The Psychophysics Psyber Lab




Alan Taylor's Thesis

Auditory psychophysics in birds:
The effects of unique noise on sensitivity


Submitted for the degree of Doctor of Philosophy in Psychology
Victoria University of Wellington, New Zealand


The performances of observers in auditory experiments are likely to be affected by extraneous noise from physiological or neurological sources and also by decision noise. Attempts have been made to measure the characteristics of this noise. In particular its level relative to that of masking noise provided by the experimenter. This study investigated an alternative approach, a method of analysis which seeks to reduce the effects of extraneous noise on measures derived from experimental data.

Group-Operating-Characteristic (GOC) analysis was described by Watson (1963) and investigated by Boven (1976). Boven distinguished between common and unique noise. GOC analysis seeks to reduce the effects of unique noise.

In the analysis, ratings of the same stimulus on different occasions are summed. The cumulative frequency distributions of the resulting variable define a GOC curve. This curve is analogous to an ROC curve, but since the effects of unique noise tend to be averaged out during the summation, the GOC is less influenced by extraneous noise. The amount of improvement depends on the relative variance of the unique and common noise (k). Higher levels of unique noise lead to greater improvement.

In this study four frequency discrimination experiments were carried out with pigeons as observers, using a three-key operant procedure. In other experiments, computer-simulated observers were used.

The first two pigeon experiments, and the simulations, were based on known distributions of common noise. The ROCs for the constructed distributions provided a standard with which the GOC curve could be compared. In all the cases the analysis led to improvements in the measures of performance and increased the match of the experimental results and the ideal ROC.

The amount of improvement, as well as reflecting the level of unique noise, depended on the number of response categories. With smaller numbers of categories, improvement was reduced and k was underestimated. Since the pigeon observers made only "yes" or "no" responses, the results for the pigeon experiments were compared with the results of simulations with known distributions in order to obtain more accurate estimates of k.

The third and fourth pigeon experiments involved frequency discrimination tasks with a standard 450 Hz and comparison frequencies of 500, 600, 700, 800 and 900 Hz, and 650 Hz, respectively. With the multiple comparison frequencies the results were very variable. This was due to the small number of trials for each frequency and the small number of replications. The results obtained with one comparison frequency were more orderly but, like those of the previous experiment, were impossible to distinguish from those which would be expected if there was no common noise.

A final set of experiments was based on a hardware simulation. Signals first used in the fourth pigeon experiment were processed by a system made up of a filter, a zero-axis crossing detector and a simulated observer. The results of these experiments were compatible with the possibility that the amount of unique noise in the pigeon experiments overwhelmed any evidence of common noise.

Last updated 09 Nov 2009 11:39 AM

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