Pitch strength of regular-interval click trains with different length “runs” of regular intervals

Yost, William A.; Mapes-Riordan, Dan; Shofner, William P.; Dye, Raymond H.; Sheft, Stanley

doi:10.1121/1.1863712

Cited by 10 publications

(7 citation statements)

References 23 publications

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“…This general scheme would also be consistent with McKay and Carlyon's (1999) finding that listeners can perceive both the carrier and modulator rates of AM stimuli, if one assumes that they can selectively “attend” to different subsets of the more-central neurons. At the same time, it would also be consistent with reports that higher-order intervals do not have a large effect on the pitches of pulse trains that do not produce large and/or regular modulations in the AN response (Kaernbach and Demany, 1998; Plack and White, 2000; Kaernbach and Bering, 2001; Yost et al, 2005).…”

Section: Introductionsupporting

confidence: 90%

“…Carlyon et al's (2002) model successfully accounted for a wide range of findings using a single set of parameters. Furthermore, the idea that the pitches of pulse trains are dominated by first-order intervals is consistent with the conclusions from a number of other recent studies (Kaernbach and Demany, 1998; Kaernbach and Bering, 2001; Yost et al, 2005). However, it has a number of limitations.…”

Section: Introductionsupporting

confidence: 90%

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Behavioral and physiological correlates of temporal pitch perception in electric and acoustic hearing

Carlyon

Mahendran

Deeks

et al. 2008

The Journal of the Acoustical Society of America

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In the "4-6" condition of experiment 1, normal-hearing (NH) listeners compared the pitch of a bandpass-filtered pulse train, whose inter-pulse intervals (IPIs) alternated between 4 and 6 ms, to that of isochronous pulse trains. Consistent with previous results obtained at a lower signal level, the pitch of the 4-6 stimulus corresponded to that of an isochronous pulse train having a period of 5.7 ms -longer than the mean IPI of 5 ms. In other conditions the IPI alternated between 3.5-5.5 ms and 4.5-6.5 ms. Experiment 2 was similar but presented electric pulse trains to one channel of a CI. In both cases, as overall IPI increased, the pitch of the alternating-interval stimulus approached that of an isochronous train having a period equal to the mean IPI. Experiment 3 measured compound action potentials (CAPs) to alternating-interval stimuli in guinea pigs and in NH listeners. The CAPs to pulses occurring after 4-ms intervals were smaller than responses to pulses occurring after 6-ms intervals, resulting in a modulated pattern that was independent of overall level. The results are compared to the predictions of a simple model incorporating auditory-nerve (AN) refractoriness, and where pitch is estimated from 1 st -order intervals in the AN response.

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Section: Introductionsupporting

confidence: 90%

Section: Introductionsupporting

confidence: 90%

Behavioral and physiological correlates of temporal pitch perception in electric and acoustic hearing

Carlyon

Mahendran

Deeks

et al. 2008

The Journal of the Acoustical Society of America

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“…There is some evidence (Chait et al, 2005) that this is the case; however, the exact relationship between recorded MEG responses and behavior should be elaborated on in future studies. These investigations may provide a key as to the aspects of stimulus statistics to which listeners are sensitive (Yost et al, 2005) as well as illuminate the dimensions of auditory signals that are relevant for the construction of perceptual representations. A-D, Plotted in black is the rms magnetic field over all 157 channels derived from the grand average (average over subjects and stimulus repetitions) of the evoked auditory cortical field low-pass filtered at 10 Hz.…”

Section: Discussionmentioning

confidence: 99%

Processing Asymmetry of Transitions between Order and Disorder in Human Auditory Cortex

Chait¹,

Poeppel²,

Cheveigné³

et al. 2007

J. Neurosci.

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Auditory environments vary as a result of the appearance and disappearance of acoustic sources, as well as fluctuations characteristic of the sources themselves. The appearance of an object is often manifest as a transition in the pattern of ongoing fluctuation, rather than an onset or offset of acoustic power. How does the system detect and process such transitions? Based on magnetoencephalography data, we show that the temporal dynamics and response morphology of the neural temporal-edge detection processes depend in precise ways on the nature of the change. We measure auditory cortical responses to transitions between "disorder," modeled as a sequence of random frequency tone pips, and "order," modeled as a constant tone. Such transitions embody key characteristics of natural auditory edges. Early cortical responses (from ϳ50 ms post-transition) reveal that order-disorder transitions, and vice versa, are processed by different neural mechanisms. Their dynamics suggest that the auditory cortex optimally adjusts to stimulus statistics, even when this is not required for overt behavior. Furthermore, this response profile bears a striking similarity to that measured from another order-disorder transition, between interaurally correlated and uncorrelated noise, a radically different stimulus. This parallelism suggests the existence of a general mechanism that operates early in the processing stream on the abstract statistics of the auditory input, and is putatively related to the processes of constructing a new representation or detecting a deviation from a previously acquired model of the auditory scene. Together, the data reveal information about the mechanisms with which the brain samples, represents, and detects changes in the environment.

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“…We tested this hypothesis using acoustic pulse trains, a sequence of brief sounds that can be temporally jittered parametrically between a periodic temporal structure ("regular") and a highly random temporal structure ("irregular"). A regular pulse train generates a salient pitch percept, and the pitch salience degrades with increasing temporal irregularity even though the average repetition rate remains unchanged (Kaernbach and Demany 1998; Yost et al 2005). Here we show that pitch-selective neurons are sensitive to temporal regularity and that the firing rates of modulation sensitive neurons outside the putative pitch center generally do not change between regular and irregular acoustic pulse trains with the same average repetition rate.…”

mentioning

confidence: 99%

Neural Coding of Periodicity in Marmoset Auditory Cortex

Bendor

Wang

2010

Journal of Neurophysiology

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Bendor D, Wang X. Neural coding of periodicity in marmoset auditory cortex. J Neurophysiol 103: 1809 -1822, 2010. First published February 10, 2010 doi:10.1152/jn.00281.2009. Pitch, our perception of how high or low a sound is on a musical scale, crucially depends on a sound's periodicity. If an acoustic signal is temporally jittered so that it becomes aperiodic, the pitch will no longer be perceivable even though other acoustical features that normally covary with pitch are unchanged. Previous electrophysiological studies investigating pitch have typically used only periodic acoustic stimuli, and as such these studies cannot distinguish between a neural representation of pitch and an acoustical feature that only correlates with pitch. In this report, we examine in the auditory cortex of awake marmoset monkeys (Callithrix jacchus) the neural coding of a periodicity's repetition rate, an acoustic feature that covaries with pitch. We first examine if individual neurons show similar repetition rate tuning for different periodic acoustic signals. We next measure how sensitive these neural representations are to the temporal regularity of the acoustic signal. We find that neurons throughout auditory cortex covary their firing rate with the repetition rate of an acoustic signal. However, similar repetition rate tuning across acoustic stimuli and sensitivity to temporal regularity were generally only observed in a small group of neurons found near the anterolateral border of primary auditory cortex, the location of a previously identified putative pitch processing center. These results suggest that although the encoding of repetition rate is a general component of auditory cortical processing, the neural correlate of periodicity is confined to a special class of pitch-selective neurons within the putative pitch processing center of auditory cortex.

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Pitch strength of regular-interval click trains with different length “runs” of regular intervals

Cited by 10 publications

References 23 publications

Behavioral and physiological correlates of temporal pitch perception in electric and acoustic hearing

Behavioral and physiological correlates of temporal pitch perception in electric and acoustic hearing

Processing Asymmetry of Transitions between Order and Disorder in Human Auditory Cortex

Neural Coding of Periodicity in Marmoset Auditory Cortex

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