An open-source tool based on computational vision and machine learning shows high accuracy and sensitivity in the analysis of ultrasonic vocalizations.

The accuracy of the Hybrid Vocalization Localizer (HyVL) brings a revolution to the study of social vocalizations of rodents and other animals, where vocalizations often occur in close proximity, and will empower downstream analysis of sequence and semantic analyses.

Inhibitory neurons in the hypothalamus and amygdala push and pull on the midbrain vocal gating circuit to trigger and suppress ultrasonic vocalization (USV) production in the mouse.

Snout-to-snout contact modulates the response of rat auditory cortex to calls from other animals, indicating that the multisensory nature of social interaction is directly represented in the rat brain.

A microphone array enables the vocal contribution of each socially interacting individual to be quantified, and reveals that vocalizations are exchanged between the sexes during mouse courtship.

The decision to vocalize depends on neural circuits that balance the rewards of potential social affiliation with the risks of advertising.

DAS is a universal tool for segmenting and identifying acoustic signals in single and multi channel recordings robustly, reliably, and at low latency.

Successful autism spectrum disorder gene discovery using forward genetics identifies KDM5A, which encodes a histone H3 lysine 4 demethylase, as a disease gene.

Cerebellar-periaqueductal grey interactions contribute to fear-conditioned processes and, as such, provide a novel target for treating psychological conditions including post-traumatic stress disorder.