Neural correlates of the pitch of complex tones. I. Pitch and pitch salience
01 Sep 1996-Journal of Neurophysiology (American Physiological Society Bethesda, MD)-Vol. 76, Iss: 3, pp 1698-1716
TL;DR: The temporal discharge patterns of auditory nerve fibers in Dial-anesthetized cats were studied in response to periodic complex acoustic waveforms that evoke pitches at their fundamental frequencies, suggesting that existence of a central processor capable of analyzing these interval patterns could provide a unified explanation for many different aspects of pitch perception.
Abstract: 1. The temporal discharge patterns of auditory nerve fibers in Dial-anesthetized cats were studied in response to periodic complex acoustic waveforms that evoke pitches at their fundamental frequencies. Single-formant vowels, amplitude-modulated (AM) and quasi-frequency-modulated tones. AM noise, click trains, and other complex tones were utilized. Distributions of intervals between successive spikes ("1st-order intervals") and between both successive and nonsuccessive spikes ("all-order intervals") were computed from spike trains. Intervals from many fibers were pooled to estimate interspike interval distributions for the entire auditory nerve. Properties of these "pooled interspike interval distributions," such as the positions of interval peaks and their relative heights, were examined for correspondence to the psychophysical data on pitch frequency and pitch salience. 2. For a diverse set of complex stimuli and levels, the most frequent all-order interspike interval present in the pooled distribution corresponded to the pitch heard in psychophysical experiments. Pitch estimates based on pooled interval distributions (30-85 fibers, 100 stimulus presentations per fiber) were highly accurate (within 1%) for harmonic stimuli that produce strong pitches at 60 dB SPL. 3. Although the most frequent intervals in pooled all-order interval distributions were very stable with respect to sound intensity level (40, 60, and 80 dB total SPL), this was not necessarily the case for first-order interval distributions. Because the low pitches of complex tones are largely invariant with respect to level, pitches estimated from all-order interval distributions correspond better to perception. 4. Spectrally diverse stimuli that evoke similar low pitches produce pooled interval distributions with similar most-frequent intervals. This suggests that the pitch equivalence of these different stimuli could result from central auditory processing mechanisms that analyze interspike interval patterns. 5. Complex stimuli that evoke strong or "salient" pitches produce pooled interval distributions with high peak-to-mean ratios. Those stimuli that evoke weak pitches produce pooled interval distributions with low peak-to-mean ratios. 6. Pooled interspike interval distributions for stimuli consisting of low-frequency components generally resembled the short-time auto-correlation function of stimulus waveforms. Pooled interval distributions for stimuli consisting of high-frequency components resembled the short-time autocorrelation function of the waveform envelope. 7. Interval distributions in populations of neurons constitute a general, distributed means of encoding, transmitting, and representing information. Existence of a central processor capable of analyzing these interval patterns could provide a unified explanation for many different aspects of pitch perception.
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TL;DR: An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds, based on the well-known autocorrelation method with a number of modifications that combine to prevent errors.
Abstract: An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated over a database of speech recorded together with a laryngograph signal. There is no upper limit on the frequency search range, so the algorithm is suited for high-pitched voices and music. The algorithm is relatively simple and may be implemented efficiently and with low latency, and it involves few parameters that must be tuned. It is based on a signal model (periodic signal) that may be extended in several ways to handle various forms of aperiodicity that occur in particular applications. Finally, interesting parallels may be drawn with models of auditory processing.
1,975 citations
Journal Article•
TL;DR: Alk-3-en-1-ols are produced in good yields from isobutylene and formaldehyde in the presence of organic carboxylic acid salts of Group IB metals.
Abstract: The yield of alkenols and cycloalkenols is substantially improved by carrying out the reaction of olefins with formaldehyde in the presence of selected catalysts. In accordance with one embodiment, alk-3-en-1-ols are produced in good yields from isobutylene and formaldehyde in the presence of organic carboxylic acid salts of Group IB metals.
851 citations
TL;DR: The existence of neurons in the auditory cortex of marmoset monkeys that respond to both pure tones and missing fundamental harmonic complex sounds with the same f0, providing a neural correlate for pitch constancy are shown.
Abstract: Pitch perception plays a critical role in identifying and segregating auditory objects 1 , especially in the context of music and speech. The perception of pitch is not unique to humans and has been experimentally demonstrated in several animal species 2,3 . Pitch is the subjective attribute of a sound’s fundamental frequency (f0), that is determined by both the temporal regularity and average repetition rate of its acoustic waveform. Spectrally dissimilar sounds can have the same pitch if they share a common f0. Even when the acoustic energy at f0 is removed (“missing fundamental”) the same pitch is still perceived 1 . Despite its importance for hearing, how pitch is represented in the cerebral cortex remains unknown. Here we show the existence of neurons in the auditory cortex of marmoset monkeys that respond to both pure tones and missing fundamental harmonic complex sounds (MFs) with the same f0, providing a neural correlate for pitch constancy 1 . These pitchselective neurons are located in a restricted low-frequency cortical region near the anterolateral border of primary auditory cortex (AI), consistent with the location of a pitch-selective area identified in recent human imaging studies 4,5 .
547 citations
TL;DR: The OPERA hypothesis is used to account for the observed superior subcortical encoding of speech in musically trained individuals, and to suggest mechanisms by which musical training might improve linguistic reading abilities.
Abstract: Mounting evidence suggests that musical training benefits the neural encoding of speech. This paper offers a hypothesis specifying why such benefits occur. The “OPERA” hypothesis proposes that such benefits are driven by adaptive plasticity in speech-processing networks, and that this plasticity occurs when five conditions are met. These are: 1) Overlap: there is anatomical overlap in the brain networks that process an acoustic feature used in both music and speech (e.g., waveform periodicity, amplitude envelope), 2) Precision: music places higher demands on these shared networks than does speech, in terms of the precision of processing, 3) Emotion: the musical activities that engage this network elicit strong positive emotion, 4) Repetition: the musical activities that engage this network are frequently repeated, and 5) Attention: the musical activities that engage this network are associated with focused attention. According to the OPERA hypothesis, when these conditions are met neural plasticity drives the networks in question to function with higher precision than needed for ordinary speech communication. Yet since speech shares these networks with music, speech processing benefits. The OPERA hypothesis is used to account for the observed superior subcortical encoding of speech in musically trained individuals, and to suggest mechanisms by which musical training might improve linguistic reading abilities.
464 citations
Cites background from "Neural correlates of the pitch of c..."
...At the subcortical level, the auditory system likely uses similar mechanisms and networks for encoding periodicity in speech and music, including patterns of action potential timing in neurons in the auditory pathway between cochlea and inferior colliculus (Cariani and Delgutte, 1996; cf. Figure 2)....
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...The periodicities in the FFR reflect the synchronized component of this population response, arising from neural phase locking to speech waveform periodicities in the auditory nerve and propagating up the auditory pathway (cf. Cariani and Delgutte, 1996)....
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TL;DR: The results support the possibility of neural plasticity at the brainstem level that is induced by language experience that may be enhancing or priming linguistically relevant features of the speech input.
413 citations
References
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Book•
01 Jan 1977
TL;DR: In this paper, the nature of sound and the structure and function of the auditory system are discussed, including absolute thresholds, frequency selectivity, masking and the critical band, and the perception of loudness.
Abstract: Preface to the Fifth Edition The nature of sound and the structure and function of the auditory system Absolute thresholds Frequency selectivity, masking and the critical band The perception of loudness Temporal processing in the auditory system Pitch perception Space perception Auditory pattern and object perception Speech perception Practical applications References Glossary Index
2,729 citations
Book•
03 Dec 1990
TL;DR: This description of the processing of sound by the human hearing system presents the quantitative relationship between sound stimuli and auditory perceptions in terms of hearing sensations, and implements these relationships in model form.
Abstract: Stimuli and Procedures * Hearing Area * Information Processing in the Auditory System * Masking * Pitch and Pitch Strength * Critical Bands and Excitation * Just-Noticeable Sound Changes * Loudness * Sharpness and Sensory Pleasantness * Fluctuation Strength * Roughness * Subjective Duration * Rhythm * The Ear's Own Nonlinear Distortion * Binaural Hearing * Examples of Application.
2,105 citations
TL;DR: In this paper, the authors provide an account of current trends in auditory research on a level not too technical for the novice, by relating psychological and perceptual aspects of sound to the underlying physiological mechanisms of hearing in a way that the material can be used as a text to accompany an advanced undergraduate or graduate level course in auditory perception.
Abstract: The author's stated general approach is to relate the psychological and perceptual aspects of sound to the underlying physiological mechanisms of hearing in a way that the material can be used as a text to accompany an advanced undergraduate- or graduate-level course in auditory perception. The attempt is to provide an account of current trends in auditory research on a level not too technical for the novice. Psychoacoustic studies on humans and physiological studies on animals serve as the primary bases for subject matter presentation, and many practical applications are offered. Among the chapters are the following: the nature of sound and the structure of the auditory system; loudness, adaptation, and fatigue; frequency analysis, masking, and critical bands; pitch perception and auditory pattern perception; space perception; and speech perception. Within these chapter headings special attention is given to a number of topics, including signal detection theory, monaural and binaural hearing,
1,956 citations
TL;DR: It is shown that the newer extended data on human cadaver ears and from living animal preparations are quite well fit by the same basic function, which increases the function's value in plotting auditory data and in modeling concerned with speech and other bioacoustic signals.
Abstract: Accurate cochlear frequency-position functions based on physiological data would facilitate the interpretation of physiological and psychoacoustic data within and across species. Such functions might aid in developing cochlear models, and cochlear coordinates could provide potentially useful spectral transforms of speech and other acoustic signals. In 1961, an almost-exponential function was developed (Greenwood, 1961b, 1974) by integrating an exponential function fitted to a subset of frequency resolution-integration estimates (critical bandwidths). The resulting frequency-position function was found to fit cochlear observations on human cadaver ears quite well and, with changes of constants, those on elephant, cow, guinea pig, rat, mouse, and chicken (Bekesy, 1960), as well as in vivo (behavioral-anatomical) data on cats (Schucknecht, 1953). Since 1961, new mechanical and other physiological data have appeared on the human, cat, guinea pig, chinchilla, monkey, and gerbil. It is shown here that the newer extended data on human cadaver ears and from living animal preparations are quite well fit by the same basic function. The function essentially requires only empirical adjustment of a single parameter to set an upper frequency limit, while a "slope" parameter can be left constant if cochlear partition length is normalized to 1 or scaled if distance is specified in physical units. Constancy of slope and form in dead and living ears and across species increases the probability that the function fitting human cadaver data may apply as well to the living human ear. This prospect increases the function's value in plotting auditory data and in modeling concerned with speech and other bioacoustic signals, since it fits the available physiological data well and, consequently (if those data are correct), remains independent of, and an appropriate means to examine, psychoacoustic data and assumptions.
1,789 citations
"Neural correlates of the pitch of c..." refers methods in this paper
...This human CF distribution was estimated by scaling the distribution of cat ANF CFs (Liberman 1982; Melcher 1993) downward in frequency by a factor of 2.8 (Greenwood 1990)....
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966 citations