Musicians have an advantage on a spatial-hearing task only when they are highly trained, start training early, and continue to play.

Musicians perform better than non-musicians on a variety of non-musical sound-perception tasks. Whether that musicians' advantage extends to spatial hearing is a topic of increasing interest. Here we investigated one facet of that topic by assessing musicians' and non-musicians' sensitivity to the two primary cues to sound-source location on the horizontal plane: interaural-level-differences (ILDs) and interaural-time-differences (ITDs). Specifically, we measured discrimination thresholds for ILDs at 4 kHz (n =246) and ITDs at 0.5 kHz (n = 137) in participants whose musical-training histories covered a wide range of lengths, onsets, and offsets. For ILD discrimination, when only musical-training length was considered in the analysis, no musicians' advantage was apparent. However, when thresholds were compared between subgroups of non-musicians (<2 years of training) and extreme musicians (≥10 years of training, started ≤ age 7, still playing) a musicians' advantage emerged. Threshold comparisons between the extreme musicians and other subgroups of highly trained musicians (≥10 years of training) further indicated that the advantage required both starting young and continuing to play. In addition, the advantage was larger in males than in females, by some measures, and was not evident in an assessment of learning. For ITD discrimination, in contrast to ILD discrimination, parallel analyses revealed no apparent musicians' advantage. The results suggest that musicianship is associated with greater sensitivity to ILDs, a fundamental sound-localization cue, even though that sensitivity is not central to music, that this musicians' advantage arises, at least in part, from nurture, and that it is governed by a neural substrate where ILDs are processed separately from, and more malleably than, ITDs.

Steep temporal integration for tone detection in a multi-tone, random-frequency masker.

In the detection of a tone burst, masking by several tones with random frequencies can produce steep temporal integration. This feature was evaluated for nine normal-hearing adults for 1000-Hz tone bursts presented in a continuous train of four-tone masker bursts. Masker frequencies were randomly selected (250-4000 Hz) for each burst, with the proviso that all tones were separated by ≥0.2 oct. Bursts were 80-ms in duration; when present, signal bursts were gated synchronously with masker bursts. The observed mean temporal-integration function was exceptionally steep-thresholds improved by 26 dB as signal duration increased from 1 to 8 bursts. The results also showed that the individual differences were large, and that the mean psychometric function was exceptionally shallow, spanning a range of 35 dB between 0.6 and 0.9 proportion correct responses, consistent with previous reports. These findings were interpreted in the context of three signal-detection models, one based on the absolute-level cue, and two based on the relative-level cue via template matching; all cues were derived from the excitation patterns of the stimuli. Template-matching models were able to predict the shallow psychometric functions as observed, but all models fall short in the steepness of the observed temporal integration.

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.

Discrimination thresholds for interaural-time differences and interaural-level differences in naïve listeners: Sex differences and learning.

The two primary cues to sound-source location on the horizontal plane are interaural time differences (ITDs) and interaural level differences (ILDs). Here we asked whether the ability to discriminate small changes in each of these interaural cues differs between the sexes. We tested one group of males (n = 43) and females (n = 94) on ITD discrimination at 0.5 kHz and a separate group of males (n = 80) and females (n = 166) on ILD discrimination at 4 kHz. None of the participants had any prior experience with psychoacoustic tasks. Testing of each participant was completed in a single testing session of 4-5 blocks of 60 trials. For ILD discrimination, the overall mean threshold, as well as the mean threshold for each block, was statistically significantly lower for males than for females. Despite that, males and females learned at an equal rate over the course of testing. For ITD discrimination, in contrast, thresholds did not differ significantly between the sexes for the overall mean or for any block. There also was no statistically significant learning across blocks for either sex. For both tasks and both sexes, the individual thresholds spanned a wide range. The presence of a statistically significant sex difference and learning for ILD but not for ITD discrimination, along with a larger effect size for ILD than for ITD discrimination, suggests that the factors responsible for these outcomes acted upon an ILD-specific neural pathway, and not upon an ITD-specific pathway, nor any pathway common to the two cues. Because the ILD and ITD specific pathways are most separable initially, the factors associated with sex and learning may have acted upon the ILD-specific pathway at an early stage.

Humans attend to signal duration but not temporal structure for sound detection: Steady-state versus pulse-train signals.

Most sounds fluctuate in amplitude, but do listeners attend to the temporal structure of those fluctuations when trying to detect the mere presence of those sounds? This question was addressed by leading listeners to expect a faint sound with a fixed temporal structure (pulse train or steady-state tone) and total duration (300 ms) and measuring their ability to detect equally faint sounds of unexpected temporal structure (pulse train when expecting steady state) and/or total duration (<300 ms). Detection was poorer for sounds with unexpected than with expected total durations, replicating previous outcomes, but was uninfluenced by the temporal structure of the expected sound. The results disagree with computational predictions of the multiple-look model, which posits that listeners attend to both the total duration and temporal structure of the signal, but agree with predictions of the matched-window energy-detector model, which posits that listeners attend to the total duration but not the temporal structure of the signal. Moreover, the matched-window energy-detector model could also account for previous results, including some that were originally interpreted as supporting the multiple-look model. Taken together, at least when detecting faint sounds, listeners appear to attend to the total duration of expected sounds but to ignore their detailed temporal structure.

Neural Correlates of Morphology Acquisition through a Statistical Learning Paradigm.

The neural basis of statistical learning as it occurs over time was explored with stimuli drawn from a natural language (Russian nouns). The input reflected the "rules" for marking categories of gendered nouns, without making participants explicitly aware of the nature of what they were to learn. Participants were scanned while listening to a series of gender-marked nouns during four sequential scans, and were tested for their learning immediately after each scan. Although participants were not told the nature of the learning task, they exhibited learning after their initial exposure to the stimuli. Independent component analysis of the brain data revealed five task-related sub-networks. Unlike prior statistical learning studies of word segmentation, this morphological learning task robustly activated the inferior frontal gyrus during the learning period. This region was represented in multiple independent components, suggesting it functions as a network hub for this type of learning. Moreover, the results suggest that subnetworks activated by statistical learning are driven by the nature of the input, rather than reflecting a general statistical learning system.

On averaging multiple estimates of decision weights within or across listeners.

As a practical guide, a formula is provided for averaging multiple estimates of decision weights, for the purpose of improving the accuracy and reliability of the final estimate of decision weights. The averaging over multiple weight estimates can take place either within or across listeners.

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.

Optimal integration of independent observations from Poisson sources.

The optimal integration of information from independent Poisson sources (such as neurons) was analyzed in the context of a two-interval, forced-choice detection task. When the mean count of the Poisson distribution is above 1, the benefit of integration is closely approximated by the predictions based on the square-root law of the Gaussian model. When the mean count falls far below 1, however, the benefit of integration clearly exceeds the predictions based on the square-root law.

Effect of stimulus bandwidth and duration on monaural envelope correlation perception.

Monaural envelope correlation perception is the ability to discriminate between stimuli composed of two or more bands of noise based on envelope correlation. Sensitivity decreases as stimulus bandwidth is reduced below 100 Hz. The present study manipulated stimulus bandwidth (25-100 Hz) and duration (25-800 ms) to evaluate whether performance of highly trained listeners is limited by the number of inherent modulation periods in each presentation. Stimuli were two bands of noise, separated by a 500-Hz gap centered on 2250 Hz. Performance improved reliably with increasing numbers of envelope modulation periods, although there were substantial individual differences.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Separating the contributions of primary and unwanted cues in psychophysical studies.

A fundamental issue in the design and the interpretation of experimental studies of perception relates to the question of whether the participants in these experiments could perform the perceptual task assigned to them using another feature, or cue, than that intended by the experimenter. An approach frequently used by auditory- and visual-perception researchers to guard against this possibility involves applying random variations to the stimuli across presentations or trials so as to make the "unwanted" cue unreliable for the participants. However, the theoretical basis of this widespread practice is not well developed. In this article, we describe a 2-channel model based on general principles of psychophysical signal detection theory, which can be used to assess the respective contributions of the unwanted cue and of the primary cue to performance or thresholds measured in perceptual discrimination experiments involving stimulus randomization. Example applications of the model to the analysis of results obtained in representative studies from the auditory- and visual-perception literature are provided. In several cases, the results of the model-based analyses indicate that the effectiveness of the randomization procedure was less than originally assumed by the authors of these studies. These findings underscore the importance of quantifying the potential influence of unwanted cues on the results of psychophysical experiments, even when stimulus randomization is used.

Psychometric functions for pure-tone frequency discrimination.

The form of the psychometric function (PF) for auditory frequency discrimination is of theoretical interest and practical importance. In this study, PFs for pure-tone frequency discrimination were measured for several standard frequencies (200-8000 Hz) and levels [35-85 dB sound pressure level (SPL)] in normal-hearing listeners. The proportion-correct data were fitted using a cumulative-Gaussian function of the sensitivity index, d', computed as a power transformation of the frequency difference, Δf. The exponent of the power function corresponded to the slope of the PF on log(d')-log(Δf) coordinates. The influence of attentional lapses on PF-slope estimates was investigated. When attentional lapses were not taken into account, the estimated PF slopes on log(d')-log(Δf) coordinates were found to be significantly lower than 1, suggesting a nonlinear relationship between d' and Δf. However, when lapse rate was included as a free parameter in the fits, PF slopes were found not to differ significantly from 1, consistent with a linear relationship between d' and Δf. This was the case across the wide ranges of frequencies and levels tested in this study. Therefore, spectral and temporal models of frequency discrimination must account for a linear relationship between d' and Δf across a wide range of frequencies and levels.

On the theoretical error bound for estimating psychometric functions.

The theoretical limits to the amount of error, or the Cramer-Rao bounds, were derived for estimating psychometric functions. These theoretical error bounds were compared with the variability of psychometric functions estimated from human as well as computer-simulated observers. For the simulated observers, due to the limited efficiency of the sampling strategies, including the placement of the signals and the distribution of the trials, the variances of the estimated parameters are seven times the theoretical bound for threshold and 22 times that for slope. For the human observers, the variance is 18 times the theoretical bounds for threshold and 80 times that for slope. Therefore, a major portion of the variances (60% for threshold and 73% for slope) for the human observers is associated with factors other than sampling strategies. Further improvement of the accuracy for estimating psychometric functions will depend on not only optimizing the sampling strategy, but also better understanding the various sources of error related to the behavior of human observers.

Harmonic pitch: dependence on resolved partials, spectral edges, and combination tones.

Perceptual weights were estimated in a pitch-comparison experiment to assess the relative influences of individual partial tones on listeners' pitch judgments. The stimuli were harmonic sounds (F0=200 Hz) with partials up to the 12th. Low-numbered partials were removed step-by-step, so that the remaining higher-numbered partials would have a better chance of showing any effect. The individual frequencies of the partials were perturbed randomly on each stimulus presentation, and weights were estimated as the correlation coefficients between the frequency perturbations and the listeners' responses. When the harmonic sounds contained all twelve partials, the listeners depended mostly on the low-numbered, resolved partials within the well-established dominance region. As the low-numbered partials were taken out of the dominance region, the listeners mostly listened to the lowest and highest partials at the spectral edges. For one listener, such an edge-listening strategy took the form of relying on nonlinear combination tones. Overall, there was no indication of any influence on pitch from unresolved partials, thus no evidence of contribution to pitch from temporal cues carried by this group of partials. The estimated patterns of weights were well described by the predictions of Goldstein's optimal-processor model. The predicted weights were inversely proportional to the amount of error for estimating the individual frequencies of the partials. The agreement between the predicted and measured weights suggests that, for harmonic sounds, partials whose frequencies are perceived with the best precision will likely have the greatest influence on perceived pitch.

Psychophysical reverse correlation with multiple response alternatives.

Psychophysical reverse-correlation methods such as the "classification image" technique provide a unique tool to uncover the internal representations and decision strategies of individual participants in perceptual tasks. Over the past 30 years, these techniques have gained increasing popularity among both visual and auditory psychophysicists. However, thus far, principled applications of the psychophysical reverse-correlation approach have been almost exclusively limited to two-alternative decision (detection or discrimination) tasks. Whether and how reverse-correlation methods can be applied to uncover perceptual templates and decision strategies in situations involving more than just two response alternatives remain largely unclear. Here, the authors consider the problem of estimating perceptual templates and decision strategies in stimulus identification tasks with multiple response alternatives. They describe a modified correlational approach, which can be used to solve this problem. The approach is evaluated under a variety of simulated conditions, including different ratios of internal-to-external noise, different degrees of correlations between the sensory observations, and various statistical distributions of stimulus perturbations. The results indicate that the proposed approach is reasonably robust, suggesting that it could be used in future empirical studies.

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.

Limiting unwanted cues via random rove applied to the yes-no and multiple-alternative forced choice paradigms.

When a random rove is used in a perceptual task to control the influence of an unwanted cue that may confound the decision strategy of primary interest, the effectiveness of the rove is determined by its range. Green [Profile Analysis (Oxford University Press, Oxford, 1988)] provided a formula which allows experimenters to determine the roving range required to ensure that the listeners relying on the unwanted cue cannot exceed a pre-defined percentage of correct responses in a two-interval, two-alternative forced-choice experiment. Here, Green's analysis is extended to the yes-no and m-alternative, forced-choice paradigms (m>2).

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.

On suppressing unwanted cues via randomization.

In certain perceptual discrimination tasks, a change in a particular stimulus variable can be perceived as changes along multiple perceptual dimensions. If the study is primarily concerned with a particular perceptual dimension or cue, it is important that the experimenter keep the influences of the other unwanted but correlated perceptual cues under control. One way to accomplish this objective is to randomize the stimuli along the stimulus dimensions primarily associated with these unwanted cues, making them unreliable as a basis for the discrimination. This theoretical note presents a mathematical proof that a uniform randomization is the most effective way of suppressing unwanted cues.