Project Summary
Despite ongoing advances in auditory prostheses, patients with hearing loss often have difficulty understanding
speech and other important sounds in noisy environments. This is due, in part, to degraded spatial and
spectral sound information, which is leveraged by normal-hearing listeners to parse concurrent sounds in the
real world. Current understanding of spatial processing is drawn primarily from studies in which the subject is
head-fixed relative to the sound sources. Despite this dominant experimental paradigm, listeners in real-world
conditions typically move through space while orienting their head to improve their ability to understand
auditory signals. The existence of neural connections between the vestibular, motor, and auditory systems
suggests that a listener's movement and body posture provide substantial input to the auditory system to
facilitate hearing. A better understanding of how the healthy auditory system operates while moving through an
acoustic environment will support new treatments for auditory disorders.
The current study will investigate how information about a listener's motion and body/head posture influence
sound processing in the auditory cortex. Historically, studies in free-moving subjects have been limited by the
difficulty of precisely measuring auditory input during unconstrained movement through a complex sound field.
Recent advances in computing, machine learning, and neural recording technology now make this problem
tractable. There are two specific aims. The first is to simultaneously record from large numbers of auditory
cortex neurons during free movement through a calibrated sound field. These experiments will develop the
equipment, experimental approach, and computational techniques needed to accurately track the sound input
to each ear during movement through an auditory scene. The second aim will evaluate how the position and
self-motion impact sound coding in auditory cortex. Recently developed methods use artificial neural networks
to predict the activity in single neurons evoked by complex natural sounds. These algorithms will be updated to
include body posture and self-motion as inputs, allowing measurement of how response properties may
change based on these variables. By characterizing dynamic sound coding in free-moving animals, these
studies will provide new insight into how the auditory system processes sound under more natural conditions
and can support improved signal processing algorithms for auditory prostheses.