Elsevier

Clinical Neurophysiology

Volume 127, Issue 1, January 2016, Pages 790-802
Clinical Neurophysiology

Frequency characteristics of neuromagnetic auditory steady-state responses to sinusoidally amplitude-modulated sweep tones

https://doi.org/10.1016/j.clinph.2015.05.002Get rights and content

Highlights

  • Frequency characteristics of neuromagnetic auditory steady-state response (ASSR) were captured for 0.1–12.5 kHz.

  • Strength of the ASSR obtained at constant SPL was maximum at 0.5 kHz.

  • Corresponding loudness model was plateaued between 0.5 and 4 kHz.

Abstract

Objective

This study aimed to capture the neuronal frequency characteristics, as indexed by the auditory steady-state response (ASSR), relative to physical characteristics of constant sound pressure levels (SPLs). Relationship with perceptual characteristics (loudness model) was also examined.

Methods

Neuromagnetic 40-Hz ASSR was recorded in response to sinusoidally amplitude-modulated sweep tones with carrier frequency covering the frequency range of 0.1–12.5 kHz. Sound intensity was equalized at 50-, 60-, and 70-dB SPL with an accuracy of ±0.5-dB SPL at the phasic peak of the modulation frequency. Corresponding loudness characteristics were modeled by substituting the detected individual hearing thresholds into a standard formula (ISO226:2003(E)).

Results

The strength of the ASSR component was maximum at 0.5 kHz, and it decreased linearly on logarithmic scale toward lower and higher frequencies. Loudness model was plateaued between 0.5 and 4 kHz.

Conclusions

Frequency characteristics of the ASSR were not equivalent to those of SPL and loudness model. Factors other than physical and perceptual frequency characteristics may contribute to characterizing the ASSR.

Significance

The results contribute to the discussion of the most efficient signal summation for the generation of the ASSR at 0.5 kHz and efficient neuronal processing at higher frequencies, which require less energy to retain equal perception.

Introduction

Auditory steady-state response (ASSR) is an electrical component of neuronal activity encoding information of periodic modulations of a sound (Langner, 1992, Picton et al., 2003, Joris et al., 2004, Stapells et al., 2004). The ASSR component is specifically characterized by its sensitivity to carrier frequencies (fc) (Galambos et al., 1981, Pantev et al., 1996, Ross et al., 2000, Ross et al., 2003, Wienbruch et al., 2006), providing a useful measure with respect to evaluating the perceptual hearing characteristics per fc, particularly at threshold levels (Aoyagi et al., 1994, Aoyagi et al., 1996, Aoyagi et al., 1999, Lins et al., 1996, Perez-Abalo et al., 2001, Dimitrijevic et al., 2002, Herdman and Stapells, 2003, Picton et al., 2005, Vander Werff and Brown, 2005, Scherf et al., 2006, Ahn et al., 2007). However, the relationship between the frequency characteristics of the ASSR component and hearing characteristics at the supra-threshold levels remains unclear (Vander Werff and Brown, 2005, Ménard et al., 2008, Zenker Castro et al., 2008), despite its possible application, for instance, to adjust the hearing aids objectively and automatically.

The key technical issues concerned with the investigation of the frequency characteristics of the neuromagnetic ASSR component at the supra-threshold level involve the frequency width and frequency resolution to be tested and the accuracy in the calibration of the sound intensity at the output. In the neuromagnetic studies so far, the neuronal sensitivity has been investigated discretely for four or five fc covering the frequency range between 0.25 and 4 kHz (Pantev et al., 1996, Ross et al., 2000, Ross et al., 2002, Ross et al., 2003) or at most up to 6561 Hz (Wienbruch et al., 2006). In fact, the perception of the lower and higher frequencies might not be critical for daily life. However, it is important for higher cognitive functions such as music appreciation and discrimination of individuals (Hayakawa and Itakura, 1994, Besacier et al., 2000). Further, the stimulus tones are typically delivered at 60 or 70 dB sensation level (SL) above the subjects’ hearing thresholds, with an accuracy of ±4 dB sound pressure level (SPL) (Pantev et al., 1996) or ±10 dB SPL (Ross et al., 2000). Considering the fact that 10-dB amplification would result in a 1.5-fold augmentation of the equivalent current dipole (ECD) moment in a 60–70-dB SL range (Ross et al., 2000), it is considered critical to improve the accuracy of the sound intensity calibration method.

In the present study, we examined the frequency characteristics of the neuromagnetic ASSR at the supra-threshold level for a wider frequency range at a finer resolution. Sinusoidally amplitude-modulated (SAM) sweep tones with modulation frequency (fm) of 40 Hz and a carrier frequency (fc) exponentially ascending from 0.1 to 12.5 kHz were presented as stimulus tones, taking advantage of its sweeping characteristics to test the entire frequency range en bloc at the finest resolution. The sound intensity levels of the SAM sweep tones were thoroughly equalized at the fm phasic peaks, in the range of 50–70-dB SPL with an accuracy of ±0.5-dB SPL by applying inverse filtering and real-ear measurement techniques. The magnetoencephalographic (MEG) signal was recorded in response to several kinds of SAM sweep tones that varied in the acoustic and/or presentation parameters. Responses to SAM non-sweeping tones with fixed fc were also examined. The instantaneous strength of the ECD moment at fc sweeping through the frequency/time axes was captured. Corresponding loudness model was simulated by substituting the detected individual hearing threshold into a standard formula for deriving loudness level contour (ISO226:2003(E)). The frequency characteristics of the constant SPL versus the ASSR component, and the ASSR component versus the estimated loudness model, were compared. The differences were quantified and tested statistically.

Section snippets

Stimulus

A stimulus tone was generated by a swept-frequency cosine (chirp) signal ascending exponentially from 0.1 to 12.5 kHz as a function of time with a constant amplitude and a continuous phase. This paradigm was intended to transiently but sequentially activate the frequency-specific auditory cortical neurons located at logarithmic spacing (Romani et al., 1982, Pantev et al., 1988, Pantev et al., 1989, Pantev et al., 1994, Pantev et al., 1995, Pantev et al., 1996, Langner et al., 1997), at an equal

Results

Fig. 2 shows the MEG signals at each stage of the analysis procedure. The temporal courses of the raw, tSSS filtered, and band-pass filtered signals of one sensor from the right temporal area of one subject in response to the stimulus tone [1] are shown in Fig. 2A–C, respectively. The fast-Fourier transformed spectra are shown in the right column, which indicate that the ASSR component was clearly elicited at the fm in the spectral domain. The 40-epochs averaged signal is shown in Fig. 2D,

Methodological issues

In this study, the SAM sweep tones with fc sweeping from 0.1 to 12.5 kHz were presented as stimulus sounds to examine most of the audible frequency range in detail in one analysis. The frequency characteristics of the SAM sweep tones were equalized by dB SPL. The corresponding loudness model was simulated by shifting the detected threshold levels of the individuals according to the LGF of the ISO model (ISO226:2003(E)), per fc. This method was advantageous in controlling the physical frequency

Conclusions

The primary outcome of this study was that the neuronal frequency characteristics for 0.125–10 kHz, as indexed by the ASSR component, showed the maximum strength at 0.5 kHz, relative to the physical characteristics of the constant sound intensity (50–70 (±0.5)-dB SPL) and to the perceptual characteristics simulated to be plateaued between 0.5 and 4 kHz. The difference between the physical, neuronal, and perceptual frequency characteristics was quantified and interpreted as an increase in neuronal

Acknowledgments

The authors thank Dr. Samu Taulu and Dr. Kunihiko Okano for their valuable comments and advice. We are also grateful to Dr. Takayuki Kagomiya and Dr. Kazuhito Ito for providing expert knowledge. This study was supported by the Funding Program for Next-Generation World-Leading Researchers provided by the Cabinet Office, Government of Japan, and the Research Program for the Standardization of MEG, the MEXT Regional Innovation Cluster Program.

Conflict of interest: None declared.

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