Scientists at Carnegie Mellon University have discovered that our ears use the most efficient way to process the sounds we hear, from babbling brooks to wailing babies.
These results represent a significant advance in our understanding of how sound is encoded for transmission to the brain, according to the authors, whose work is published with an accompanying "News and Views" editorial in the Feb. 23 issue of Nature.
The research provides a new mathematical framework for understanding sound processing and suggests that our hearing is highly optimized in terms of signal coding--the process by which sounds are translated into information by our brains--for the range of sounds we experience. The same work also has far-reaching, long-term technological implications, such as providing a predictive model to vastly improve signal processing for better quality compressed digital audio files and designing brain-like codes for cochlear implants, which restore hearing to the deaf.
To achieve their results, the researchers took a radically different approach to analyzing how the brain processes sound signals. Abstracting from the neural code at the auditory nerve, they represented sound as a discrete set of time points, or a "spike code," in which acoustic components are represented only in terms of their temporal relationship with each other. That's because the intensity and basic frequency of a given feature are essentially "kernalized," or compressed mathematically, into a single spike. This is similar to a player piano roll that can reproduce any song by recording what note to press when the spike code encodes any natural sound in terms of the precise timings of the elemental acoustic features. Remarkably, when the researchers derived the optimal set of features for natural sounds, they corresponded exactly to the patterns observed by neurophysiologists in the auditory nerves.
"We've found that timing of just a sparse number of spikes actually encodes the whole range of nature sounds, including components of speech such as vowels and consonants, and natural environment sounds like footsteps in a forest or a flowing stream," said Michael Lewicki, associate professor of computer science at Carnegie Mellon and a member of the Center for the Neural Basis of Cognition (CNBC). "We found that the optimal code for natural sounds is the same as that for speech. Oddly enough, cats share our own optimal auditory code for the English language."
"Our work is the only research to date that efficiently processes auditory code as kernalized spikes," said Evan Smith, a graduate student in psychology at the CNBC.