Exponential modeling of human frequency-following responses to voice pitch.

OBJECTIVE

Recent studies have shown that the frequency-following response (FFR) to voice pitch can be a useful method to evaluate the signal-processing mechanisms and neural plasticity in the human brainstem. The purpose of this study was to examine the quantitative properties of the FFR trends with an exponential curve-fitting model.

DESIGN

FFR trends obtained with increasing number of sweeps (up to 8000 sweeps) at three stimulus intensities (30, 45, and 60 dB nHL) were fit to an exponential model that consisted of estimates of background noise amplitude, asymptotic response amplitude, and a time constant. Five objective indices (Frequency Error, Slope Error, Tracking Accuracy, Pitch Strength and RMS Ratio) were used to represent different perspectives of pitch processing in the human brainstem.

STUDY SAMPLE

Twenty-three native speakers (16 males; age = 24.7 ± 2.1 years) of Mandarin Chinese were recruited.

RESULTS

The results demonstrated that the exponential model provided a good fit (r(2) = 0.89 ± 0.10) to the FFR trends with increasing number of sweeps for the five objective indices.

CONCLUSIONS

The exponential model, combined with the five objective indices, can be used for difficult-to-test patients and may prove to be useful as an assessment and diagnostic method in both clinical and basic research efforts.