{"title":"Development of a Rat-Licking Device for Operant Conditioning Experiments","authors":"Shan Ma, Rongchao Peng, Dachao Wei, Yi Li","doi":"10.1145/3502871.3502898","DOIUrl":null,"url":null,"abstract":"Behavior experiments in rodents are one of the main methods to study depression. However, most animal behavior experiments rely on experimenters to manually record data, and it is prone to errors caused by human factors. When the experiment involves a large number of animal subjects and takes a long time, it is really a heavy workload for the experimenters. To overcome these shortcomings, we developed a device using electromechanical integration technology to automatically record the data of the rat's licking behavior and automatically feed the animal for reward. This device is composed of a Raspberry Pi computer and a syringe pump. The Raspberry Pi identifies different IDs through the radio frequency identification module to select different experimental plans. When the experiment is going, the Raspberry Pi collects the rat's licking and movement data through two touch sensors and an infrared sensor, automatically stores them in a text file, and determines whether to drive the syringe pump to feed the animal according to pre-set licking criteria. The feeding is a fixed small volume of sugar water that is given to the rat for reward, and the volume is configurable by the user before the experiment. When tested, the device worked stably and reliably. The accuracy of the touch sensors for touching is 97.56%, and they reliably detected fast-speed touching in small touch areas. The error of the real infusion volumes is less than 8% of the pre-set volumes. We think this device is helpful in practical use. It will bring convenience to the experimenter, reduce the manual workload and improve the precision of the experiments.","PeriodicalId":253757,"journal":{"name":"Proceedings of the 2021 8th International Conference on Biomedical and Bioinformatics Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 8th International Conference on Biomedical and Bioinformatics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3502871.3502898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Behavior experiments in rodents are one of the main methods to study depression. However, most animal behavior experiments rely on experimenters to manually record data, and it is prone to errors caused by human factors. When the experiment involves a large number of animal subjects and takes a long time, it is really a heavy workload for the experimenters. To overcome these shortcomings, we developed a device using electromechanical integration technology to automatically record the data of the rat's licking behavior and automatically feed the animal for reward. This device is composed of a Raspberry Pi computer and a syringe pump. The Raspberry Pi identifies different IDs through the radio frequency identification module to select different experimental plans. When the experiment is going, the Raspberry Pi collects the rat's licking and movement data through two touch sensors and an infrared sensor, automatically stores them in a text file, and determines whether to drive the syringe pump to feed the animal according to pre-set licking criteria. The feeding is a fixed small volume of sugar water that is given to the rat for reward, and the volume is configurable by the user before the experiment. When tested, the device worked stably and reliably. The accuracy of the touch sensors for touching is 97.56%, and they reliably detected fast-speed touching in small touch areas. The error of the real infusion volumes is less than 8% of the pre-set volumes. We think this device is helpful in practical use. It will bring convenience to the experimenter, reduce the manual workload and improve the precision of the experiments.