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Updated: Aug 13, 2026
08:45
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Cortical speech-in-noise processing reflects subcortical syllable encoding and lexical attention
Subong Kim1, Susan Arzac1, Natalie Dokic1
1Department of Communication Sciences and Disorders, Montclair State University, Montclair, NJ, USA.
Hearing Research
|August 11, 2026
Summary
Individual differences in speech-in-noise perception are linked to how the brain processes sound and attention. Neural signal-to-noise ratio (SNR) reflects both sensory encoding and attention, impacting speech understanding.
Area of Science:
- Neuroscience
- Auditory Neuroscience
- Cognitive Neuroscience
Background:
- Individual variability exists in speech-in-noise (SPIN) performance despite similar hearing sensitivity.
- This variability may arise from differences in peripheral sensory processing and top-down attentional control.
- Cortical speech representation, particularly neural signal-to-noise ratio (SNR), is a potential marker for these individual differences.
Purpose of the Study:
- To investigate how subcortical speech-syllable encoding and lexical attention influence cortical speech-in-noise representation.
- To determine the relationship between neural SNR, behavioral SPIN performance, and underlying sensory and attentional mechanisms.
- To elucidate the combined contributions of bottom-up and top-down processes to cortical SPIN processing.
Main Methods:
- Measured neural signal-to-noise ratio (SNR) using auditory-evoked responses to speech and noise onsets.
- Assessed subcortical speech-syllable encoding fidelity.
- Evaluated lexical attentional performance in participants.
- Correlated neural SNR with behavioral SPIN performance across different acoustic difficulties.
Main Results:
- Neural SNR significantly correlated with behavioral SPIN performance in moderate-difficulty conditions.
- Subcortical syllable encoding and lexical attention independently predicted neural SNR.
- A shared, partially overlapped contribution from sensory, attentional, and cortical measures was observed in behavioral performance.
Conclusions:
- Individual neural SNR is a behaviorally relevant cortical representation of speech-in-noise perception.
- Both bottom-up sensory encoding (subcortical syllable processing) and top-down attention (lexical attention) contribute to neural SNR.
- Understanding these converging mechanisms is crucial for explaining individual differences in speech-in-noise understanding.
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