Biomedical subjects

T G Forrest

Publications and source records attributed to T G Forrest.

6 recordsLinked to original sources

PubMed1992

The role of frequency selectivity in measures of auditory and vibrotactile temporal resolution.

The purpose of this study was to compare the role of frequency selectivity in measures of auditory and vibrotactile temporal resolution. In the first experiment, temporal modulation transfer functions for a sinusoidally amplitude modulated (SAM) 250-Hz carrier revealed auditory modulation thresholds significantly lower than corresponding vibrotactile modulation thresholds at SAM frequencies greater than or equal to 100 Hz. In the second experiment, auditory and vibrotactile gap detection thresholds were measured by presenting silent gaps bounded by markers of the same or different frequency. The marker frequency F1 = 250 Hz preceded the silent gap and marker frequencies after the silent gap included F2 = 250, 255, 263, 310, and 325 Hz. Auditory gap detection thresholds were lower than corresponding vibrotactile thresholds for F2 markers less than or equal to 263 Hz, but were greater than the corresponding vibrotactile gap detection thresholds for F2 markers greater than or equal to 310 Hz. When the auditory gap detection thresholds were transformed into filter attenuation values, the results were modeled well by a constant-percentage (10%) bandwidth filter centered on F1. The vibrotactile gap detection thresholds, however, were independent of marker frequency separation. In a third experiment, auditory and vibrotactile rate difference limens (RDLs) were measured for a 250-Hz carrier at SAM rates less than or equal to 100 Hz. Auditory RDLs were lower than corresponding vibrotactile RDLs for standard rates greater than 10 Hz. Combination tones may have confounded auditory performance for standard rates of 80 and 100 Hz. The results from these experiments revealed that frequency selectivity influences auditory measures of temporal resolution, but there was no evidence of frequency selectivity affecting vibrotactile temporal resolution.

Adult↗

PubMed1991

Detection of silent temporal gaps in sinusoidal markers.

Gap detection thresholds were measured by forced-choice procedure for conditions where the duration of a silent gap was varied adaptively between pairs of sinusoidal markers of the same or different frequency. Frequencies of the first sinusoid in a pair of markers ranged from F1 = 500 to 4000 Hz. Second-sinusoid marker frequencies F2 included F1 = F2, and usually frequencies 2%, 5%, 24%, and 50% higher than F1. In preliminary studies the role of presentation level (E/N0) on gap detection was considered. Preliminary data revealed confounding extraneous factors arising from gating transients and from overall stimulus (i.e., markers + gap) and/or masker duration cues. In the main experiments, the contributions of these extraneous cues were evaluated with experimental designs aimed at identifying and minimizing the confounding roles of these cues in gap detection. For conditions where extraneous gating transient cues were minimized (by presenting the sinusoidal markers in a continuous noise masker with random onset phase for the second sinusoid in every pair of markers) and overall stimulus duration cues were diminished (by randomizing the duration of each marker independently), gap detection thresholds increased from 5 to 90 ms as the frequency separation between F1 and F2 was increased by half an octave. When the gap detection thresholds were treated as filter attenuation values by normalizing and converting the data into decibels, the data were closely fit by the roex filter model. On average, the listeners' performances were modeled well by a constant-percentage (7%) bandwidth filter centered on F1.

Attention↗

PubMed1989

Temporal gaps in noise and sinusoids.

The ability of human observers to detect partially filled or completely silent intervals (gaps) was measured using a variety of different waveforms. The slopes of the psychometric functions for gap detection using broadband noise are dependent upon the amount of noise remaining during the gap. For completely silent intervals, the psychometric function covers a range of only 2 ms, but the psychometric functions for partially filled intervals are less steep. The detection of gaps in narrow-band noise (surrounded by complementary band-reject maskers) is strongly influenced by the signal-to-noise ratio. The signal bandwidth and center frequency also influence detectability. Gap detection improved as signal bandwidth increased, and detection improved when signal bands containing gaps were centered at higher frequencies. Detection of gaps in single components of a 21-component, equal-amplitude complex also showed lower thresholds as the frequency of the component containing the gap increased. Increasing the number of components in the complex that contained the gap improved the detectability of the gap, more so when the gaps were all presented at the same time (synchronous condition). Uncertainty about the temporal position of the gap within the observation interval made the gap more difficult to detect. This temporal uncertainty effect occurred for gaps in broadband noise, in narrow-band noise, and in sinusoidal waveforms.

Acoustic Stimulation↗

PubMed1987

Frequency effects in profile analysis and detecting complex spectral changes.

Seven experiments on the detectability of intensity changes in complex multitonal acoustic spectra are reported. Two general questions organize the experimental efforts. The first question is how the detectability of a change in a flat (equal energy) spectrum depends on the frequency region where a single intensive change is made. The answer is that frequency region plays a relatively minor role. Frequency changes in the midregion of the spectrum are the easiest to hear, but thresholds increase by only about 5 dB over the range from 200 to 5000 Hz. For all frequencies, the psychometric function is of the form d' = k(delta p), where k is a constant and delta p is the change in pressure. The second question is how can we predict the detectability of complex changes over the entire frequency range from the detectability of change at each separate region. Thresholds for detecting a change from a flat spectrum to a spectrum whose amplitude varies in sinusoidal ("rippled") fashion over logarithmic frequency are measured at different frequencies of ripple. The thresholds are found to be independent of ripple frequency and are 7 dB higher than predicted on the basis of an optimum combination rule.

Adult↗

PubMed1987

Detection of partially filled gaps in noise and the temporal modulation transfer function.

Results of experiments on the detection of silent intervals, or gaps, in broadband noise are reported for normal-hearing listeners. In some preliminary experiments, a gap threshold of about 2 ms was measured. This value was independent of the duration of the noise burst, variation of the noise level on each presentation, or the temporal position of the gap within the noise burst. In the main experiments, the thresholds for partial decrements in the noise waveform as well as brief increments were determined. As predicted by a model that assumes a single fixed peak-to-valley detection ratio, thresholds for increments are slightly higher than thresholds for decrements when the signal is measured as the change in rms noise level. A first-order model describes the temporal properties of the auditory system as a low-pass filter with a 7- to 8-ms time constant. Temporal modulation transfer functions were determined for the same subjects, and the estimated temporal parameters agreed well with those estimated from the gap detection data. More detailed modeling was carried out by simulating Viemeister's three-stage temporal model. Simulations, using an initial stage bandwidth of 4000 Hz and a 3-ms time constant for the low-pass filter, generate data that are very similar to those obtained from human subjects in both modulation and gap detection.

Attention↗

PubMed1986

Profile analysis and background noise.

Spectral shape discrimination, or profile analysis, of complex waveforms (21 components) in the presence of broadband noise and special sinusoidal maskers of random amplitude was studied. The first experiment involved the discrimination between a standard flat spectrum and a "rippled" spectrum in broadband noise of different spectrum levels. Thresholds obtained under control conditions, without noise or without a standard, were used to estimate constants of an equation that predict thresholds where standard and noise are both present. The model assumes an external variance, produced by the noise, is added linearly to an internal variance caused by the flat standard. The mean squared error is less than 2 dB. The second experiment involved the detection of an increment on the center component of the 21-component standard. Added to the standard was an additional masking sinusoid of random amplitude. Both the frequency and the range of the random amplitude were varied and both showed a systematic influence on the detectability of the 1000-Hz increment.

Attention↗