventional simple-averaging based method. Results: Our results showed that the KDE method performed better than the conventional method and offered some advantages over the conventional method. Conclusion: The new method provided a more reliable and sensitive approach to the post-session analysis of PPI data.