Estimating human neural tuning curves at low-level sound from human psychophysical masking data and the cochlea-frequency maps

Abstract

We proposed a three-slope method to estimate human frequency tuning curves at low sound levels. As a starting point, cat neural excitation patterns (Allen and Fahey, 1993) are derived from Liberman’s cat cochlea neural tuning curves data (Liberman, 1978) in a mathematical way. A three-slope structure inspired by (Rhode,1978) is proposed to represent neural excitation patterns. The aim of this paper is to estimate the three-slope structure for human neural excitation patterns and then transform human neural excitation patterns into human tuning curves by using a human cochlea-frequency map (Greenwood, 1990). In 1993, Allen and Fahey introduced the concept of the second cochlea map, which was shown to be highly correlated with both neural excitation patterns and distortion product otoacoustic emissions (DPOAE). Thus, three slopes of human neural excitation patterns may be estimated via the second cochlea map and human masking data (Wegel and Lane, 1924). In the present study, slopes are estimated from limited existing psychophysical data, which can be improved with more accurate experimental data in the future.