Four triggering factors in loudness adaptation.

A factor analysis was used to determine whether induced loudness adaptation (Botte, Canevet, & Scharf, 1982; Scharf, 1983) and adaptation measured by Hood's (1950) classic Simultaneous Dichotic Loudness Balance technique (SDLB) would cluster on the same factors. The two phenomena did not cluster on the same factors; thus, induced adaptation cannot replace SDLB adaptation. Four independent factors that trigger auditory adaptation were identified in the factor analysis.     

Ipsilateral loudness adaptation over multiple intensity levels

Could monaural loudness adaptation be a simple artifact of psychophysical contrast? From adaptation data based on the Ipsilateral Comparison Paradigm (ICP), A. J. Dange, J. S. Warm, E. M. Weiler, and W. N. Dember (1993) concluded that loudness adaptation was not an artifact of psychophysical contrast, but their conclusion was dependent on results from one intensity. This study, involving multiple intensities, re-examined the issue of contrast versus adaptation and generally supported the conclusions of Dange et al. The results also showed an unexpected asymmetry of adaptation based on the direction of the referent modulation used with the ICP technique. Some implications are discussed.     

Monaural loudness adaptation for middle-intensity middle-frequency signals: the importance of measurement technique

Using the Simple Adaptation technique (SA) and the Ipsilateral Comparison Paradigm (ICP), the authors studied monaural loudness adaptation to a middle-intensity [60 dB(A)] tone at signal frequencies of 250, 1000, and 4000 Hz in the left and right ears. Adaptation effects were absent when the SA procedure was used. However, they were observed uniformly across all frequency values with the ICP, a result that challenges the assertion in the literature, on the basis of SA measures, that loudness adaptation for middle-intensity signals occurs only at frequencies above 4000 Hz. The ICP features periodic intensity modulations (+/-10 dB relative to the base signal) to accommodate listeners' needs for referents by which they can gauge subtle changes in the loudness of the adapting tone, a key component that is missing in the SA method. Adaptation effects in this investigation were similar in both ears, supporting the equal susceptibility assumption common in loudness adaptation studies.     

Prism adaptation to dynamic events

In the present study, we explored adaptation to prism-displaced dynamic and static events under conditions of minimal information. Many of our interactions with the world are dynamic and involve reaching for or intercepting moving objects. The consequences (or feedback) of those interactions entail the presence or absence of physical contact with the moving objects. In this study, humans learned, with only heptic feedback, to intercept optically displaced falling balls. To eliminate visual feedback, the falling balls disappeared behind an occluder (which systematically varied in size across groups) prior to either striking or missing a subject's hand. As occluder size decreased, adaptation increased. With minimum occluder sizes, the greatest adaptation occurred around the training position, and adaptation decreased as distance between training and testing positions increased. The results can best be described in terms of a generalization gradient centered around the training position. This generalization gradient was not present when subjects were trained with ecologically similar static arrays. Implications for models of adaptation are discussed.     

Effects of expectations on loudness and loudness difference

To determine how expectations affect loudness and loudness difference, in two experiments we induced some subjects to expect loud sounds (condition L), some to expect soft sounds (condition S), and others to have no particular expectations (control). In Experiment 1, all subjects estimated the loudnesses of the same set of three moderately loud 1-kHz tones. Estimates were greatest for subjects in condition S and smallest for subjects in condition L. Control subjects’ estimates were intermediate but closer to those of condition S subjects. In Experiment 2, subjects estimated the difference in loudness for pairs of moderately loud 1-kHz tones. Again, estimates were smallest for condition L subjects; estimates were greatest for control subjects, and condition S subjects’ estimates were closer to control estimates than to condition L estimates. This pattern of results is explainable by a combination of (1) Parducci’s (1995) range-frequency theory and (2) a gain control mechanism in the auditory system under top-down governance (Schneider, Parker, & Murphy, 2011).     

Magnitude judgments of loudness change for discrete, dynamic, and hybrid stimuli

Recent investigations of loudness change within stimuli have identified differences as a function of direction of change and power range (e.g., Canévet, Acustica, 62, 2136–2142, 1986; Neuhoff, Nature, 395, 123–124, 1998), with claims of differences between dynamic and static stimuli. Experiment 1 provides the needed direct empirical evaluation of loudness change across static, dynamic, and hybrid stimuli. Consistent with recent findings for dynamic stimuli, quantitative and qualitative differences in pattern of loudness change were found as a function of power change direction. With identical patterns of loudness change, only quantitative differences were found across stimulus type. In Experiment 2, Points of Subjective loudness Equality (PSE) provided additional information about loudness judgments for the static and dynamic stimuli. Because the quantitative differences across stimulus type exceed the magnitude that could be expected based upon temporal integration by the auditory system, other factors need to be, and are, considered.     

Bisection of loudness

In a loudness bisection task, subjects varied one sound to lie halfway between two given sounds in terms of loudness. The two given sounds were varied from 30 to 90 dB in a 4 by 9 factorial design. Functional measurement methods based on monotone analysis provided good support for the bisection model, and yielded a loudness scale with an exponent of about .3, except for a falloff at lower intensities. Two other tasks, judging average loudness and difference in loudness of the two given sounds, yielded mixed results. In Experiment 2, in particular, the differencing judgments were not additive, even under monotone transformation. These analyses also indicated that previous applications of monotone analysis have typically lacked adequate power to allow any conclusion about the operative model. Overall, the present bisection scale agrees with Garner’s lambda scale, and the present theoretical approach agrees with that of Garner in its emphasis on algebraic models as a foundation for psychological measurement.     

Individual differences in loudness processing and loudness scales

Parameters of the psychophysical function for loudness (a 1000-Hz tone) were assessed for individual subjects in three experiments: (a) binaural loudness summation, (b) temporal loudness summation, and (c) judgments of loudness intervals. The loudness scales that underlay the additive binaural summation closely approximated S. S. Stevens's (1956) sone scale but were nonlinearly related to the scales that underlay the subtractive interval judgments, the latter approximating Garner's (1954) lambda scale. Interindividual differences in temporal summation were unrelated to differences in scaling performance or in binaural summation. Although the exponents of magnitude-estimation functions and the exponents underlying interval judgments varied considerably from subject to subject, exponents computed on the basis of underlying binaural summation varied less. The results suggest that interindividual variation in the exponent of magnitude-estimation functions largely reflects differences in the ways that subjects use numbers to describe loudnesses and that the sensory representations of loudness are fairly uniform, though probably not wholly uniform, among people with normal hearing. The magnitude of individual variation in at least one measure of auditory intensity processing, namely, temporal summation, seems at least as great as the magnitude of the variation in the underlying loudness scale.     

A linear relation between loudness and decibels

A total of 37 uninitiated observers made repeated numerical magnitude judgments of the loudness of a sequence of octave band noises spaced at 1-dB intervals, from 0 to 5 dB above a standard of about 80 dB(A), which was called 10. The observers were not instructed to use numbers as ratios. When the median responses are plotted linearly against decibels, they are fitted by straight lines. Each extra decibel adds an average of 1 unit of loudness, range for individual observers 10 through .25 units. This is consistent with the view that the subjectively equal stimulus spacing for the loudness of noise is linear in decibels, and that the observers use numbers linearly in judging the loudness.     

A dynamic context model of interactive behavior

A dynamic context model of interactive behavior was developed to explain results from two experiments that tested the effects of interaction costs on encoding strategies, cognitive representations, and response selection processes in a decision-making and a judgment task. The model assumes that the dynamic context defined by the mixes of internal and external representations and processes are sensitive to the interaction cost imposed by the task environment. The model predicts that changes in the dynamic context may lead to systematic biases in cognitive representations and processes that eventually influence decision-making and judgment outcomes. Consistent with the predictions by the model, results from the experiments showed that as interaction costs increased, encoding strategies and cognitive representations shifted from perception-based to memory-based. Memory-based comparisons of the stimuli enhanced the similarity and dominance effects, and led to stronger systematic biases in response outcomes in a choice task. However, in a judgment task, memory-based representations enhanced only the dominance effects. Results suggested that systematic response biases in the dominance context were caused by biases in the cognitive representations of the stimuli, but response biases in the similarity context were caused by biases in the comparison process induced by the choice task. Results suggest that changes in interaction costs not only change whether information was assessed from the external world or from memory but also introduce systematic biases in the cognitive representation of the information, which act as biased inputs to the subsequent decision-making and judgment processes. Results are consistent with the idea of interactive cognition, which proposes that representations and processes are contingent on the dynamic context defined by the information flow between the external task environment and internal cognition.     

A dynamic generalization of the Rasch model

In the present paper a model for describing dynamic processes is constructed by combining the common Rasch model with the concept of structurally incomplete designs. This is accomplished by mapping each item on a collection of virtual items, one of which is assumed to be presented to the respondent dependent on the preceding responses and/or the feedback obtained. It is shown that, in the case of subject control, no unique conditional maximum likelihood (CML) estimates exist, whereas marginal maximum likelihood (MML) proves a suitable estimation procedure. A hierarchical family of dynamic models is presented, and it is shown how to test special cases against more general ones. Furthermore, it is shown that the model presented is a generalization of a class of mathematical learning models, known as Luce's beta-model.     

A dynamic stimulus-driven model of signal detection

Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations--usually Gaussian distributions--even when the observer has no experience with the task. Furthermore, the classic signal detection model requires the observer to place a response criterion along the axis of stimulus strength, and without theoretical elaboration, this criterion is fixed and independent of the observer's experience. We present a dynamic, adaptive model that addresses these 2 long-standing issues. Our model describes how the stimulus representation can develop from a rough subjective prior and thereby explains changes in signal detection performance over time. The model structure also provides a basis for the signal detection decision that does not require the placement of a criterion along the axis of stimulus strength. We present simulations of the model to examine its behavior and several experiments that provide data to test the model. We also fit the model to recognition memory data and discuss the role that feedback plays in establishing stimulus representations.     

Individual loudness functions determined from direct comparisons of loudness intervals

Five subjects were required in each trial to directly compare two pairs of tones and indicate which pair of tones had the greater loudness difference. Ten 1,200-Hz tones differing only in intensity were employed. Subjects made binary comparisons among the 45 tone pairs that can be formed from these 10 tones. The loudness difference comparisons of each subject were found to satisfy two properties (transitivity and monotonicity) that are required for an interval scale representation of loudness. Therefore, individual loudness scales were constructed using a nonmetric scaling technique designed for comparisons of sensory intervals. These loudness scales differed significantly from subject to subject. Since a nonnumerical scaling procedure was employed, these individual differences could not be attributed to biases in the way in which observers use numbers or numerical concepts to describe the loudness of tones. Hence, they suggest strong individual differences in the coding of sound intensity.     

Influence of duty cycle and off time of comparison-tone pulse trains on the measurement of perstimulatory loudness adaptation

An experiment was conducted to determine if duty cycle and off time of tone pulses presented to the comparison ear influence adaptation measured at the opposite (test) ear. Eight subjects were adapted for 5 min to a 1-kHz pure tone at 60 dB SPL. Using a tracking procedure, adaptation was measured under five comparison-signal conditions, each comprised of 1-kHz pulse trains having different on/off times. The on/off times (in milliseconds) were: 200/800 (20% duty cycle); 500/500, 200/200, and 800/800 (50% duty cycle); and 800/200 (80% duty cycle). Adaptation was found to increase as the duty cycle of the comparison tones increased from 20% to 80%. This was evident even when attempts were made to account for the extent to which pulse trains are perceived as softer than continuous signals at the same level (the so-called LOT effect). For the 50%-duty-cycle conditions, similar amounts of adaptation were measured whether the on/off times of the signals were 200, 500, or 800 msec.     

Vibrotactile loudness addition

Os adjusted the intensity of vibration at a single locus on the right hand to a value equal in vibratory loudness to various patterns of vibration on the left hand. The patterns were created by 1 to 5 equated vibration generators, varied with respect to sensation level and distances among the vibrators. The results were: (a) increasing from 1 to 5 vibrators produced a doubling in vibratory loudness, (b) neither loudness level of the components nor distance among vibrators had any effect on the slope of the overall loudness growth function. as also adjusted the intensity of a white noise to equal in magnitude the patterns of vibration presented (a) to the left hand as before and (b) to loci distributed over the surface of the body. The results were the same as those obtained using a single vibrator as standard. The specific loci stimulated did not appear to have any effect on vibrotactile loudness addition.     

Vibrotactile loudness addition

Os adjusted the intensity of vibration at a single locus on the right hand to a value equal in vibratory loudness to various patterns of vibration on the left hand. The patterns were created by 1 to 5 equated vibration generators, varied with respect to sensation level and distances among the vibrators. The results were: (a) increasing from 1 to 5 vibrators produced a doubling in vibratory loudness, (b) neither loudness level of the components nor distance among vibrators had any effect on the slope of the overall loudness growth function. Os also adjusted the intensity of a white noise to equal in magnitude the patterns of vibration presented (a) to the left hand as before and(b) to loci distributed over the surface of the body. The results were the same as those obtained using a single vibrator as standard. The specific loci stimulated did not appear to have any effect on vibrotactile loudness addition.