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Many hearing-impaired listeners suffer from distorted auditory processing capabilities. This study examines which aspects of auditory coding (i.e., intensity, time, or frequency) are distorted and how this affects speech perception. The distortion-sensitivity model is used: The effect of distorted auditory coding of a speech signal is simulated by an artificial distortion, and the sensitivity of speech intelligibility to this artificial distortion is compared for normal-hearing and hearing-impaired listeners. Stimuli (speech plus noise) are wavelet coded using a complex sinusoidal carrier with a Gaussian envelope (1/4 octave bandwidth). Intensity information is distorted by multiplying the modulus of each wavelet coefficient by a random factor. Temporal and spectral information are distorted by randomly shifting the wavelet positions along the temporal or spectral axis, respectively. Measured were (1) detection thresholds for each type of distortion, and (2) speech-reception thresholds for various degrees of distortion. For spectral distortion, hearing-impaired listeners showed increased detection thresholds and were also less sensitive to the distortion with respect to speech perception. For intensity and temporal distortion, this was not observed. Results indicate that a distorted coding of spectral information may be an important factor underlying reduced speech intelligibility for the hearing impaired.

Hearing-impaired listeners are known to suffer from reduced speech intelligibility in noise, even if sounds are above their hearing thresholds. This study examined the possible contribution of reduced acuity of intensity coding to this problem. The "distortion-sensitivity model" was used: the effect of reduced acuity of auditory intensity coding on intelligibility was mimicked by an artificial distortion of the speech intensity coding, and the sensitivity to this distortion for hearing-impaired listeners was compared with that for normal-hearing listeners. Stimuli (speech plus noise) were wavelet coded using a Gaussian wavelet (1/4-octave bandwidth). The intensity coding was distorted by multiplying the modulus of each wavelet coefficient by a random factor. Speech-reception thresholds (SRTs) were measured for various degrees of intensity perturbation. Hearing-impaired listeners were classified as suffering from suprathreshold deficits if intelligibility of undistorted speech was worse than predicted from audibility by the speech intelligibility index model [ANSI, ANSI S3.5-1997 (1997)]. Hearing-impaired listeners without suprathreshold deficits were as sensitive to the intensity distortion as the normal-hearing listeners. Hearing-impaired listeners with suprathreshold deficits appeared to be less sensitive. Results indicate that reduced acuity of auditory intensity coding may be a factor underlying reduced speech intelligibility in noise for the hearing impaired.

The just-noticeable difference in intensity jnd(I) was measured for 1-kHz tones with a Gaussian-shaped envelope as a function of their spectro-temporal shape. The stimuli, with constant energy and a constant product of bandwidth and duration, ranged from a long-duration narrow-band "tone" to a short-duration broadband "click." The jnd(I) was measured in three normal-hearing listeners at sensation levels of 0, 10, 20, and 30 dB in 35 dB(A) SPL pink noise. At intermediate sensation levels, jnd(I) depends on the spectro-temporal shape: at the extreme shapes (tones and clicks), intensity discrimination performance is best, whereas at intermediate shapes the jnd(I) is larger. Similar results are observed at a higher overall sound level, and at a higher carrier frequency. The maximum jnd(I) is observed for stimuli with an effective bandwidth of about 1/3 octave and an effective duration of 4 ms at 1 kHz (1 ms at 4 kHz). A generalized multiple-window model is proposed that assumes that the spectro-temporal domain is partitioned into "internal" auditory frequency-time windows. The model predicts that intensity discrimination thresholds depend upon the number of windows excited by a signal: jnd(I) is largest for stimuli covering one window.

The problem of obtaining the retinal source distribution that generates the electroretinogram (ERG) from measured skin potentials is addressed. A realistic three-dimensional (3-D) volume conductor model of the head is constructed from magnetic resonance image (MRI) data sets. The skin potential distribution generated in this model by a dipole layer source at the retina is computed by using the boundary element method (BEM). The influence of the various compartments of the complete model on the results was investigated, and a simplified model was defined. An inverse procedure for estimating the source distribution at the retina from ERG's obtained from skin electrodes was developed. The procedure was tested on simulated potentials. A fair correspondence between the original and estimated source distribution was found. Furthermore, the ERG's measured at seven skin electrodes were used to estimate the source distribution at the retina. The ERG potential waveform at an additional skin electrode was computed from this source distribution and compared to the measured potential at this electrode. Again a fair correspondence was obtained. It is concluded that the methods may become a useful tool for clinical applications, i.e., for the assessment of localized defects in retinal function.