A Subtype of Ultrasonic Vocalizations during Palatable Food Consumption in Rats Identified by Machine Learning-Assisted Classification.

Identifying behavioral and physiological responses to rewarding stimuli is essential for understanding positive emotional states in animals and for investigating their neural basis. Ultrasonic vocalizations (USVs) in rats are modulated by various behavioral contexts and are thought to represent affective-like states. However, their diversity during palatable food consumption remains underexplored. In this study, we investigated acoustic features of USVs in male rats consuming chocolate, a highly palatable food. Using a machine learning-assisted logistic regression model trained on spectrogram features, we identified a distinct USV subtype-the 40 kHz inverted-U type-that was selectively emitted during chocolate consumption. The emission of this subtype was tightly time-locked to chocolate-feeding behavior. Systemic administration of naloxone, an opioid receptor antagonist, significantly reduced the emission of the 40 kHz inverted-U USVs during chocolate intake. Direct comparison with standard food pellet consumption revealed that 40 kHz flat USVs occurred at comparable levels across both conditions, whereas 40 kHz inverted-U USVs were significantly more frequent during chocolate consumption. These findings suggest that these USVs may reflect internal states associated with palatable feeding and are under modulation by the endogenous opioid system. Moreover, our data demonstrate the utility of machine learning for high-throughput, objective classification of USV subtypes. This framework provides a promising approach for decoding emotion-related vocal expressions in rats and highlights the potential of specific USVs as behavioral readouts for studying the neurobiology of positive emotions.