New software flags telltale squeaks in autistic rat model | Spectrum

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whine who: A new software tool analyzes rodent squeals according to the sources of the calls and their targets.

People are talking; the rats squeal. But rodents also communicate through inaudible ultrasonic vocalizations, which provide insight into their social behavior. A new software tool called TrackUSF can help researchers collect ultrasound data by recording vocalizations and detecting differences between them, according to a new report. study.

Whether ultrasonic vocalizations are strong analogues of people’s communication abilities is up for debate, but the tool could aid research in animal models of autism; such vocalizations are altered in animals with certain genetic mutations linked to autism, previous research has found.

TrackUSF uses an approach often used by human speech recognition software: identify signatures and compare them to each other, says lead researcher Shlomo Wagnerassociate professor of neurobiology and social behavior at the University of Haifa in Israel.

“The idea of ​​TrackUSF is to analyze the signature of [ultrasonic vocalizations] emitted by different groups of animals, such as [autism] models and their wild-type littermates, to compare them and identify the differences between them,” he says.

Wagner and his team classified the signatures using a measure called Mel frequency cepstral coefficients (MFCCs). Coefficients are meant to represent what a listener actually hears, and they correspond to sounds of different frequencies divided into distinct units.

The benefits of TrackUSF, Wagner says, are that it can be used for any condition, on many animals at once, and users generally don’t need explicit training. “Also, unlike previous tools, TrackUSF can be used for animals other than rats and mice, such as bats.”

OWhile some vocalization analysis tools require experts to train them on reference or baseline audio samples beforehand, TrackUSF is designed to identify changes in vocalization between groups without any prior training, says Wagner.

Vocal groups: Some types of rat vocalizations showed clear patterns based on sources and intended recipients, while others were less consistent.

To that end, he and his team tested the tool on wild-type rats and rats lacking one or both copies of the autism-linked gene SHANK3. Across 109 recording sessions, TrackUSF categorized animal calls into distinct groups, grouped by both the animal making the vocalization and the intended listener. For example, wild-type and SHANK3 rats tended to make similar sounds when communicating with their cagemates, but not when communicating with unfamiliar rats.

Adapting human voice analysis techniques for use with rodent squeals introduces problems when it comes to processing the sounds, says Ryōsuke Tachibana, an associate professor of behavioral neuroscience at the University of Tokyo in Japan, who was not involved in the work. “MFCC emphasizes frequency resonance patterns in the vocal tract using signal harmonic structures,” making it a good unit of measurement for analyzing the human voice, he says, but when When it comes to mouse vocalizations, which usually have no harmonics, MFCC may not be the best measure.

TrackUSF is not designed to characterize ultrasonic vocalizations in detail, notes Wagner. But even high-level screening could be useful for researchers looking for any changes from baseline characteristics in rats.

“For example, a pharmaceutical company can use it to examine their drug library and find which drug restores typical vocalizations in SHANK3 rats, indicating possible drug treatments for Phelan-McDermid syndrome,” he says. “All they have to do is place ultrasound microphones in the animal cages and use TrackUSF for analysis.”

Cite this article: https://doi.org/10.53053/QROX5528

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