Deep behavioral phenotyping of diabetic neuropathy mouse model using an open field test

Abstract

Diabetic neuropathy (DN) presents significant challenges, impacting life quality with relentless pain, sensory deficits, and motor dysfunction. While behavioral assessments in rodents have been crucial for gauging neuropathic effects, 2D tracking has limitations in capturing nuanced behaviors. This study explores the 3D pose dynamics of nicotinamide (NA) and streptozotocin (STZ)-induced DN in mice, using an unsupervised machine learning algorithm and a 3D depth camera. DN was induced through intraperitoneal NA (240 mg/kg) and STZ (100 mg/kg) administration in the first week, with blood glucose and body weight monitoring in the second week. Behavioral evaluations, covering mechanical sensitivity and locomotor/exploratory activities, occurred in the second and third weeks. ‘Syllables’ define 3D modular components of mouse body language. Results revealed heightened sensitivity to mechanical stimuli in diabetic neuropathy mice. In the open field test, significant disparities in position, posture distance, and speed were noted, with no substantial height variance. Among 22 3D behavioral motifs, 14 exhibited significant differences linked to increased mechanical sensitivity, indicating heightened neuropathic pain, while 8 showed no variance. Additionally, diabetic neuropathy mice displayed enhanced symmetry, correlated with increased sensitivity to mechanical stimuli and an increased likelihood of transitioning between dissimilar behavioral syllables. In conclusion, this study unveils intricate 3D behavioral motifs and high-order patterns overlooked by 2D tracking in DN mice. It underscores the significance of 3D behavioral motifs and transitions, providing valuable insights into increased sensitivity to mechanical stimuli in diabetic neuropathy.