The optimum decision rules for the oddity task

Sensorineural hearing loss alters auditory discrimination of natural soundscapes

OBJECTIVE

The ability to discriminate natural soundscapes recorded in a temperate terrestrial biome was measured in 15 hearing-impaired (HI) listeners with bilateral, mild to severe sensorineural hearing loss and 15 normal-hearing (NH) controls.

DESIGN

Soundscape discrimination was measured using a three-interval oddity paradigm and the method of constant stimuli. On each trial, sequences of 2-second recordings varying the habitat, season and period of the day were presented diotically at a nominal SPL of 60 or 80 dB.

RESULTS

Discrimination scores were above chance level for both groups, but they were poorer for HI than NH listeners. On average, the scores of HI listeners were relatively well accounted for by those of NH listeners tested with stimuli spectrally-shaped to match the frequency-dependent reduction in audibility of individual HI listeners. However, the scores of HI listeners were not significantly correlated with pure-tone audiometric thresholds and age.

CONCLUSIONS

These results indicate that the ability to discriminate natural soundscapes associated with changes in habitat, season and period of the day is disrupted but it is not abolished. The deficits of the HI listeners are partly accounted for by reduced audibility. Supra-threshold auditory deficits and individual listening strategies may also explain differences between NH and HI listeners.

Auditory discrimination of natural soundscapes

A previous modelling study reported that spectro-temporal cues perceptually relevant to humans provide enough information to accurately classify "natural soundscapes" recorded in four distinct temperate habitats of a biosphere reserve [Thoret, Varnet, Boubenec, Ferriere, Le Tourneau, Krause, and Lorenzi (2020). J. Acoust. Soc. Am. 147, 3260]. The goal of the present study was to assess this prediction for humans using 2 s samples taken from the same soundscape recordings. Thirty-one listeners were asked to discriminate these recordings based on differences in habitat, season, or period of the day using an oddity task. Listeners' performance was well above chance, demonstrating effective processing of these differences and suggesting a general high sensitivity for natural soundscape discrimination. This performance did not improve with training up to 10 h. Additional results obtained for habitat discrimination indicate that temporal cues play only a minor role; instead, listeners appear to base their decisions primarily on gross spectral cues related to biological sound sources and habitat acoustics. Convolutional neural networks were trained to perform a similar task using spectro-temporal cues extracted by an auditory model as input. The results are consistent with the idea that humans exclude the available temporal information when discriminating short samples of habitats, implying a form of a sub-optimality.

A general formula for computing maximum proportion correct scores in various psychophysical paradigms with arbitrary probability distributions of stimulus observations

Proportion correct (Pc) is a fundamental measure of task performance in psychophysics. The maximum Pc score that can be achieved by an optimal (maximum-likelihood) observer in a given task is of both theoretical and practical importance, because it sets an upper limit on human performance. Within the framework of signal detection theory, analytical solutions for computing the maximum Pc score have been established for several common experimental paradigms under the assumption of Gaussian additive internal noise. However, as the scope of applications of psychophysical signal detection theory expands, the need is growing for psychophysicists to compute maximum Pc scores for situations involving non-Gaussian (internal or stimulus-induced) noise. In this article, we provide a general formula for computing the maximum Pc in various psychophysical experimental paradigms for arbitrary probability distributions of sensory activity. Moreover, easy-to-use MATLAB code implementing the formula is provided. Practical applications of the formula are illustrated, and its accuracy is evaluated, for two paradigms and two types of probability distributions (uniform and Gaussian). The results demonstrate that Pc scores computed using the formula remain accurate even for continuous probability distributions, as long as the conversion from continuous probability density functions to discrete probability mass functions is supported by a sufficiently high sampling resolution. We hope that the exposition in this article, and the freely available MATLAB code, facilitates calculations of maximum performance for a wider range of experimental situations, as well as explorations of the impact of different assumptions concerning internal-noise distributions on maximum performance in psychophysical experiments.

Evidence of across-channel processing for spectral-ripple discrimination in cochlear implant listeners

Spectral-ripple discrimination has been used widely for psychoacoustical studies in normal-hearing, hearing-impaired, and cochlear implant listeners. The present study investigated the perceptual mechanism for spectral-ripple discrimination in cochlear implant listeners. The main goal of this study was to determine whether cochlear implant listeners use a local intensity cue or global spectral shape for spectral-ripple discrimination. The effect of electrode separation on spectral-ripple discrimination was also evaluated. Results showed that it is highly unlikely that cochlear implant listeners depend on a local intensity cue for spectral-ripple discrimination. A phenomenological model of spectral-ripple discrimination, as an "ideal observer," showed that a perceptual mechanism based on discrimination of a single intensity difference cannot account for performance of cochlear implant listeners. Spectral modulation depth and electrode separation were found to significantly affect spectral-ripple discrimination. The evidence supports the hypothesis that spectral-ripple discrimination involves integrating information from multiple channels.

Some Memories are Odder than Others: Judgments of Episodic Oddity Violate Known Decision Rules

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment of episodic oddity, whereby participants select the mnemonically odd members of triplets (e.g., a new item hidden among two studied items). Using the only two known signal-detection rules of oddity judgment derived from the sensory perception literature, the unequal variance signal-detection model predicted that an old item among two new items would be easier to discover than a new item among two old items. In contrast, four separate empirical studies demonstrated the reverse pattern: triplets with two old items were the easiest to resolve. This finding was anticipated by the dual-process approach as the presence of two old items affords the greatest opportunity for recollection. Furthermore, a bootstrap-fed Monte Carlo procedure using two independent datasets demonstrated that the dual-process parameters typically observed during single item recognition correctly predict the current oddity findings, whereas unequal variance signal-detection parameters do not. Episodic oddity judgments represent a case where dual- and single-process predictions qualitatively diverge and the findings demonstrate that novelty is "odder" than familiarity.

On the choice of adequate randomization ranges for limiting the use of unwanted cues in same-different, dual-pair, and oddity tasks

A major concern when designing a psychophysical experiment is that participants may use a stimulus feature (cue) other than that intended by the experimenter. One way to avoid this problem is to apply random variations to the corresponding feature across stimulus presentations to make the unwanted cue unreliable. An important question facing experimenters who use this randomization (roving) technique is how large the randomization range should be to ensure that the participants cannot achieve a certain proportion correct by using the unwanted cue, while at the same time avoiding unnecessary interference of the randomization with task performance. Previous researchers have provided formulas for the selection of adequate randomization ranges in yes-no and multiple-alternative forced choice tasks. In this article, we provide figures and tables that can be used to select randomization ranges that are better suited to experiments involving a same-different, dual-pair, or oddity task.

Likelihood ratio, optimal decision rules, and relationship between proportion correct and d' in the dual-pair AB-versus-BA identification paradigm

The equal-variance Gaussian signal detection theory (SDT) decision model for the dual-pair (4IAX) change-detection paradigm has been described in earlier publications. In this research article, we consider the equal-variance Gaussian SDT model for the related 4IAX AB-versus-BA identification paradigm. The likelihood ratios, optimal decision rules, receiver-operating characteristics (ROCs), and relationships between d' and proportion correct (PC) are analyzed for two special cases: that of statistically independent observations, which typically applies in constant-stimuli experiments, and that of highly correlated observations, which typically applies in experiments where stimuli are roved widely across trials or pairs. A surprising outcome of this analysis is that, although these two situations lead to different optimal decision rules, the predicted ROCs and PC responses for these two cases are not substantially different and are either identical to or similar to those observed in the basic yes-no paradigm. Supplemental materials for this study can be downloaded from app.psychonomic-journals.org/content/supplemental.

Likelihood ratio, optimal decision rules, and correct response probabilities in a signal detection theoretic, equal-variance Gaussian model of the observer in the 4IAX paradigm

This article provides a synthetic account of the likelihood ratio, optimal decision rules, and correct response probabilities in a signal detection theoretic model of the observer in the dual-pair comparison, or four-interval AX (4IAX), paradigm. The model assumes a static sampling process, resulting in four, equal-variance normally distributed (i.e., Gaussian) observations on each trial First, a likelihood ratio equation allowing for an arbitrary degree of correlation between observations is provided. Specific solutions for the cases of independent and highly correlated observations are then derived. It is shown that these solutions, and the associated decision rules, correspond to those provided independently in earlier publications. A modified 4IAX paradigm involving, as a standard, an additional stimulus (C) located medially between the A and the B stimuli is also considered. It is shown that the optimal (static, equal-variance, Gaussian) decision model for this paradigm is unaffected by correlation between observations and is equivalent to the standard 4IAX with highly correlated observations. Finally, we consider how, under the considered (static, equal-variance, Gaussian) model, the proportion of correct responses in the different versions of the 4IAX paradigm is related to d', and a solution for the case of independent observations is provided.

A Thurstonian model for the dual pair (4IAX) discrimination method

In the dual pair method, the subject is presented with two stimuli in two pairs: One pair is composed of two samples of the same stimulus; the other pair is composed of two samples of different stimuli, one being the same as that in the identical pair. The task of the judge is to select the most different pair. The psychometric function for the dual pair method is derived and expressed in terms of a singly noncentral beta distribution. A table is provided that connects a measure of the degree of difference, d, to the probability of a correct response. This table assumes an unbiased observer and differencing decision rule. A table is provided to give an estimate of the variance of d , the experimental estimate of d. The power of the dual pair method is also investigated, and a formula to determine the sample size required to meet Type I and Type II error specifications is given. The dual pair method appears to be slightly less powerful than the duo-trio and the triangular methods. Experimental investigation is needed to explore the dual pair in applied research work.

Intensity discrimination of Gaussian-windowed tones: indications for the shape of the auditory frequency-time window

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.

Discrimination of changes in the spectral shape of noise bands

Discrimination experiments were performed for a change in the spectral shape of noise bands. The subject's task was to discriminate noise bands with a positive spectral slope from those with a negative spectral slope. Thresholds were measured at several bandwidths and center frequencies, as well as for several noise samples. Experiments were performed while roving the overall intensity. At a fixed center frequency of 1 kHz, sensitivity was best for bandwidths of 3-6 semitones (ST). At larger bandwidths, thresholds increased only slowly. At a fixed bandwidth of 1 ST, threshold hardly changed as a function of the center frequency. At a fixed bandwidth of 58 Hz, threshold was lowest near 500-1000 Hz. Model calculations show that the EWAIF model [Feth, Percept. Psychophys. 15, 375-378 (1974)] can account for the present results if the signal's bandwidth does not exceed 1 ST. The IWAIF model [Anantharaman et al., J. Acoust. Soc. Am. 94, 723-729 (1993)] can account for the present results only if the signal's bandwidth is smaller than 1 ST but larger than about 25 Hz. Results obtained with broadband signals could be described only qualitatively with the multichannel model [Durlach et al., J. Acoust. Soc. Am. 80, 63-72 (1986)]. Then, the model needs the assumption that either the output of the different frequency bands cannot be optimally combined, or that only two bands are used in the discrimination process. The present results are compared with those obtained with two-tone complexes measured under identical conditions [Versfeld and Houtsma, J. Acoust. Soc. Am. 98, 807-816 (1995)].

The optimum decision rules in the same-different paradigm

In this paper we derive the optimum (likelihood-ratio) decision statistic for a same-different paradigm. The likelihood ratio is dependent on the degree of correlation between the two observations on each trial. For the two extreme cases in which the observations are either independent or highly correlated, the optimum decision rule is identical to each of two previously suggested decision rules. For these two cases, the receiver-operating characteristic (ROC) curves are calculated. Finally, an experimental procedure is suggested for assessing the decision rule actually used by the observer in a same-different task.