Prairie voles are socially monogamous rodents that form social bonds similar to those seen in primates. Social behavior investigation in these species, that include studying their breathing regulation, can provide us with an invaluable psychological model to understand social and emotional functions in both animals and humans. There have been several studies associated with the respiratory pattern of these species in the state of fear-induced defense. However, non-invasive measurement methods employed so far suffer from the lack of a natural experiment environment for the rodents. In this paper, we present a remote depth-based system, which applies a modified autocorrelation algorithm to automatically extract respiration patterns in small rodents. We evaluated our estimation accuracy through a series of experiments and comparing the extracted results with breathing rates obtained from visual inspection of synchronously collected RGB videos. In a preliminary test on a human participant, breathing rate was estimated with 100% accuracy, while the estimation accuracy was 94.8% for a restrained vole. Finally, we monitored the respiratory alternations of three voles in transition from a baseline, to a fearful state, and back to a normal state; the estimated breathing rates confirmed the existing hypothesis regarding animal defense strategies.