Effects of Task Demands on Neural Correlates of Acoustic and Semantic Processing in Challenging Listening Conditions

Semantic processing in children with Cochlear Implants: A review of current N400 studies and recommendations for future research

Deaf and hard of hearing children with cochlear implants (CI) often display impaired spoken language skills. While a large number of studies investigated brain responses to sounds in this population, relatively few focused on semantic processing. Here we summarize and discuss findings in four studies of the N400, a cortical response that reflects semantic processing, in children with CI. A study with auditory target stimuli found N400 effects at delayed latencies at 12 months after implantation, but at 18 and 24 months after implantation effects had typical latencies. In studies with visual target stimuli N400 effects were larger than or similar to controls in children with CI, despite lower semantic abilities. We propose that in children with CI, the observed large N400 effect reflects a stronger reliance on top-down predictions, relative to bottom-up language processing. Recent behavioral studies of children and adults with CI suggest that top-down processing is a common compensatory strategy, but with distinct limitations such as being effortful. A majority of the studies have small sample sizes (N < 20), and only responses to image targets were studied repeatedly in similar paradigms. This precludes strong conclusions. We give suggestions for future research and ways to overcome the scarcity of participants, including extending research to children with conventional hearing aids, an understudied group.

The effects of speech masking on neural tracking of acoustic and semantic features of natural speech

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.

Prediction of Speech Intelligibility by Means of EEG Responses to Sentences in Noise

Objective

Understanding speech in noisy conditions is challenging even for people with mild hearing loss, and intelligibility for an individual person is usually evaluated by using several subjective test methods. In the last few years, a method has been developed to determine a temporal response function (TRF) between speech envelope and simultaneous electroencephalographic (EEG) measurements. By using this TRF it is possible to predict the EEG signal for any speech signal. Recent studies have suggested that the accuracy of this prediction varies with the level of noise added to the speech signal and can predict objectively the individual speech intelligibility. Here we assess the variations of the TRF itself when it is calculated for measurements with different signal-to-noise ratios and apply these variations to predict speech intelligibility.

Methods

For 18 normal hearing subjects the individual threshold of 50% speech intelligibility was determined by using a speech in noise test. Additionally, subjects listened passively to speech material of the speech in noise test at different signal-to-noise ratios close to individual threshold of 50% speech intelligibility while an EEG was recorded. Afterwards the shape of TRFs for each signal-to-noise ratio and subject were compared with the derived intelligibility.

Results

The strongest effect of variations in stimulus signal-to-noise ratio on the TRF shape occurred close to 100 ms after the stimulus presentation, and was located in the left central scalp region. The investigated variations in TRF morphology showed a strong correlation with speech intelligibility, and we were able to predict the individual threshold of 50% speech intelligibility with a mean deviation of less then 1.5 dB.

Conclusion

The intelligibility of speech in noise can be predicted by analyzing the shape of the TRF derived from different stimulus signal-to-noise ratios. Because TRFs are interpretable, in a manner similar to auditory evoked potentials, this method offers new options for clinical diagnostics.

On the Role of Neural Oscillations Across Timescales in Speech and Music Processing

This mini review is aimed at a clinician-scientist seeking to understand the role of oscillations in neural processing and their functional relevance in speech and music perception. We present an overview of neural oscillations, methods used to study them, and their functional relevance with respect to music processing, aging, hearing loss, and disorders affecting speech and language. We first review the oscillatory frequency bands and their associations with speech and music processing. Next we describe commonly used metrics for quantifying neural oscillations, briefly touching upon the still-debated mechanisms underpinning oscillatory alignment. Following this, we highlight key findings from research on neural oscillations in speech and music perception, as well as contributions of this work to our understanding of disordered perception in clinical populations. Finally, we conclude with a look toward the future of oscillatory research in speech and music perception, including promising methods and potential avenues for future work. We note that the intention of this mini review is not to systematically review all literature on cortical tracking of speech and music. Rather, we seek to provide the clinician-scientist with foundational information that can be used to evaluate and design research studies targeting the functional role of oscillations in speech and music processing in typical and clinical populations.