Rodents are a cornerstone of neuroscience and physiology research, but the methods for monitoring
behavior and physiology in these animals suffer from several key limitations. Monitoring physiological
processes such as heart rate, breathing, and muscle activity requires invasive sensors that impede natural
behavior of the animals. Similarly, behavioral assays can require highly constraining apparatus. This proposal
is based on the hypothesis that we can greatly improve the sensitivity, accuracy, and reliability of rodent
behavior quantification by taking advantage of a stream of information that, to date, has been completely
ignored. When an animal is behaving in an environment, muscle contractions associated with breathing, heart
rate, and voluntary and involuntary movements apply subtle forces to the surfaces the animal contacts. These
forces generate elastic waves that propagate through the material (i.e., waveguide) at ultrasonic frequencies.
The overarching hypothesis of this proposal is that these elastic waves - Guided Ultrasonic Waves (GUWs) -
provide valuable information about mouse physiology, behavior, and underlying mental states. Under this
proposal we will test the hypothesis that GUWs can be used to non-invasively track low-amplitude responses,
such as breathing, heart rate, and startle, which currently can only be monitored using invasive or highly
constraining apparatus. In addition, we predict that GUWs can be used to improve the sensitivity and accuracy
with which other rodent behaviors can be identified and tracked. We will conduct experiments in which GUWs
are recorded as mice explore an arena outfitted with piezoelectric sensors. We will simultaneously record
information about physiology and behavior using traditional video tracking and implanted telemetry devices. By
comparing these streams of information, we will identify GUW features that report mouse heart rate, startle,
and a variety of other behaviors. In addition, we will use supervised and unsupervised machine learning
approaches to develop GUW metrics that precisely and accurately classify behaviors that cannot be detected
using current methods. Completion of these aims will yield hardware and associated analytics that will enhance
the precision and objectivity of rodent behavior monitoring and allow researchers to simultaneously monitor
behavior and physiology without the need for restrictive or invasive apparatus. Our goal is that the
piezoelectric-based apparatus and associated analyses developed here will allow labs without specialized
equipment or expertise to perform precise monitoring of mouse behavior and physiology without the need for
invasive test equipment.