Automated classification of the behavior of rats in the forced swimming test with support vector machines

作者：Froehlich Holger; Hoenselaar Andreas; Eichner Jonas; Rosenbrock Holger; Birk Gerald; Zell Andreas

来源：Neural Networks, 2008, 21(1): 92-101.

DOI：10.1016/j.neunet.2007.09.019

• support vector machine
• kernel
• automated behavior classification
• forced swimming test
• antidepressant activity

The forced swimming test of rats or mice is a frequently used behavioral test to evaluate compounds for antidepressant activity in vivo. The aim of this study was to replace the human observer, needed to score and analyze the behavior of animals, by a fully automated method. For this purpose, in a first step from a video recording of each rat, an activity profile was calculated, from which subsequently a set of meaningful properties was extracted. This set was finally used to train a Support Vector Machine (SVM). Furthermore, specialized kernel functions, namely the so-called time resolved p-spectrum and modified optimal assignment kernels, were developed to calculate the similarity of activity profiles. Our method allows for a very reliable discrimination of animals treated with antidepressants of different classes (tricyclics imipramine and desipramine as well as selective serotonin reuptake inhibitor, SSRI, fluoxetine) versus a vehicle-treated group. Moreover, our technique is able to classify between tricyclic antidepressants and SSRIs. The results of this work enabled the development of an automated and highly accurate behavior classification system.

• 出版日期2008-1
• 单位上海生物信息技术研究中心