Paper Info
Title
A Neuronal Network Model for Pitch Selectivity and Representation.
Abstract
Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among convergent auditory nerve fibers across frequency channels. Their selectivity for only very fast rising slopes of convergent input enables these slope-detectors to distinguish the most prominent coincidences in multi-peaked input time courses. Pitch can then be estimated from the first-order interspike intervals of the slope-detectors. The regular firing pattern of the slope-detector neurons are similar for sounds sharing the same pitch despite the distinct timbres. The decoded pitch strengths also correlate well with the salience of pitch perception as reported by human listeners. Therefore, our model can serve as a neural representation for pitch. Our model performs successfully in estimating the pitch of missing fundamental complexes and reproducing the pitch variation with respect to the frequency shift of inharmonic complexes. It also accounts for the phase sensitivity of pitch perception in the cases of Schroeder phase, alternating phase and random phase relationships. Moreover, our model can also be applied to stochastic sound stimuli, iterated-ripple-noise, and account for their multiple pitch perceptions.
Year
DOI
Venue
2016
10.3389/fncom.2016.00057
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
Keywords
Field
DocType
pitch,slope-detector,missing fundamental,inharmonics,alternating phase,Schroeder phase,iterated-ripple-noise
Relative pitch,Fundamental frequency,Audio time-scale/pitch modification,Computer science,Speech recognition,Coincidence detection in neurobiology,Biological neural network,Pitch detection algorithm,Pitch (Music),Missing fundamental
Journal
Volume
ISSN
Citations 
10
1662-5188
3
PageRank 
References 
Authors
0.41
2
2
Name
Order
Citations
PageRank
Chengcheng Huang130.41
John Rinzel2459219.68