Elsevier

Brain Research

Volume 786, Issues 1–2, 9 March 1998, Pages 18-30
Brain Research

Research report
Pitch vs. spectral encoding of harmonic complex tones in primary auditory cortex of the awake monkey

https://doi.org/10.1016/S0006-8993(97)01423-6Get rights and content

Abstract

Neuromagnetic studies in humans and single-unit studies in monkeys have provided conflicting views regarding the role of primary auditory cortex (A1) in pitch encoding. While the former support a topographic organization based on the pitch of complex tones, single-unit studies support the classical tonotopic organization of A1 defined by the spectral composition of the stimulus. It is unclear whether the incongruity of these findings is due to limitations of noninvasive recordings or whether the discrepancy genuinely reflects pitch representation based on population encoding. To bridge these experimental approaches, we examined neuronal ensemble responses in A1 of the awake monkey using auditory evoked potential (AEP), multiple-unit activity (MUA) and current source density (CSD) techniques. Macaque monkeys can perceive the missing fundamental of harmonic complex tones and therefore serve as suitable animal models for studying neural encoding of pitch. Pure tones and harmonic complex tones missing the fundamental frequency (f0) were presented at 60 dB SPL to the ear contralateral to the hemisphere from which recordings were obtained. Laminar response profiles in A1 reflected the spectral content rather than the pitch (missing f0) of the compound stimuli. These findings are consistent with single-unit data and indicate that the cochleotopic organization is preserved at the level of A1. Thus, it appears that pitch encoding of multi-component sounds is more complex than suggested by noninvasive studies, which are based on the assumption of a single dipole generator within the superior temporal gyrus. These results support a pattern recognition mechanism of pitch encoding based on a topographic representation of stimulus spectral composition at the level of A1.

Introduction

Pitch is a fundamental feature of auditory perception. It underlies recognition of gender and intonation in speech and forms a basis for our appreciation of music. On a more primitive level, the pitch percept can be viewed as a product of auditory scene analysis, the process by which the auditory system integrates or segregates overlapping frequencies generated by multiple sources in order to construct accurate representations of sound sources in the environment [5]. The pitch evoked by a pure sinusoidal tone correlates with its frequency. However, natural sounds almost always are composed of many simultaneously occurring frequencies. In addition, these component frequencies often are harmonically related, i.e., they are consecutive integer multiples, or harmonics, of a common fundamental frequency (f0). Our auditory experience generally consists not of the pitches of the individual harmonics of complex sounds (spectral pitch), but rather of a unified global pitch equal to the f0. Most importantly, the global pitch of the harmonic complex persists even when spectral energy at the f0 is completely absent from the stimulus.

This phenomenon, known as the pitch of the missing fundamental (also as residue pitch, periodicity pitch and virtual pitch), serves as the foundation for hypotheses regarding the extraction of pitch information from complex sounds 16, 27, 44, 45, 59, 64. Current theories of pitch perception emerge from two different, although not necessarily incompatible, perspectives on auditory system function. One conceptualizes the pitch mechanism as involving an initial spectral analysis of complex sounds based on the place of maximal auditory nerve fiber activation along the basilar membrane. The perceived pitch is subsequently derived by matching the resolved spectral information to a central harmonic template corresponding to the f0 of which the components are integer multiples 16, 19, 59, 64. In contrast to spectral pattern-recognition models, temporal models of pitch representation are based on the auditory system's ability to follow the periodicity of the composite waveform of a harmonic complex tone. Since the repetition rate of the amplitude modulated envelope arising from the summation of component harmonics is equal to the f0, even in the absence of spectral energy at that frequency, pitch information is conveyed by the temporal firing pattern of neurons phase-locked to the f07, 8, 20, 21, 27, 28, 47. While the debate between proponents of spectral pattern-recognition models and temporal models of pitch encoding has assumed an either–or character, ample psychoacoustic evidence has accumulated supporting the coexistence of two mechanisms, one operating in the frequency domain for stimuli containing aurally resolved harmonics and the other operating in the time domain for stimuli consisting of upper harmonics that the peripheral auditory system fails to resolve 16, 19, 20, 52. Given that natural sources typically produce sounds containing harmonically related components, it seems reasonable that neuronal populations might exist that respond to the harmonic features of sound, utilizing either or both of these strategies.

A tonotopic organization of A1 has been demonstrated in a number of mammals (e.g., cat 31, 41, monkey 30, 33). Studies based on positron emission tomography, auditory evoked potentials and auditory evoked magnetic fields have suggested a similar topographic representation in humans, with activity on the superior temporal plane occurring more laterally for tones of low frequency and more medially for tones of higher frequency 3, 26, 36. Such a tonotopic organization has led to the proposal that the pitch of harmonic complex tones, with or without the f0, is mapped onto essentially the same regions as pure tone frequency in auditory cortex [29]. In a human neuromagnetic study designed to test this hypothesis, Pantev et al. [37]reported that the depth of the equivalent current dipole corresponding to the M100 component did not differ significantly in response to a 250 Hz pure tone and to a missing fundamental complex tone of equivalent pitch, whereas significant differences in depth were observed in response to those pure tones that were contained in the complex tone. These results were interpreted as demonstrating an organization in A1 based on pitch rather than frequency. An additional study replicated these results and included the finding that the corresponding virtual pitch representation was activated when the harmonics of the complex tone were distributed between ears, as predicted by psychoacoustic studies demonstrating the central formation of virtual pitch from dichotically presented harmonics 19, 35. Because the M100 component is thought to be generated by activity in A1 and because auditory cortex lesions that include A1 disrupt missing fundamental perception in cats and humans, it is possible that A1 plays a key role in pitch perception for complex tones 36, 63, 66. However, single-unit studies in awake macaques failed to find neurons that responded to the missing fundamental and, therefore, to pitch [51]. Instead, single-unit responses to missing fundamental stimuli were determined by the relationship between the spectral content of the stimulus and the pure tone neuronal tuning curves. The latter finding is consistent with the classical topographic organization of A1 based on frequency. Given the high degree of similarity in auditory cortical anatomy between macaques and humans, it seems unlikely that their primary auditory areas would exhibit functionally disparate organizations of representation [15]. Thus, the basis for pitch encoding of complex sounds in A1 remains controversial.

It is possible that the respective limitations of the techniques employed in these studies are responsible for the disparity of the results. While single-unit studies provide detailed information regarding the firing properties of individual cells, non-invasive studies monitor the synchronous synaptic activity of large neuronal populations, albeit with more limited spatial resolution. Thus, the supposition that the M100 magnetic response is uniquely generated in A1 without contributions from additional adjacent auditory areas is problematic. Consequently, the assumption of a single dipole generator within the superior temporal gyrus that is capable of adequately representing the auditory topographic organization for pitch may not be justified. On the other hand, it is possible that pitch encoding relies on the pattern of activity across large ensembles of neurons (i.e., population encoding), a dimension of analysis that is largely inaccessible using single-unit techniques. Synchronized responses of neuronal ensembles have been shown to represent the functional organization of auditory cortex more reliably than the single-unit firing rate, suggesting that concerted activity of neuronal populations may underlie encoding of perceptual features such as pitch [12].

The present study attempts to clarify whether A1 is characterized by topographic organization based on frequency or on pitch by bridging the single-unit level of analysis with that explored using non-invasive techniques measuring synchronous activity of neuronal populations. Simultaneous intracranial recordings of auditory evoked potentials (AEPs), multiunit activity (MUA) and the laminar distribution of current source density (CSD) derived from the AEP profiles were used to identify the location and magnitude of neuronal ensemble activation in A1 of the macaque monkey, as they relate to the encoding of harmonic complex tones missing the f0. The advantage of these techniques is that they measure both firing patterns and synchronized synaptic activity of neuronal populations with higher spatial resolution than in noninvasive studies. In addition, these techniques allow dissociation of cortical activity into its temporally discrete components and thereby permit analysis of individual phases of the response. As suggested by the reported uniqueness of the human M100 in correlating with pitch, these distinct response components may reflect activity in specific processing streams encoding specific attributes of environmental sounds [37]. Macaques share many features of auditory cortical anatomy and physiology with humans and also are capable of perceiving the missing fundamental of harmonic complex tones, making them a suitable animal model for exploring intracortical mechanisms underlying pitch encoding in the auditory system 15, 57, 60.

Section snippets

Materials and methods

Four adult male monkeys (Macaca fascicularis) were studied using methods previously reported [54]. All animals were housed in our AAALAC-accredited Animal Institute under daily supervision by veterinary staff. Briefly, under general anesthesia and using aseptic techniques, small holes were made in the exposed skull to accommodate epidural matrices of adjacently placed 18-gauge stainless steel tubes. Matrices were stereotaxically positioned to target A1 and were oriented at an angle of 30° from

Results

Results are based on a total of 16 electrode penetrations into A1 of four monkeys with BFs between 300 and 2000 Hz. Although not included in the statistical analysis, results from eight additional electrode penetrations with BFs outside the range of f0s encompassed by the compound stimuli are discussed at the end of the results section.

In all of the cortical sites examined, MUA elicited by harmonic complexes clearly reflects the spectral content and not the missing f0 of the stimulus,

Discussion

Previous physiological studies have provided conflicting conceptions of the cortical mechanisms involved in encoding the pitch of complex tones. Single-unit studies in awake macaques demonstrate that responses to harmonic complex tones missing the f0 are determined by the relationship between the BF of the area and the spectral content of the stimulus [51]. Conversely, non-invasive neuromagnetic studies in humans support a topographic organization at the level of A1 which is based on the pitch

Acknowledgements

We are sincerely grateful to Dr. Steven Walkley and May Huang for providing histological facilities and assistance, Dr. Charles Schroeder for his assistance with the surgical procedures, Shirley Seto for constructing the electrodes and Susana Chan for technical help. This research was supported by grants DC00657 and MH06723 and the Institute for the Study of Music and Neurologic Function of Beth Abraham Hospital. Submitted in partial fulfillment of the requirements for the degree of Doctor of

References (66)

  • M. Steinschneider et al.

    Tonotopic features of speech-evoked activity in primate auditory cortex

    Brain Res.

    (1990)
  • M. Steinschneider et al.

    Speech-evoked activity in primary auditory cortex: effects of voice onset time

    Electroencephalogr. Clin. Neurophysiol.

    (1994)
  • M. Steinschneider et al.

    Cellular generators of the cortical auditory evoked potential initial component

    Electroencephalogr. Clin. Neurophysiol.

    (1992)
  • C.C. Wood et al.

    Scalp topography of human auditory evoked potentials: II. Evidence for overlapping sources and involvement of auditory cortex

    Electroencephalogr. Clin. Neurophysiol.

    (1982)
  • J.C. Arezzo, H.G. Vaughan Jr., M.A. Kraut, M. Steinschneider, A.D. Legatt, Intracranial generators of event-related...
  • O. Bertrand et al.

    Evidence for a tonotopic organization of the auditory cortex observed with auditory evoked potentials

    Acta Oto-Laryngol. (Stockh) Suppl.

    (1991)
  • A. Bieser et al.

    Auditory responsive cortex in the squirrel monkey: neural responses to amplitude-modulated sounds

    Exp. Brain. Res.

    (1996)
  • A.S. Bregman, Auditory Scene Analysis: The Perceptual Organization of Sound, MIT Press, Cambridge, Massachusetts,...
  • M. Brosch et al.

    Stimulus-dependent modulations of correlated high-frequency oscillations in cat visual cortex

    Cereb. Cortex

    (1997)
  • P.A. Cariani et al.

    Neural correlates of the pitch of complex tones: I. Pitch and pitch salience

    J. Neurophysiol.

    (1996)
  • P.A. Cariani et al.

    Neural correlates of the pitch of complex tones: II. Pitch shift, pitch ambiguity, phase invariance, pitch circularity, rate pitch and the dominance region for pitch

    J. Neurophysiol.

    (1996)
  • H.B. Coslett et al.

    Pure word deafness after primary auditory cortex infarcts

    Neurology

    (1984)
  • O. Creutzfeldt et al.

    Thalamocortical transformation of responses to complex auditory stimuli

    Exp. Brain Res.

    (1980)
  • J. Cynx et al.

    Perception of missing fundamental by a species of songbird (Sturnus vulgaris)

    J. Comp. Psychol.

    (1986)
  • R.C. DeCharms et al.

    Cortical representation of sounds by the coordination of action potential timing

    Nature

    (1996)
  • J.A. Freeman et al.

    Experimental optimization of current source density technique for anuran cerebellum

    J. Neurophysiol.

    (1975)
  • A. Galaburda et al.

    Cytoarchitectonic organization of the human auditory cortex

    J. Comp. Neurol.

    (1980)
  • J.L. Goldstein

    An optimum processor theory for the central formation of the pitch of complex tones

    J. Acoust. Soc. Am.

    (1973)
  • M.H. Goldstein et al.

    Responses of the auditory cortex to repetitive acoustic stimuli

    J. Acoust. Soc. Am.

    (1959)
  • H. Heffner et al.

    Perception of the missing fundamental by cats

    J. Acoust. Soc. Am.

    (1976)
  • A.J.M. Houtsma et al.

    The central origin of the pitch of complex tones: evidence from musical interval recognition

    J. Acoust. Soc. Am.

    (1972)
  • A.J.M. Houtsma et al.

    Pitch identification and discrimination for complex tones with many harmonics

    J. Acoust. Soc. Am.

    (1990)
  • G. Langner

    Periodicity pitch and party effect: temporal processing, intrinsic oscillations and binding in the auditory system

    Soc. Neurosci. Abstr.

    (1995)
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