MIT Research on Pitch Perception Could Lead to Better Cochlear Implants

CAMBRIDGE, MASSACHUSSETTS — New research from MIT neuroscientists suggests that natural soundscapes have shaped our sense of hearing, optimizing it for the kinds of sounds we most often encounter.

In a study reported Dec. 14 in the journal Nature Communications, researchers led by McGovern Institute for Brain Research associate investigator Josh McDermott used computational modeling to explore factors that influence how humans hear pitch. Their model’s pitch perception closely resembled that of humans — but only when it was trained using music, voices, or other naturalistic sounds.

Humans’ ability to recognize pitch — essentially, the rate at which a sound repeats — gives melody to music and nuance to spoken language. Although this is arguably the best-studied aspect of human hearing, researchers are still debating which factors determine the properties of pitch perception, and why it is more acute for some types of sounds than others. McDermott, who is also an associate professor in MIT’s Department of Brain and Cognitive Sciences, and an Investigator with the Center for Brains, Minds, and Machines (CBMM) at MIT, is particularly interested in understanding how our nervous system perceives pitch because cochlear implants, which send electrical signals about sound to the brain in people with profound deafness, don’t replicate this aspect of human hearing very well.

“Cochlear implants can do a pretty good job of helping people understand speech, especially if they’re in a quiet environment. But they really don’t reproduce the percept of pitch very well,” says Mark Saddler, a graduate student and CBMM researcher who co-led the project and an inaugural graduate fellow of the K. Lisa Yang Integrative Computational Neuroscience Center.

“One of the reasons it’s important to understand the detailed basis of pitch perception in people with normal hearing is to try to get better insights into how we would reproduce that artificially in a prosthesis.”

 

Artificial Hearing

 

Pitch perception begins in the cochlea, the snail-shaped structure in the inner ear where vibrations from sounds are transformed into electrical signals and relayed to the brain via the auditory nerve. The cochlea’s structure and function help determine how and what we hear. And although it hasn’t been possible to test this idea experimentally, McDermott’s team suspected our “auditory diet” might shape our hearing as well.

To explore how both our ears and our environment influence pitch perception, McDermott, Saddler, and Research Assistant Ray Gonzalez built a computer model called a deep neural network. Neural networks are a type of machine learning model widely used in automatic speech recognition and other artificial intelligence applications. Although the structure of an artificial neural network coarsely resembles the connectivity of neurons in the brain, the models used in engineering applications don’t actually hear the same way humans do — so the team developed a new model to reproduce human pitch perception. Their approach combined an artificial neural network with an existing model of the mammalian ear, uniting the power of machine learning with insights from biology.

“These new machine-learning models are really the first that can be trained to do complex auditory tasks and actually do them well, at human levels of performance,” says Saddler.

Read full story on MIT’s website.


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