A convolutional neural network model detecting lasting behavioral changes in mice with kanamycin-induced unilateral inner ear dysfunction

Abstract

In acute aminoglycoside ototoxicity of the unilateral inner ear, physical abnormalities, such as nystagmus and postural alteration, are relieved within a few days by neural compensation. To examine exploratory behavior over an extended period, behaviors of freely moving mice after unilateral kanamycin injection into the inner ear were recorded in a home cage environment. The tail was excluded from deep learning-mediated object detection because of its delayed movement relative to the body. All detection results were confirmed using a convolutional neural network classification model. In kanamycin-injected mice, the total distance moved in 15 min increased on postoperative day 3. Furthermore, injured mice turned more frequently toward the healthy side up to 17 days after the surgery. This tendency resulted in increased clockwise movements in home cage recordings. Moreover, tail suspension and twisting toward the healthy side induced a physical sign for up to 14 days after the injury; the mice rapidly rotated with dorsal bending. Our analysis strategy employing deep learning helps to evaluate neuronal compensatory processes for an extended period and is useful for assessing the efficacy of therapeutic interventions.

Keywords

• Animal models
• Deep learning
• Open field test
• Ototoxicity
• Unilateral hearing loss