Biomedical subjects

C Kaernbach

Publications and source records attributed to C Kaernbach.

4 recordsLinked to original sources

PubMed1992

On the consistency of tapping to repeated noise.

Repeated noise at 1-4 cycles per second evokes an effortless heard rhythmic sensation which is often heard as "clanks" and "rasping." Tapping in synchrony with the period of the perceived structure is easy and consistent within one presentation. The present study addresses the question of whether the tapping to presentations at different times is consistent across presentations and across subjects. Nine listeners from three countries were presented with repeated Gaussian noise samples in 300 separate cyclical presentations. Nine samples of Gaussian noise with sample lengths ranging from 500 to 700 ms were used. In each of the presentations, one of these samples was selected at random and presented cyclically with transientless juxtapositions. The listeners were instructed to tap in synchrony with the perceived structure (i.e., once per period). Tapping to later presentations of a given sample was found to be consistent with prior tapping to the same sample: In most cases, one or two different tapping points per noise sample could be reproduced in different presentations. In the case of two possible tapping points in different presentations, the two points are usually far away from each other (most likely half a period away). The correlation between subjects is noticeable, although not perfect. The correlation between subjects of the same country is not significantly higher. The noise generating algorithm is given explicitly to allow subsequent studies to use exactly the same noises.

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PubMed1991

Poisson signal-detection theory: link between threshold models and the Gaussian assumption.

The Gaussian model of signal detection cannot fit asymmetric data as long as the variances of the distributions are kept equal. It is therefore common practice to assume unequal variances in order to fit these data. But this assumption leads to the well-known crossover problem. The present paper provides new arguments for the abandonment of the Gaussian model with unequal variances. In its stead, this paper reevaluates multiple-parallel-threshold models. In particular, the Poisson model turns out to be very useful: it can handle data with any degree of asymmetry, giving a reasonable interpretation of the two parameters of the receiver-operating characteristic. The three-state-threshold model (Krantz, 1969) is given a new interpretation in light of the Poisson model. The slope of Poisson double-probability plots turns out to be much closer to unity than is predicted by the Gaussian approximation.

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PubMed1991

Simple adaptive testing with the weighted up-down method.

This paper proposes a method for adaptive testing that is less complicated than the commonly used transformed up-down methods (1 up 2 down, 1 up 3 down, etc.). In addition, the weighted up-down method can converge to any desired point of the psychometric function. The rule is very simple: Each correct response leads to a decrease in signal level, each incorrect response to an increase. The only difference from the simple up-down method (1 up 1 down) is that the steps upward and the steps downward are of a different size. The straightforward construction of the novel procedure pays off in efficiency and stability: A Monte Carlo simulation reveals a definite advantage, though small, of the weighted up-down method over the 1-up-2-down rule.

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PubMed1990

A single-interval adjustment-matrix (SIAM) procedure for unbiased adaptive testing.

A new unbiased adaptive procedure is described that requires only half as many presentations in achieving the same precision as the well-known two-interval forced-choice (2IFC) 2-step procedure. The procedure is based on a yes-no task which avoids redundant presentation time. Furthermore, certain psychophysical studies can only be realized with yes-no tasks. Every trial contains randomly presented signals or noises and the answer is either yes or no. The outcome (hit, miss, false alarm, correct rejection) is taken into account by adjusting the signal level in a staircase manner. The adjustment matrix is set up to induce a neutral response criterion. Its convergence point can be adjusted at will. The single-interval adjustment-matrix (SIAM) procedure is compared to von Békésy and 2IFC transformed up-down methods using a Monte-Carlo simulation. The SIAM procedure proves to be the fastest of the unbiased procedures. A test on four subjects verified these results. Implications for optimum track length and the number of reversals to discard are discussed.

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