Elsevier

NeuroImage

Volume 20, Issue 1, September 2003, Pages 265-275
NeuroImage

Regular article
Spectrotemporal features of the auditory cortex: the activation in response to dynamic ripples

https://doi.org/10.1016/S1053-8119(03)00258-1Get rights and content

Abstract

Functional MRI was used to investigate the characteristics of the human cerebral response to dynamic ripples. Dynamic ripples are sound stimuli containing regular spectrotemporal modulations, which are of major importance in speech processing; however, in contrast to speech, dynamic ripples can be characterized fully by a limited number of parameters. Extensive activation consisting of multiple separate regions was found bilaterally in the auditory cortex, particularly along the Heschl's gyri. This agrees with the presence of a structural cortical subdivision into functional fields. The level and the extent of activation were measured and correlated highly (R2 = 0.97). Both measures depended strongly on the spectral density, temporal frequency, and amplitude of the modulations and matched the perceptual discernibility of the spectrotemporal modulations. The largest responses occurred for parameter values near the optimal human sensitivity. The drift direction of the modulations did not influence the activation. No quantitative differences were found between the two hemispheres. Average brain activation levels proved to be separable with regard to the spectral density and temporal frequency of the modulations. Topographic mappings of the modulation density and frequency onto the cortical surface were shown, approximately in posterolateral-to-anteromedial and lateral-to-medial directions, respectively. Posterolateral regions were most sensitive to spectrotemporal features at a scale similar to phonemes. Anteromedial regions, however, were also relatively sensitive to smaller scale acoustic features. This spatially dependent sensitivity suggests a functional topographic and hierarchical organization of the auditory cortex.

Introduction

In this study we focused on sound properties related to speech, the processing of which obviously is an important function of the human brain Belin et al., 2000, Belin et al., 2002, Jäncke et al., 2002, Wong et al., 2002, Wise et al., 2001, Scott et al., 2000. In systematic studies, the structural complexity of vocal sounds is a significant problem when defining their exact properties (Hickok and Poeppel, 2000). Therefore, simpler sound signals have been derived that can be defined with mathematical exactitude, but that still contain some essential characteristics of vocal sounds. An important category of such signals comprises modulated noise. The most basic of these modulated noise signals contain either temporal amplitude modulations Giraud et al., 2000, Wakefield and Viemeister, 1990 or static spectral modulations, also known as rippled noise Supin et al., 1999, Calhoun and Schreiner, 1998, Versnel and Shamma, 1998. However, modulations in the spectrum of speech are dynamic. Similar dynamic behavior can be incorporated into modulated noise by combining temporal and spectral modulations, resulting in a spectral ripple drifting in time along the frequency axis (Fig. 1). Such signals have a similar spectrotemporal envelope as speech and can model formant transitions between vowels and changes in pitch due to intonation. However, the resemblances between dynamic ripples and vocal sounds are limited to acoustic and phonetic properties. Dynamic ripples are not associated with speech on a phonological or linguistical level, involving the recognition of syllables or the comprehension of words.

Dynamic ripples can be characterized by four parameters (Fig. 2): the spectral modulation density Ω (in cycles per octave, c/o), the temporal modulation frequency ω (in cycles per second, c/s), the modulation amplitude A (%), and the drift direction d (downward or upward). Any sound pattern can be regarded as a superposition of such dynamic ripples, since they form a complete orthonormal basis of functions. In electrophysiological animal studies, dynamic ripples play a useful role in characterizing neuronal spectrotemporal response fields Miller et al., 2002, Depireux et al., 2001, Klein et al., 2000, Kowalski et al., 1996. Selective neuronal responses to the speed and direction of spectral changes have been reported using a range of stimuli Liang et al., 2002, deCharms et al., 1998, Tian and Rauschecker, 1998, as well as corresponding topographic mappings on the brain's cortical surface Versnel et al., 1995, Mendelson et al., 1993, Shamma et al., 1993. However, in humans electrophysiological experiments are unfeasible due to the invasive nature of this technique. Psychoacoustical experiments have been performed to measure thresholds for the perceptual detection of spectrotemporal modulations; near an optimum at Ω = 0.5 c/o and ω = 4 c/s, dynamic ripples with amplitudes A as low as 5% can be discerned from noise without modulations (Chi et al., 1999).

We used functional MRI (fMRI), which is a volume imaging technique that is suitable for humans, with the additional advantage of a high spatial resolution. Although the poor time resolution prevented us from directly detecting any synchronization of neuronal responses with the temporal sound modulations, sustained changes in overall activity due to selective neural activation were measurable (Seifritz et al., 2002). Given that the presence of tonotopy in the auditory cortex has previously been demonstrated using fMRI Engelien et al., 2002, Le et al., 2001, Talavage et al., 2000, Bilecen et al., 1998, Wessinger et al., 1997, it may also be able to reveal any topographic organization associated with dynamic ripples. In contrast to animal studies, the activation of the human auditory cortex in response to dynamic ripples has not yet been studied systematically; in this paper we investigate the magnitude and spatial distribution of the cortical activation as a function of the previously mentioned dynamic ripple characteristics.

Section snippets

Subjects

Nine healthy subjects with normal hearing were recruited (eight male, one female; aged 23–59 years, mean 37 years) and gave written informed consent to participate in this study. Of all subjects, four were right-handed, three left-handed, and two ambidextrous (Oldfield, 1971). Subjects received an explanation and a short demonstration beforehand, but were not trained to the task.

Stimulus paradigm

A sound generation setup was used to present the auditory stimuli. Each stimulus presentation consisted of a series

Activation extent and activation level

The cerebral activation caused by the spectrotemporal modulations in dynamic ripples depended on the parameters of the stimulus. Fig. 4 shows the results with respect to the ae, averaged over all subjects. We found that ae is maximal for low modulation densities (Ω=14 c/o ) and small modulation frequencies (ω = 2 c/s) and decreases monotonically for both Ω and ω. With regard to the modulation amplitude we found that ae increased with A. In contrast, we did not find any significant changes in ae

Activation dependencies

We considered two quantitative measures, the extent (ae) and the level (al) of activation. In principle it is possible for these two measures to show different dependencies on the dynamic ripple parameter values. After all, large volumes that show marginally significant activation might well be imagined, as well as confined regions with high activation levels. Nevertheless, our data show an almost perfect correspondence between both measures (R2 = 0.97); ae shows the same general trends as al.

References (62)

  • P Morosan et al.

    Human primary auditory cortexcytoarchitectonic subdivisions and mapping into a spatial reference system

    Neuroimage

    (2001)
  • R.C Oldfield

    The assessment and analysis of handednessthe Edinburgh inventory

    Neuropsychologia

    (1971)
  • K.J Palomaki et al.

    Cortical processing of speech sounds and their analogues in a spatial auditory environment

    Brain Res. Cogn. Brain Res.

    (2002)
  • J Rademacher et al.

    Probabilistic mapping and volume measurement of human primary auditory cortex

    Neuroimage

    (2001)
  • C.E Schreiner et al.

    Representation of amplitude modulation in the auditory cortex of the cat. II. Comparison between cortical fields

    Hearing. Res.

    (1988)
  • T.M Talavage et al.

    Frequency-dependent responses exhibited by multiple regions in human auditory cortex

    Hearing Res.

    (2000)
  • D Wong et al.

    PET imaging of differential cortical activation by monaural speech and nonspeech stimuli

    Hearing Res.

    (2002)
  • R.J Zatorre et al.

    Structure and function of auditory cortexmusic and speech

    Trends Cogn. Sci.

    (2002)
  • E Amaro et al.

    Acoustic noise and functional magnetic resonance imagingCurrent strategies and future prospects

    J. Magn. Reson. Imaging

    (2002)
  • W.H Backes et al.

    Simultaneous sampling of event-related BOLD responses in auditory cortex and brainstem

    Magn. Reson. Med.

    (2002)
  • P Belin et al.

    Voice-selective areas in human auditory cortex

    Nature

    (2000)
  • J.R Binder et al.

    Human brain language areas identified by functional magnetic resonance imaging

    J. Neurosci.

    (1997)
  • J.R Binder et al.

    Human temporal lobe activation by speech and nonspeech sounds

    Cereb. Cortex

    (2000)
  • A Brechmann et al.

    Sound-level-dependent representation of frequency modulations in human auditory cortexa low-noise fMRI study

    J. Neurophysiol.

    (2002)
  • B.M Calhoun et al.

    Spectral envelope coding in cat primary auditory cortexlinear and non-linear effects of stimulus characteristics

    Eur. J. Neurosci.

    (1998)
  • T Chi et al.

    Spectro-temporal modulation transfer functions and speech intelligibility

    J. Acoust. Soc. Am.

    (1999)
  • R.C deCharms et al.

    Optimizing sound features for cortical neurons

    Science

    (1998)
  • J.F Demonet et al.

    The anatomy of phonological and semantic processing in normal subjects

    Brain

    (1992)
  • D.A Depireux et al.

    Spectro-temporal response field characterization with dynamic ripples in ferret primary auditory cortex

    J. Neurophysiol.

    (2001)
  • W.B Edmister et al.

    Improved auditory cortex imaging using clustered volume acquisitions

    Human Brain Mapp.

    (1999)
  • A Galaburda et al.

    Cytoarchitectonic organization of the human auditory cortex

    J. Comp. Neurol.

    (1980)
  • Cited by (0)

    View full text