Preliminary Investigation of the Passively Evoked N400 as a Tool for Estimating Speech-in-Noise Thresholds

Jamison, Caroline; Aiken, Steven J.; Kiefte, Michael; Newman, Aaron J.; Bance, Manohar; Petley, Lauren

doi:10.1044/2016_aja-15-0080

Cited by 12 publications

(9 citation statements)

References 74 publications

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“…Furthermore, the effect declined in the more degraded speech as the speech became less comprehensible and less predictable. Accordingly, a similar nonlinear N400 effect was also found in a previous study manipulating 6 levels of signal to noise ratio (Jamison et al, 2016). Furthermore, lexicalsemantic processing is modulated when the spectral properties of the speech are disrupted as shown by Obleser & Kotz (2011) and Strauß et al (2013).…”

Section: Neural Speech Tracking Could Be Affected By Other Potential ...supporting

confidence: 80%

Speech intelligibility changes the temporal evolution of neural speech tracking

et al. 2023

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Section: Neural Speech Tracking Could Be Affected By Other Potential ...supporting

confidence: 80%

Speech intelligibility changes the temporal evolution of neural speech tracking

et al. 2023

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“…Furthermore, the effect declined in the more degraded speech as the speech became less comprehensible and less predictable. Accordingly, a similar nonlinear N400 effect was also found in a previous study manipulating 6 levels of signal to noise ratio (Jamison et al, 2016). Furthermore, lexical-semantic processing is modulated when the spectral properties of the speech are disrupted as shown by Obleser & Kotz (2011) and Strauß et al (2013).…”

Section: Discussionsupporting

confidence: 84%

Speech intelligibility changes the temporal evolution of neural speech tracking

Chen

Schmidt

Keitel

et al. 2022

Preprint

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Listening to speech with poor signal quality is challenging. Neural speech tracking of degraded speech has been used to advance the understanding of how brain processes and speech intelligibility are interrelated, however the temporal dynamics of neural speech tracking are not clear. In the present MEG study, we thereby exploited temporal response functions (TRFs) and generated signal-degraded speech to depict the temporal evolution of speech intelligibility modulation on neural speech tracking. In addition, we inter-related facets of neural speech tracking (e.g., speech envelope reconstruction, speech-brain coherence, and components of broadband coherence spectra) to endorse our findings in TRFs. Our TRF analysis yielded marked temporally differential effects of vocoding: reduction of intelligibility went along with large increases of early peak responses (∼50-110 ms, M50TRF), but strongly reduced responses around 175-230 ms (M200TRF). For the late responses 315-380 ms (M350TRF), the maximum response occurred for degraded speech that was still comprehensible then declined with reduced intelligibility. Furthermore, we related the TRF components to our other neural “tracking“ measures and found that M50TRF and M200TRF play a differential role in the shifting center frequency of the broadband coherence spectra. Overall, our study highlights the importance of time-resolved computation and parametrization of coherence spectra on neural speech tracking and provides a better understanding of degraded speech processing.HighlightsWe use MEG to show that speech intelligibility differentially impacts the temporal evolution of neural speech tracking.TRF responses around 200 ms show the strongest relationship with behaviour.Relating TRF effects to parameterized coherence spectra using FOOOF suggests that M50TRF and M200TRF reflect shifts in which speech features are tracked over time.

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“…The copyright holder for this preprint this version posted February 12, 2023. ; https://doi.org/10.1101/2023.02.10.527537 doi: bioRxiv preprint tracking is larger in older compared to younger adults (Presacco et al, 2016;Presacco et al, 2019), despite the fact that older adults typically comprehend speech less well. Semantic processing, as captured by the N400 response, is also sensitive to whether or not speech was understood (Broderick et al, 2018;Strauß et al, 2013;Jamison et al, 2016). We investigated whether speech intelligibility is reflected in responses either to the acoustic or the semantic features of speech by examining function fits to intelligibility data, and to acoustic and semantic tracking amplitudes and latencies, as a function of SNR (Figure 5).…”

Section: Changes In Speech Intelligibility Most Closely Resemble Chan...mentioning

confidence: 99%

The Effects of Speech Masking on Neural Tracking of Acoustic and Semantic Features of Natural Speech

Yasmin¹,

Irsik²,

Johnsrude³

et al. 2023

Preprint

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Listening environments contain background sounds that mask speech and lead to communication challenges. Sensitivity to slow acoustic fluctuations in speech can help segregate speech from background noise. Semantic context can also facilitate speech perception in noise, for example, by enabling prediction of upcoming words. However, not much is known about how different degrees of background masking affect the neural processing of acoustic and semantic features during naturalistic speech listening. In the current electroencephalography (EEG) study, participants listened to engaging, spoken stories masked at different levels of multi-talker babble to investigate how neural activity in response to acoustic and semantic features changes with acoustic challenges, and how such effects relate to speech intelligibility. The pattern of neural response amplitudes associated with both acoustic and semantic speech features across masking levels was U-shaped, such that amplitudes were largest for moderate masking levels. This U-shape may be due to increased attentional focus when speech comprehension is challenging, but manageable. The latency of the neural responses increased linearly with increasing background masking, and neural latency change associated with acoustic processing most closely mirrored the changes in speech intelligibility. Finally, tracking responses related to semantic dissimilarity remained robust until severe speech masking (-3 dB SNR). The current study reveals that neural responses to acoustic features are highly sensitive to background masking and decreasing speech intelligibility, whereas neural responses to semantic features are relatively robust, suggesting that individuals track the meaning of the story well even in moderate background sound.

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Preliminary Investigation of the Passively Evoked N400 as a Tool for Estimating Speech-in-Noise Thresholds

Cited by 12 publications

References 74 publications

Speech intelligibility changes the temporal evolution of neural speech tracking

Speech intelligibility changes the temporal evolution of neural speech tracking

Speech intelligibility changes the temporal evolution of neural speech tracking

The Effects of Speech Masking on Neural Tracking of Acoustic and Semantic Features of Natural Speech

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