Bayesian adaptive estimation of the auditory filter

Toward parametric Bayesian adaptive procedures for multi-frequency categorical loudness scaling

A series of Bayesian adaptive procedures to estimate loudness growth across a wide frequency range from individual listeners was developed, and these procedures were compared. Simulation experiments were conducted based on multinomial psychometric functions for categorical loudness scaling across ten test frequencies estimated from 61 listeners with normal hearing and 87 listeners with sensorineural hearing loss. Adaptive procedures that optimized the stimulus selection based on the interim estimates of two types of category-boundary models were tested. The first type of model was a phenomenological model of category boundaries adopted from previous research studies, while the other type was a data-driven model derived from a previously collected set of categorical loudness scaling data. An adaptive procedure without Bayesian active learning was also implemented. Results showed that all adaptive procedures provided convergent estimates of the loudness category boundaries and equal-loudness contours between 250 and 8000 Hz. Performing post hoc model fitting, using the data-driven model, on the collected data led to satisfactory accuracies, such that all adaptive procedures tested in the current study, independent of modeling approach and stimulus-selection rules, were able to provide estimates of the equal-loudness-level contours between 20 and 100 phons with root-mean-square errors typically under 6 dB after 100 trials.

Test-retest evaluation of a notched-noise test using consumer-grade mobile audio equipment

OBJECTIVE

The aim of this study was to investigate whether consumer-grade mobile audio equipment can be reliably used as a platform for the notched-noise test, including when the test is conducted outside the laboratory.

DESIGN

Two studies were conducted: Study 1 was a notched-noise masking experiment with three different setups: in a psychoacoustic test booth with a standard laboratory PC; in a psychoacoustic test booth with a mobile device; and in a quiet office room with a mobile device. Study 2 employed the same task as Study 1, but compared circumaural headphones to insert earphones.

STUDY SAMPLE

Nine and ten young, normal-hearing participants completed studies 1 and 2, respectively.

RESULTS

The test-retest accuracy of the notched-noise test on the mobile implementation did not differ from that for the laboratory setup. A possible effect of the earphone design was identified in Study 1, which was corroborated by Study 2, where test-retest variability was smallest when comparing results from experiments conducted using identical acoustic transducers.

CONCLUSIONS

Results and test-retest repeatability comparable to standard laboratory settings for the notched-noise test can be obtained with mobile equipment outside the laboratory.

Application of Bayesian Active Learning to the Estimation of Auditory Filter Shapes Using the Notched-Noise Method

Time-efficient hearing tests are important in both clinical practice and research studies. This particularly applies to notched-noise tests, which are rarely done in clinical practice because of the time required. Auditory-filter shapes derived from notched-noise data may be useful for diagnosis of the cause of hearing loss and for fitting of hearing aids, especially if measured over a wide range of center frequencies. To reduce the testing time, we applied Bayesian active learning (BAL) to the notched-noise test, picking the most informative stimulus parameters for each trial based on nine Gaussian Processes. A total of 11 hearing-impaired subjects were tested. In 20 to 30 min, the test provided estimates of signal threshold as a continuous function of frequency from 500 to 4000 Hz for nine notch widths and for notches placed both symmetrically and asymmetrically around the signal frequency. The thresholds were found to be consistent with those obtained using a 2-up/1-down forced-choice procedure at a single center frequency. In particular, differences in threshold between the methods did not vary with notch width. An independent second run of the BAL test for one notch width showed that it is reliable. The data derived from the BAL test were used to estimate auditory-filter width and asymmetry and detection efficiency for center frequencies from 500 to 4000 Hz. The results agreed with expectations for cochlear hearing losses that were derived from the audiogram and a hearing model.

Individualized estimation of the Speech Intelligibility Index for short sentences: Test-retest reliability

The speech intelligibility index (SII) model was modified to allow individualized parameters. These parameters included the relative weights of speech cues in five octave-frequency bands ranging from 0.25 to 4 kHz, i.e., the band importance function, and the transfer function that allows the SII to generate predictions on speech-recognition scores. A Bayesian adaptive procedure, the quick-band-importance-function (qBIF) procedure, was utilized to enable efficient estimation of the SII parameters from individual listeners. In two experiments, the SII parameters were estimated for 30 normal-hearing adults using Institute of Electrical and Electronics Engineers (IEEE) sentences at speech levels of 55, 65, and 75 dB sound pressure level (in Experiment I) and for 15 hearing-impaired (HI) adult listeners using amplified IEEE or AzBio sentences (in Experiment II). In both experiments, even without prior training, the estimated model parameters showed satisfactory reliability between two runs of the qBIF procedure at least one week apart. For the HI listeners, inter-listener variability in most estimated SII parameters was larger than intra-listener variability of the qBIF procedure.

Visual Field Estimation by Probabilistic Classification

The gold standard clinical tool for evaluating visual dysfunction in cases of glaucoma and other disorders of vision remains the visual field or threshold perimetry exam. Administration of this exam has evolved over the years into a sophisticated, standardized, automated algorithm that relies heavily on specifics of disease processes particular to common retinal disorders. The purpose of this study is to evaluate the utility of a novel general estimator applied to visual field testing. A multidimensional psychometric function estimation tool was applied to visual field estimation. This tool is built on semiparametric probabilistic classification rather than multiple logistic regression. It combines the flexibility of nonparametric estimators and the efficiency of parametric estimators. Simulated visual fields were generated from human patients with a variety of diagnoses, and the errors between simulated ground truth and estimated visual fields were quantified. Error rates of the estimates were low, typically within 2 dB units of ground truth on average. The greatest threshold errors appeared to be confined to the portions of the threshold function with the highest spatial frequencies. This method can accurately estimate a variety of visual field profiles with continuous threshold estimates, potentially using a relatively small number of stimuli.

Conjoint psychometric field estimation for bilateral audiometry

Behavioral testing in perceptual or cognitive domains requires querying a subject multiple times in order to quantify his or her ability in the corresponding domain. These queries must be conducted sequentially, and any additional testing domains are also typically tested sequentially, such as with distinct tests comprising a test battery. As a result, existing behavioral tests are often lengthy and do not offer comprehensive evaluation. The use of active machine-learning kernel methods for behavioral assessment provides extremely flexible yet efficient estimation tools to more thoroughly investigate perceptual or cognitive processes without incurring the penalty of excessive testing time. Audiometry represents perhaps the simplest test case to demonstrate the utility of these techniques. In pure-tone audiometry, hearing is assessed in the two-dimensional input space of frequency and intensity, and the test is repeated for both ears. Although an individual's ears are not linked physiologically, they share many features in common that lead to correlations suitable for exploitation in testing. The bilateral audiogram estimates hearing thresholds in both ears simultaneously by conjoining their separate input domains into a single search space, which can be evaluated efficiently with modern machine-learning methods. The result is the introduction of the first conjoint psychometric function estimation procedure, which consistently delivers accurate results in significantly less time than sequential disjoint estimators.

The effect of speech material on the band importance function for Mandarin Chinese

Speech material influences the relative contributions of different frequency regions to intelligibility for English. In the current study, whether a similar effect of speech material is present for Mandarin Chinese was investigated. Speech recognition was measured using three speech materials in Mandarin, including disyllabic words, nonsense sentences, and meaningful sentences. These materials differed from one another in terms of the amount of contextual information and word frequency. The band importance function (BIF), as defined under the Speech Intelligibility Index (SII) framework, was used to quantify the contributions across frequency regions. The BIFs for the three speech materials were estimated from 16 adults who were native speakers of Mandarin. A Bayesian adaptive procedure was used to efficiently estimate the octave-frequency BIFs for the three materials for each listener. As the amount of contextual information increased, low-frequency bands (e.g., 250 and 500 Hz) became more important for speech recognition, consistent with English. The BIF was flatter for Mandarin than for comparable English speech materials. Introducing the language- and material-specific BIFs to the SII model led to improved predictions of Mandarin speech-recognition performance. Results suggested the necessity of developing material-specific BIFs for Mandarin.

Amplitude modulation detection and temporal modulation cutoff frequency in normal hearing infants

The goal of this study was to determine if temporal modulation cutoff frequency was mature in three-month-old infants. Normal-hearing infants and young adults were tested in a single-interval forced-choice observer-based psychoacoustic procedure. Two parameters of the temporal modulation transfer function (TMTF) were estimated to separate temporal resolution from amplitude modulation sensitivity. The modulation detection threshold (MDT) of a broadband noise amplitude modulated at 10 Hz estimated the y-intercept of the TMTF. The cutoff frequency of the TMTF, measured at a modulation depth 4 dB greater than the MDT, provided an estimate of temporal resolution. MDT was obtained in 27 of 33 infants while both MDT and cutoff frequency was obtained in 15 infants and in 16 of 16 adults. Mean MDT was approximately 10 dB poorer in infants compared to adults. In contrast, mean temporal modulation cutoff frequency did not differ significantly between age groups. These results suggest that temporal resolution is mature, on average, by three months of age in normal hearing children despite immature sensitivity to amplitude modulation. The temporal modulation cutoff frequency approach used here may be a feasible way to examine development of temporal resolution in young listeners with markedly immature sensitivity to amplitude modulation.

Bayesian active probabilistic classification for psychometric field estimation

Psychometric functions are typically estimated by fitting a parametric model to categorical subject responses. Procedures to estimate unidimensional psychometric functions (i.e., psychometric curves) have been subjected to the most research, with modern adaptive methods capable of quickly obtaining accurate estimates. These capabilities have been extended to some multidimensional psychometric functions (i.e., psychometric fields) that are easily parameterizable, but flexible procedures for general psychometric field estimation are lacking. This study introduces a nonparametric Bayesian psychometric field estimator operating on subject queries sequentially selected to improve the estimate in some targeted way. This estimator implements probabilistic classification using Gaussian processes trained by active learning. The accuracy and efficiency of two different actively sampled estimators were compared to two non-actively sampled estimators for simulations of one of the simplest psychometric fields in common use: the pure-tone audiogram. The actively sampled methods achieved estimate accuracy equivalent to the non-actively sampled methods with fewer observations. This trend held for a variety of audiogram phenotypes representative of the range of human auditory perception. Gaussian process classification is a general estimation procedure capable of extending to multiple input variables and response classes. Its success with a two-dimensional psychometric field informed by binary subject responses holds great promise for extension to complex perceptual models currently inaccessible to practical estimation.

An Analysis of Individual Differences in Recognizing Monosyllabic Words Under the Speech Intelligibility Index Framework

Individual differences in the recognition of monosyllabic words, either in isolation (NU6 test) or in sentence context (SPIN test), were investigated under the theoretical framework of the speech intelligibility index (SII). An adaptive psychophysical procedure, namely the quick-band-importance-function procedure, was developed to enable the fitting of the SII model to individual listeners. Using this procedure, the band importance function (i.e., the relative weights of speech information across the spectrum) and the link function relating the SII to recognition scores can be simultaneously estimated while requiring only 200 to 300 trials of testing. Octave-frequency band importance functions and link functions were estimated separately for NU6 and SPIN materials from 30 normal-hearing listeners who were naïve to speech recognition experiments. For each type of speech material, considerable individual differences in the spectral weights were observed in some but not all frequency regions. At frequencies where the greatest intersubject variability was found, the spectral weights were correlated between the two speech materials, suggesting that the variability in spectral weights reflected listener-originated factors.

Toward Routine Assessments of Auditory Filter Shape

Purpose A Bayesian adaptive procedure, that is, the quick auditory filter (qAF) procedure, has been shown to improve the efficiency for estimating auditory filter shapes of listeners with normal hearing. The current study evaluates the accuracy and test-retest reliability of the qAF procedure for naïve listeners with a variety of ages and hearing status. Method Fifty listeners who were naïve to psychophysical experiments and exhibit wide ranges of age (19-70 years) and hearing threshold (-5 to 70 dB HL at 2 kHz) were recruited. Their auditory filter shapes were estimated for a 15-dB SL target tone at 2 kHz using both the qAF procedure and the traditional threshold-based procedure. The auditory filter model was defined using 3 parameters: (a) the sharpness of the tip portion of the auditory filter, p; (b) the prominence of the low-frequency tail of the filter, 10log( w); and (c) the listener's efficiency in detection, 10log( K). Results The estimated parameters of the auditory filter model were consistent between 2 qAF runs tested on 2 separate days. The parameter estimates from the 2 qAF runs also agreed well with those estimated using the traditional procedure despite being substantially faster. Across the 3 auditory filter estimates, the dependence of the auditory filter parameters on listener age and hearing threshold was consistent across procedures, as well as consistent with previously published estimates. Conclusions The qAF procedure demonstrates satisfactory test-retest reliability and good agreement to the traditional procedure for listeners with a wide range of ages and with hearing status ranging from normal hearing to moderate hearing impairment.

Efficient assessment of the time course of perceptual sensitivity change

Perceptual sensitivity is usually estimated over trials and time intervals, which results in imprecise and biased estimates when it changes rapidly over time. We develop a novel procedure, the quick Change-Detection (qCD) method, to accurately, precisely, and efficiently assess the trial-by-trial time course of perceptual sensitivity change. Based on Bayesian adaptive testing, qCD selects the optimal stimulus, and updates, trial by trial, a joint probability distribution of the parameters that quantify perceptual sensitivity change over time. We demonstrate the utility of the method in measuring the time course of dark adaptation. Simulations showed that the accuracy and precision of the estimated dark adaptation curve after one qCD run (root mean squared error (RMSE): 0.002; the half width of the 68.2% credible interval (HWCI): 0.016; standard deviation (SD): 0.020; all in log₁₀ units) was higher than those obtained by ten runs of the quick Forced-Choice (qFC) procedure (RMSE: 0.020; HWCI: 0.032; SD: 0.031) and ten runs of a weighted up-down staircase procedure (RMSE: 0.026; SD: 0.031). Further, the dark adaptation curve obtained from one qCD run in a psychophysics experiment was highly consistent with the average of four qFC runs (RMSE = 0.076 log₁₀ units). Overall, qCD provides a procedure to characterize the detailed time course of perceptual sensitivity change in both basic research and clinical applications.

A Hearing-Model-Based Active-Learning Test for the Determination of Dead Regions

This article describes a Bayesian active-learning procedure for estimating the edge frequency, f_e, of a dead region, that is, a region in the cochlea with no or very few functioning inner hair cells or neurons. The method is based on the psychophysical tuning curve (PTC) but estimates the shape of the PTC from the parameters of a hearing model, namely f_e, and degree of outer hair cell loss. It chooses the masker frequency and level for each trial to be highly informative about the model parameters in the context of previous data. The procedure was tested using 14 ears from eight subjects previously diagnosed with high-frequency dead regions. The estimates of f_e agreed well with estimates obtained using “Fast PTCs” or more extensive measurements from an earlier study. On average, 33 trials were needed for the estimate of f_e to fall and stay within 0.3 Cams of the final “true” value on the equivalent rectangular bandwidth-number scale. The time needed to obtain a reliable estimate was 5 to 8 min. This is comparable to the time required for Fast PTCs and short enough to be used when fitting a hearing aid. Compared with Fast PTCs, the new method has the advantage of using yes-no judgments rather than continuous Békésy tracking. This allows the slope of a subject’s psychometric function and thus the reliability of his or her responses to be estimated, which in turn allows the test duration to be adjusted so as to achieve a given accuracy.

Audiogram estimation using Bayesian active learning

Two methods for estimating audiograms quickly and accurately using Bayesian active learning were developed and evaluated. Both methods provided an estimate of threshold as a continuous function of frequency. For one method, six successive tones with decreasing levels were presented on each trial and the task was to count the number of tones heard. A Gaussian Process was used for classification and maximum-information sampling to determine the frequency and levels of the stimuli for the next trial. The other method was based on a published method using a Yes/No task but extended to account for lapses. The obtained audiograms were compared to conventional audiograms for 40 ears, 19 of which were hearing impaired. The threshold estimates for the active-learning methods were systematically from 2 to 4 dB below (better than) those for the conventional audiograms, which may indicate a less conservative response criterion (a greater willingness to respond for a given amount of sensory information). Both active-learning methods were able to allow for wrong button presses (due to lapses of attention) and provided accurate audiogram estimates in less than 50 trials or 4 min. For a given level of accuracy, the counting task was slightly quicker than the Yes/No task.

Fast, Continuous Audiogram Estimation Using Machine Learning

OBJECTIVES

Pure-tone audiometry has been a staple of hearing assessments for decades. Many different procedures have been proposed for measuring thresholds with pure tones by systematically manipulating intensity one frequency at a time until a discrete threshold function is determined. The authors have developed a novel nonparametric approach for estimating a continuous threshold audiogram using Bayesian estimation and machine learning classification. The objective of this study was to assess the accuracy and reliability of this new method relative to a commonly used threshold measurement technique.

DESIGN

The authors performed air conduction pure-tone audiometry on 21 participants between the ages of 18 and 90 years with varying degrees of hearing ability. Two repetitions of automated machine learning audiogram estimation and one repetition of conventional modified Hughson-Westlake ascending-descending audiogram estimation were acquired by an audiologist. The estimated hearing thresholds of these two techniques were compared at standard audiogram frequencies (i.e., 0.25, 0.5, 1, 2, 4, 8 kHz).

RESULTS

The two threshold estimate methods delivered very similar estimates at standard audiogram frequencies. Specifically, the mean absolute difference between estimates was 4.16 ± 3.76 dB HL. The mean absolute difference between repeated measurements of the new machine learning procedure was 4.51 ± 4.45 dB HL. These values compare favorably with those of other threshold audiogram estimation procedures. Furthermore, the machine learning method generated threshold estimates from significantly fewer samples than the modified Hughson-Westlake procedure while returning a continuous threshold estimate as a function of frequency.

CONCLUSIONS

The new machine learning audiogram estimation technique produces continuous threshold audiogram estimates accurately, reliably, and efficiently, making it a strong candidate for widespread application in clinical and research audiometry.

Culture and properties of adipose-derived mesenchymal stem cells: characteristics in vitro and immunosuppression in vivo

OBJECTIVE

To compare the two sources of adipose and bone marrow derived mesenchymal stem cells (BMSCs and AMSCs) in immune regulation and to evaluate the therapeutic effects of AMSCs on Con A induced hepatitis and the possible mechanism involved in it.

METHODS

We isolated bone marrow and adipose derived mesenchymal stem cells respectively and compared their differences on T lymphocyte activation, proliferation and suppression. We also test the anti-apoptosis ability of AMSCs on LO2 cell line. The effects of intravenous infusion of AMSCs on liver damage were also tested and we detected donor AMSCs in liver of recipient and their effects on the activity of intrahepatic NKT cells.

RESULTS

BMSCs and AMSCs were similar in cell phenotype and the difference existed only in the expression of CD106. The results showed that the capacity of suppressing T cells proliferation and activation was weakened in AMSCs. AMSCs ameliorated liver damage and this effect was time and dose dependent. We detected donor AMSCs in liver of recipient which suggested tissue damage could be a clue for AMSCs migration. We also found AMSCs suppress the activity of intrahepatic NKT cells, but this suppress effects was not restricted in liver only, but the whole body.

CONCLUSION

Cell origin and abundance are decisive factors in stem cells applications and with the same premise of AMSCs and BMSCs, adipose tissue is a more promising origin source of stem cells. The immunoregulatory features of MSCs might play an important role in various MSCs cellular therapies.

Rapid estimation of high-parameter auditory-filter shapes

A Bayesian adaptive procedure, the quick-auditory-filter (qAF) procedure, was used to estimate auditory-filter shapes that were asymmetric about their peaks. In three experiments, listeners who were naive to psychoacoustic experiments detected a fixed-level, pure-tone target presented with a spectrally notched noise masker. The qAF procedure adaptively manipulated the masker spectrum level and the position of the masker notch, which was optimized for the efficient estimation of the five parameters of an auditory-filter model. Experiment I demonstrated that the qAF procedure provided a convergent estimate of the auditory-filter shape at 2 kHz within 150 to 200 trials (approximately 15 min to complete) and, for a majority of listeners, excellent test-retest reliability. In experiment II, asymmetric auditory filters were estimated for target frequencies of 1 and 4 kHz and target levels of 30 and 50 dB sound pressure level. The estimated filter shapes were generally consistent with published norms, especially at the low target level. It is known that the auditory-filter estimates are narrower for forward masking than simultaneous masking due to peripheral suppression, a result replicated in experiment III using fewer than 200 qAF trials.