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      Stream Segregation in the Perception of Sinusoidally Amplitude-Modulated Tones

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          Abstract

          Amplitude modulation can serve as a cue for segregating streams of sounds from different sources. Here we evaluate stream segregation in humans using ABA- sequences of sinusoidally amplitude modulated (SAM) tones. A and B represent SAM tones with the same carrier frequency (1000, 4000 Hz) and modulation depth (30, 100%). The modulation frequency of the A signals ( f modA ) was 30, 100 or 300 Hz, respectively. The modulation frequency of the B signals was up to four octaves higher (Δ f mod ). Three different ABA- tone patterns varying in tone duration and stimulus onset asynchrony were presented to evaluate the effect of forward suppression. Subjects indicated their 1- or 2-stream percept on a touch screen at the end of each ABA- sequence (presentation time 5 or 15 s). Tone pattern, f modA , Δ f mod , carrier frequency, modulation depth and presentation time significantly affected the percentage of a 2-stream percept. The human psychophysical results are compared to responses of avian forebrain neurons evoked by different ABA- SAM tone conditions [1] that were broadly overlapping those of the present study. The neurons also showed significant effects of tone pattern and Δ f mod that were comparable to effects observed in the present psychophysical study. Depending on the carrier frequency, modulation frequency, modulation depth and the width of the auditory filters, SAM tones may provide mainly temporal cues (sidebands fall within the range of the filter), spectral cues (sidebands fall outside the range of the filter) or possibly both. A computational model based on excitation pattern differences was used to predict the 50% threshold of 2-stream responses. In conditions for which the model predicts a considerably larger 50% threshold of 2-stream responses (i.e., larger Δ f mod at threshold) than was observed, it is unlikely that spectral cues can provide an explanation of stream segregation by SAM.

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          Most cited references29

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          Derivation of auditory filter shapes from notched-noise data.

          A well established method for estimating the shape of the auditory filter is based on the measurement of the threshold of a sinusoidal signal in a notched-noise masker, as a function of notch width. To measure the asymmetry of the filter, the notch has to be placed both symmetrically and asymmetrically about the signal frequency. In previous work several simplifying assumptions and approximations were made in deriving auditory filter shapes from the data. In this paper we describe modifications to the fitting procedure which allow more accurate derivations. These include: 1) taking into account changes in filter bandwidth with centre frequency when allowing for the effects of off-frequency listening; 2) correcting for the non-flat frequency response of the earphone; 3) correcting for the transmission characteristics of the outer and middle ear; 4) limiting the amount by which the centre frequency of the filter can shift in order to maximise the signal-to-masker ratio. In many cases, these modifications result in only small changes to the derived filter shape. However, at very high and very low centre frequencies and for hearing-impaired subjects the differences can be substantial. It is also shown that filter shapes derived from data where the notch is always placed symmetrically about the signal frequency can be seriously in error when the underlying filter is markedly asymmetric. New formulae are suggested describing the variation of the auditory filter with frequency and level. The implication of the results for the calculation of excitation patterns are discussed and a modified procedure is proposed. The appendix list FORTRAN computer programs for deriving auditory filter shapes from notched-noise data and for calculating excitation patterns. The first program can readily be modified so as to derive auditory filter shapes from data obtained with other types of maskers, such as rippled noise.
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            Suggested formulae for calculating auditory-filter bandwidths and excitation patterns.

            Recent estimates of auditory-filter shape are used to derive a simple formula relating the equivalent rectangular bandwidth (ERB) of the auditory filter to center frequency. The value of the auditory-filter bandwidth continues to decrease as center frequency decreases below 500 Hz. A formula is also given relating ERB-rate to frequency. Finally, a method is described for calculating excitation patterns from filter shapes.
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              Modeling auditory processing of amplitude modulation. I. Detection and masking with narrow-band carriers.

              This paper presents a quantitative model for describing data from modulation-detection and modulation-masking experiments, which extends the model of the "effective" signal processing of the auditory system described in Dau et al. [J. Acoust. Soc. Am. 99, 3615-3622 (1996)]. The new element in the present model is a modulation filterbank, which exhibits two domains with different scaling. In the range 0-10 Hz, the modulation filters have a constant bandwidth of 5 Hz. Between 10 Hz and 1000 Hz a logarithmic scaling with a constant Q value of 2 was assumed. To preclude spectral effects in temporal processing, measurements and corresponding simulations were performed with stochastic narrow-band noise carriers at a high center frequency (5 kHz). For conditions in which the modulation rate (fmod) was smaller than half the bandwidth of the carrier (delta f), the model accounts for the low-pass characteristic in the threshold functions [e.g., Viemeister, J. Acoust. Soc. Am. 66, 1364-1380 (1979)]. In conditions with fmod > delta f/2, the model can account for the high-pass characteristic in the threshold function. In a further experiment, a classical masking paradigm for investigating frequency selectivity was adopted and translated to the modulation-frequency domain. Masked thresholds for sinusoidal test modulation in the presence of a competing modulation masker were measured and simulated as a function of the test modulation rate. In all cases, the model describes the experimental data to within a few dB. It is proposed that the typical low-pass characteristic of the temporal modulation transfer function observed with wide-band noise carriers is not due to "sluggishness" in the auditory system, but can instead be understood in terms of the interaction between modulation filters and the inherent fluctuations in the carrier.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                12 September 2012
                : 7
                : 9
                : e43615
                Affiliations
                [1]Animal Physiology and Behavior Group, Department of Biology and Environmental Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
                Max Planck Institute for Human Cognitive and Brain Sciences, Germany
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: GMK LVD. Performed the experiments: LVD. Analyzed the data: LVD. Contributed reagents/materials/analysis tools: LVD RB. Wrote the paper: LVD GMK RB.

                Article
                PONE-D-12-00311
                10.1371/journal.pone.0043615
                3440405
                22984436
                f3c25a8b-3bab-498d-8515-82ed1e2ee574
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 January 2012
                : 26 July 2012
                Page count
                Pages: 12
                Funding
                This research was supported by the Deutsche Forschungsgemeinschaft (SFB TRR 31, GRK 591) and by a Georg Christoph Lichtenberg stipend of the country of Lower Saxony to the first author. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Computational Neuroscience
                Sensory Systems
                Molecular Cell Biology
                Cellular Types
                Neurons
                Neuroscience
                Sensory Perception
                Psychoacoustics
                Psychophysics
                Sensory Systems
                Auditory System
                Medicine
                Mental Health
                Psychology
                Psychophysics

                Uncategorized
                Uncategorized

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