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Effects of consonant-vowel transitions in speech stimuli on cortical auditory evoked potentials in adults.

Doellinger M, Burger M, Hoppe U, Bosco E, Eysholdt U - Open Neurol J (2011)

Bottom Line: Significant hemispheric asymmetries were found for speech but not in noise evoked potentials.The difference signals between the AEPs to speech and corresponding noise stimuli revealed a significant negative component, which correlated with the VOT.The correlation with the VOT indicates that the significant component in the difference signal reflects the perception of the acoustic change within the consonant-vowel transition.

View Article: PubMed Central - PubMed

Affiliation: Department of Phoniatrics and Pediatric Audiology, University Hospital Erlangen, Bohlenplatz 21, 91054 Erlangen, Germany.

ABSTRACT
We examined the neural activation to consonant-vowel transitions by cortical auditory evoked potentials (AEPs). The aim was to show whether cortical response patterns to speech stimuli contain components due to one of the temporal features, the voice-onset time (VOT). In seven normal-hearing adults, the cortical responses to four different monosyllabic words were opposed to the cortical responses to noise stimuli with the same temporal envelope as the speech stimuli. Significant hemispheric asymmetries were found for speech but not in noise evoked potentials. The difference signals between the AEPs to speech and corresponding noise stimuli revealed a significant negative component, which correlated with the VOT. The hemispheric asymmetries can be referred to rapid spectral changes. The correlation with the VOT indicates that the significant component in the difference signal reflects the perception of the acoustic change within the consonant-vowel transition. Thus, at the level of automatic processing, the characteristics of speech evoked potentials appear to be determined primarily by temporal aspects of the eliciting stimuli.

No MeSH data available.


Box and whisker plot of VOTs of the diverse speech stimuli against the latencies of the negative components in the difference signal of the cortical responses. Dashed lines within the boxes display the median, the edges of the boxes display the quartiles. Whiskers indicate maximal and minimal latencies unless outliers ‘+’ occur (whiskers span 1.5 times the inter-quartile range).
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Figure 7: Box and whisker plot of VOTs of the diverse speech stimuli against the latencies of the negative components in the difference signal of the cortical responses. Dashed lines within the boxes display the median, the edges of the boxes display the quartiles. Whiskers indicate maximal and minimal latencies unless outliers ‘+’ occur (whiskers span 1.5 times the inter-quartile range).

Mentions: Fig. (6) shows the grand mean AEP waveforms of the speech (dashed lines) and noise stimuli (dotted lines) as well as the difference signals (solid lines) speech – noise. In the difference signal, a negative component could be observed in a latency range of approximately 140 ± 15 ms. For each speech-noise pair, one-tailed t-tests (subjects x channels) showed that the occurring negative component was significantly smaller than zero. Latencies and amplitudes of this negative component are given in Table 5. Ei elicits the smallest latency, latencies in response to Bett and Dieb are similar and Pult elicits the longest latency. Fig. (7) shows the VOT of the four speech stimuli plotted against the peak latency of the negative component in the difference signal. A prominent correlation of VOT and peak latency is observable. Spearman rank correlation analysis revealed that the latencies were significant positively correlated with VOT (r = 0.66, p < 0.01).


Effects of consonant-vowel transitions in speech stimuli on cortical auditory evoked potentials in adults.

Doellinger M, Burger M, Hoppe U, Bosco E, Eysholdt U - Open Neurol J (2011)

Box and whisker plot of VOTs of the diverse speech stimuli against the latencies of the negative components in the difference signal of the cortical responses. Dashed lines within the boxes display the median, the edges of the boxes display the quartiles. Whiskers indicate maximal and minimal latencies unless outliers ‘+’ occur (whiskers span 1.5 times the inter-quartile range).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3106335&req=5

Figure 7: Box and whisker plot of VOTs of the diverse speech stimuli against the latencies of the negative components in the difference signal of the cortical responses. Dashed lines within the boxes display the median, the edges of the boxes display the quartiles. Whiskers indicate maximal and minimal latencies unless outliers ‘+’ occur (whiskers span 1.5 times the inter-quartile range).
Mentions: Fig. (6) shows the grand mean AEP waveforms of the speech (dashed lines) and noise stimuli (dotted lines) as well as the difference signals (solid lines) speech – noise. In the difference signal, a negative component could be observed in a latency range of approximately 140 ± 15 ms. For each speech-noise pair, one-tailed t-tests (subjects x channels) showed that the occurring negative component was significantly smaller than zero. Latencies and amplitudes of this negative component are given in Table 5. Ei elicits the smallest latency, latencies in response to Bett and Dieb are similar and Pult elicits the longest latency. Fig. (7) shows the VOT of the four speech stimuli plotted against the peak latency of the negative component in the difference signal. A prominent correlation of VOT and peak latency is observable. Spearman rank correlation analysis revealed that the latencies were significant positively correlated with VOT (r = 0.66, p < 0.01).

Bottom Line: Significant hemispheric asymmetries were found for speech but not in noise evoked potentials.The difference signals between the AEPs to speech and corresponding noise stimuli revealed a significant negative component, which correlated with the VOT.The correlation with the VOT indicates that the significant component in the difference signal reflects the perception of the acoustic change within the consonant-vowel transition.

View Article: PubMed Central - PubMed

Affiliation: Department of Phoniatrics and Pediatric Audiology, University Hospital Erlangen, Bohlenplatz 21, 91054 Erlangen, Germany.

ABSTRACT
We examined the neural activation to consonant-vowel transitions by cortical auditory evoked potentials (AEPs). The aim was to show whether cortical response patterns to speech stimuli contain components due to one of the temporal features, the voice-onset time (VOT). In seven normal-hearing adults, the cortical responses to four different monosyllabic words were opposed to the cortical responses to noise stimuli with the same temporal envelope as the speech stimuli. Significant hemispheric asymmetries were found for speech but not in noise evoked potentials. The difference signals between the AEPs to speech and corresponding noise stimuli revealed a significant negative component, which correlated with the VOT. The hemispheric asymmetries can be referred to rapid spectral changes. The correlation with the VOT indicates that the significant component in the difference signal reflects the perception of the acoustic change within the consonant-vowel transition. Thus, at the level of automatic processing, the characteristics of speech evoked potentials appear to be determined primarily by temporal aspects of the eliciting stimuli.

No MeSH data available.