Neurobiologic responses to speech in noise in children with learning problems: deficits and strategies for improvement
Introduction
Recent studies indicate that speech-sound perception deficits may contribute to the learning problems (LP) of some children. In particular, these children have difficulty discriminating between acoustically similar sounds (Tallal and Piercy, 1974, Tallal, 1980, Elliott et al., 1989, Stark and Heinz, 1996, Kraus et al., 1996, Bradlow et al., 1999). Moreover, these deficits become worse in the presence of background noise (Nabelek and Pickett, 1974, Elliott, 1979, Bellis, 1996, Chermak and Musiek, 1997). While the underlying cause of speech-sound perception deficits remains controversial (Tallal and Piercy, 1974, Tallal, 1980, Nittrouer, 1992, Studdert-Kennedy and Mody, 1995, Denneberg, 1999), new evidence suggests that basic neurophysiologic processes related to stimulus encoding and discrimination may be involved. Three recent studies have begun to elucidate the biological bases of impaired speech perception in some individuals with LP. First, poor readers differed from good readers in neural recovery time of auditory cortical responses to rapidly presented stimuli (Nagarajan et al., 1999). Second, dyslexic individuals displayed significantly smaller far-field EEG amplitude modulated following responses than normal subjects (McAnally and Stein, 1997). Finally, a subset of children with LP showed a significant reduction in cortical responses to speech-sound contrasts differing in rapid spectro-temporal elements, consistent with their impaired behavioral discrimination of those stimuli (Kraus et al., 1996).
Despite general acknowledgement that background noise excessively taxes perception in most children with LP, little is known about the underlying neurobiologic processes. The first goal of this investigation was to determine whether speech perception deficits in some LP children are associated with abnormal neurophysiologic representation of rapidly changing speech features in noise reflected by potentials generated at brain-stem and cortical levels. To accomplish this aim, auditory brain-stem responses (ABR), frequency-following responses (FFR) and cortical-evoked potentials were studied in a group of LP children and compared to responses in normal children.
Evaluation of these electrophysiologic measures separately and in combination provides a unique opportunity to assess the integrity of central auditory stimulus-timing mechanisms at various levels of the auditory pathway. For instance, the ABR reflects neural activity synchronized to the stimulus onset. It is generated by action potentials traveling along axons in a pattern of short-duration, biphasic responses. The magnitude of the ABR depends on a high degree of synchronized firing among the neurons, such that deviations of tenths of milliseconds are considered diagnostic of brain-stem pathology (Starr and Don, 1988). If there is excessive neural ‘jitter’, which might occur in an impaired auditory system, the separation of individual neural responses by even a fraction of a millisecond could cause responses to cancel each other out. The FFR also depends on a high degree of neural synchrony. It reflects brain-stem-generated, phase-locked responses to the low frequency components of a stimulus (less than 800 Hz) (Worden and Marsh, 1968). Differences between brain-stem and cortical responses are particularly apparent in the overall spectra of the evoked responses (ABR ∼1 kHz, Boston and Moller, 1985; cortical potentials ∼10 Hz, Moller, 1994). Cortical responses reflect the summation of excitatory post-synaptic potentials originating from multiple generator sites in response to stimulus onset and other acoustic features of the stimulus. These slow dendritic events can be separated by several milliseconds and will still sum constructively. Nevertheless, cortical potentials do depend on stimulus-locked synchronous firing across neural ensembles.
The second goal of this study was to examine the perceptual and neurophysiological benefits provided to an impaired system by acoustic cue enhancements typical of ‘clear’ speech (Picheny et al., 1986) in order to gain a deeper understanding of how processing deficits can be overcome by the speech signal. Research has shown that speakers naturally alter the acoustic characteristics of their speech from a ‘conversational’ to a ‘clear’ speaking style when the listener is known to have speech perception difficulties. The acoustic characteristics of ‘conversational’ and ‘clear’ speech have been well described (Picheny et al., 1986). The perceptual benefits of ‘clear’ speech have also been established (Picheny et al., 1985, Gordon-Salant, 1986, Hazan and Simpson, 1998), and some of these features have been incorporated into commercially available auditory training programs designed for LP children (Merzenich et al., 1996, Tallal et al., 1996).
Section snippets
Subjects
Subjects consisted of normal children (n=9) and children with LP (n=9). The normal group included children between the ages of 10 and 13 years (3 female, 6 male) with no reported history of learning or attention problems and scores within normal limits on standardized tests of learning and academic achievement (Woodcock and Johnson, 1977, Woodcock and Johnson, 1989, Wilkinson, 1993). The group with LP included age-matched children (two female, 7 male) diagnosed clinically with a reading-based
Behavioral perception
In the behavioral experiment, JNDs were obtained to the ‘conversational’ speech continuum in quiet and in noise and to the ‘clear’ speech continuum in noise for normal and LP children. As expected, a comparison between ‘conversational’ speech in quiet and in noise scores indicated that both groups showed more difficulty discriminating speech in noise (Wilcoxon signed ranks test: normal, T+=45, P=0.008; LP, T+=45, P=0.008). That is, a comparison of ‘conversational’ speech in noise scores between
Discussion
Taken together, the electrophysiologic and behavioral results demonstrate a difference between these normal and LP children in the neurophysiologic representation and perception of speech in noise. Specifically, group differences arose in the JNDs of ‘conversational’ speech in noise, the magnitude of the spectral content in the FFR, the strength of the stimulus-to-response correlation coefficients reflected in the brain-stem response, the latency of wave V in the ABR and the amplitude of
Acknowledgements
We would like to acknowledge T. McGee, D. Koch, C. King, the children, and their families for their valuable contributions. This work was supported by NIH-NIDCD-DC01510.
References (70)
- et al.
The 500 Hz frequency-following potential in kangaroo rat: an evaluation with noise masking
Electroenceph clin Neurophysiol
(1980) Two-channel brain-stem frequency-following responses to pure tone and missing fundamental stimuli
Electroenceph clin Neurophysiol
(1994)- et al.
Speech-evoked brainstem frequency-following responses during verbal transformations due to word repetition
Electroenceph clin Neurophysiol
(1997) - et al.
Neural temporal coding of low pitch. I. Human frequency-following responses to complex tones
Hear Res
(1987) - et al.
The effect of cue-enhancement on the intelligibility of nonsense word and sentence materials presented in noise
Speech Commun
(1998) - et al.
Nonlinear effects of noise on phase-locked cochlear-nerve responses to sinusoidal stimuli
Hear Res
(1995) - et al.
Receptor and neural response to auditory masking of low frequency tones
Electroenceph clin Neurophysiol
(1972) - et al.
Laboratory note. Scalp-recorded early responses in man to frequencies in the speech range
Electroenceph clin Neurophysiol
(1973) - et al.
Evaluation of frequency-following potentials in man: masking and clinical studies
Electroenceph clin Neurophysiol
(1978) - et al.
Far-field recorded frequency-following responses: evidence for the locus of brainstem sources
Electroenceph clin Neurophysiol
(1975)
Sources of frequency following responses (FFR) in man
Electroenceph clin Neurophysiol Suppl
Components of the frequency-following potential in man
Electroenceph clin Neurophysiol
Developmental aphasia: rate of auditory processing and selective impairment of consonant perception
Neuropsychologia
Human short-latency auditory responses obtained by cross-correlation
Electroenceph clin Neurophysiol
Frequency-following (microphonic-like) neural responses evoked by sound
Electroenceph clin Neurophysiol
Listening in on the brain (news)
Science
Assessment and management of central auditory processing disorders in the educational setting: from science to practice
Response characteristics of cochlear nucleus neurons to 500 Hz tones and noise: findings relating to frequency-following potentials
J Neurophysiol
Brainstem auditory-evoked potentials
CRC Crit Rev Biomed Eng
Effects of lengthened formant transition duration on discrimination and neural representation of synthetic CV syllables by normal and learning-disabled children
J Acoust Soc Am
The effect of broadband noise on the human brainstem auditory evoked response. I. Rate and intensity effects
J Acoust Soc Am
Interactive software for evaluating auditory discrimination
Ear Hear
Central auditory processing disorders: new perspectives
Speech-evoked neurophysiologic responses in children with learning problems: development and behavioral correlates of perception
Ear Hear
Neurophysiologic representation of clear speech in noise
Assoc Res Otolarygol
Speech coding in the auditory nerve. V. Vowels in background noise
J Acoust Soc Am
Speech perception deficits in poor readers: auditory processing or phonological coding?
J Learn Disabil
Short-latency auditory responses obtained by cross correlation
J Acoust Soc Am
Noise enhancement of information transfer in crayfish mechanoreceptors by stochastic resonance
Nature
The correlative brain: theory and experiment in neural interaction. Studies of brain function
Performance of children aged 9 to 17 on a test of speech intelligibility in noise using sentence material with controlled word predictability
J Acoust Soc Am
Fine-grained auditory discrimination in normal children and children with language-learning problems
J Speech Hear Res
Intelligible speech encoded in the human brain stem frequency-following response
NeuroReport
Brain stem frequency-following response to dichotic vowels during attention
NeuroReport
Recognition of natural and time/intensity altered CVs by young and elderly subjects with normal hearing
J Acoust Soc Am
Cited by (229)
Children with developmental language disorder: a frequency following response in the noise study
2022, Brazilian Journal of OtorhinolaryngologyCentral auditory system responses from children while listening to speech in noise
2021, Hearing ResearchClick-evoked and speech-evoked auditory brainstem responses from individuals with multiple sclerosis
2021, Neuroscience Letters