Biology subjects

MacIntyre, A. D.

Publications and source records attributed to MacIntyre, A. D..

3 recordsLinked to original sources

bioRxiv2026

Flexible neural encoding predicts the comprehension of degraded speech

How listeners track a variable and continuous acoustic speech signal and parse it into meaningful linguistic representations is a question central to cognitive neuroscience. Moreover, the resilience of this process to acoustic signal degradation is not fully understood. The current study consists of a listening task wherein participants (n = 38) were presented with a naturalistic story whilst undergoing continuous electroencephalography (EEG). Critically, we manipulated access to speech information over two independent dimensions: Spectral clarity, which ranged from unprocessed to severely spectrally degraded; and language, which was either English, spoken by the participants, or Dutch, an incomprehensible language that is closely related to English. All stimuli were produced by the same bilingual speaker. We applied banded regression to model the neural response to a set of acoustic and linguistically derived features. We found that there is no single speech feature for which neural encoding reliably predicted speech understanding in individual listeners or conditions. Yet, differences in feature weights between experimental conditions can be combined into a composite score that strongly predicted individual subjective comprehension of spectrally degraded but linguistically accessible speech in data from held-out participant. Hence, the manner in which neural encoding flexibly adapts to listening context is associated with advantageous perceptual strategies for degraded speech. These findings underscore the complex interplay between low- and high-level features during speech listening and illustrate inter-condition differences in the neural encoding of these properties. Our results highlight natural variation within and between individuals in the encoding of acoustic and linguistic features which provides a potential pathway towards individualised assessment of clinical populations.

neuroscience↗

bioRxiv2025

Robust Decoding of Speech Acoustics from EEG: Going Beyond the Amplitude Envelope

ObjectiveDuring speech perception, properties of the acoustic stimulus can be reconstructed from the listeners brain using methods such as electroencephalography (EEG). Most studies employ the amplitude envelope as a target for decoding; however, speech acoustics can be characterised on multiple dimensions, including as spectral descriptors. The current study assesses how robustly an extended acoustic feature set can be decoded from EEG under varying levels of intelligibility and acoustic clarity. ApproachAnalysis was conducted using EEG from 38 young adults who heard intelligible and non-intelligible speech that was either unprocessed or spectrally degraded using vocoding. We extracted a set of acoustic features which, alongside the envelope, characterised instantaneous properties of the speech spectrum (e.g., spectral slope) or spectral change over time (e.g., spectral flux). We establish the robustness of feature decoding by employing multiple model architectures and, in the case of linear decoders, by standardising decoding accuracy (Pearsons r) using randomly permuted surrogate data. Main resultsLinear models yielded the highest r relative to non-linear models. However, the separate decoder architectures produced a similar pattern of results across features and experimental conditions. After converting r values to Z-scores scaled by random data, we observed substantive differences in the noise floor between features. Decoding accuracy significantly varies by spectral degradation and speech intelligibility for some features, but such differences are reduced in the most robustly decoded features. This suggests acoustic feature reconstruction is primarily driven by generalised auditory processing. SignificanceOur results demonstrate that linear decoders perform comparably to non-linear decoders in capturing the EEG response to speech acoustic properties beyond the amplitude envelope, with the reconstructive accuracy of some features also associated with understanding and spectral clarity. This sheds light on how sound properties are differentially represented by the brain and shows potential for clinical applications moving forward.

neuroscience↗

bioRxiv2024

Neural decoding of the speech envelope: Effects of intelligibility and spectral degradation

During continuous speech perception, endogenous neural activity becomes time-locked to acoustic stimulus features, such as the speech amplitude envelope. This speech-brain coupling can be decoded using non-invasive brain imaging techniques, including electroencephalography (EEG). Neural decoding may provide clinical use as an objective measure of stimulus encoding by the brain - for example during cochlear implant (CI) listening, wherein the speech signal is severely spectrally degraded. Yet, interplay between acoustic and linguistic factors may lead to top-down modulation of perception, thereby complicating audiological applications. To address this ambiguity, we assess neural decoding of the speech envelope under spectral degradation with EEG in acoustically hearing listeners (n = 38; 18-35 years old) using vocoded speech. We dissociate sensory encoding from higher-order processing by employing intelligible (English) and non-intelligible (Dutch) stimuli, with auditory attention sustained using a repeated-phrase detection task. Subject-specific and group decoders were trained to reconstruct the speech envelope from held-out EEG data, with decoder significance determined via random permutation testing. Whereas speech envelope reconstruction did not vary by spectral resolution, intelligible speech was associated with better decoding accuracy in general. Results were similar across subject-specific and group analyses, with less consistent effects of spectral degradation in group decoding. Permutation tests revealed possible differences in decoder statistical significance by experimental condition. In general, while robust neural decoding was observed at the individual and group level, variability within participants would most likely prevent the clinical use of such a measure to differentiate levels of spectral degradation and intelligibility on an individual basis.

neuroscience↗