构建自动、智能及敏感度高的避暗实验检测系统

背景：避暗法在认知功能障碍研究中应用广泛，但传统检测方法存在费时、信息量少、客观性差等问题。计算机、信息工程等现代科技的发展给构建新的实验检测方法提供了良好契机。目的：建立一种自动化、智能化、敏感程度高的避暗实验系统，用于动物的学习记忆研究。方法：采用图像处理、模式识别等技术提取动物在明暗室的活动信息，利用正常小鼠和东莨菪碱模型小鼠进行避暗实验，同时与传统检测结果进行比较。 结果与结论：实验所用的检测系统提取的指标与传统检测结果吻合度高，结果科学客观。且明暗室时间、路程、明室近口区时间等新指标可能比经典指标更加敏感。说明此系统是一种新的自动化、智能化程度高，指标敏感性强的避暗实验检测系统。

Establishment of a highly automated and intelligent experimental system of passive avoidance for mice

BACKGROUND: Widely used in cognitive dysfunction research, passive avoidance test was executed time consuming, less information and lack of objectivity in the traditional manner. The development of modern technology such as computer and information engineering is beneficial for inventing new detective methods. OBJECTIVE: To establish a highly automated and intelligent experimental system of passive avoidance for studying learning and memory in animal behavior pharmacology. METHODS: Image processing and pattern recognition technology was applied to obtain the activity information of mice in both the lit and dark chambers. Normal and cognitive dysfunction mice induced by scopolamine hydrobromide were tested in the passive avoidance test. Meanwhile, the data were compared with those acquired by manual labor. RESULTS AND CONCLUSION: Automatic control of the experiment could be realized by applying this technology and the indexes obtained by the system were consistent with those acquired by manual labor. Furthermore, besides classical indexes, the acquired new indexes, such as time spent in both the lit and dark chambers, time in the region near door in the lit chamber might be more sensitive than classical indexes. The technology has intellectual property rights and the intelligent experiment system can be widely used in the study of nootropic drugs.