Effects of Musical Training and Hearing Loss on Fundamental Frequency Discrimination and Temporal Fine Structure Processing: Psychophysics and Modeling

Several studies have shown that musical training leads to improved fundamental frequency (F-0) discrimination for young listeners with normal hearing (NH). It is unclear whether a comparable effect of musical training occurs for listeners whose sensory encoding of F-0 is degraded. To address this question, the effect of musical training was investigated for three groups of listeners (young NH, older NH, and older listeners with hearing impairment, HI). In a first experiment, F-0 discrimination was investigated using complex tones that differed in harmonic content and phase configuration (sine, positive, or negative Schroeder). Musical training was associated with significantly better F-0 discrimination of complex tones containing low-numbered harmonics for all groups of listeners. Part of this effect was caused by the fact that musicians were more robust than non-musicians to harmonic roving. Despite the benefit relative to their non-musicians counterparts, the older musicians, with or without HI, performed worse than the young musicians. In a second experiment, binaural sensitivity to temporal fine structure (TFS) cues was assessed for the same listeners by estimating the highest frequency at which an interaural phase difference was perceived. Performance was better for musicians for all groups of listeners and the use of TFS cues was degraded for the two older groups of listeners. These findings suggest that musical training is associated with an enhancement of both TFS cues encoding and F-0 discrimination in young and older listeners with or without HI, although the musicians' benefit decreased with increasing hearing loss. Additionally, models of the auditory periphery and midbrain were used to examine the effect of HI on F-0 encoding. The model predictions reflected the worsening in F-0 discrimination with increasing HI and accounted for up to 80% of the variance in the data.