Editorial: Neural Tracking: Closing the Gap Between Neurophysiology and Translational Medicine

Liberto, Giovanni M. Di; Hjortkjær, Jens; Mesgarani, Nima

doi:10.3389/fnins.2022.872600

Cited by 13 publications

(9 citation statements)

References 50 publications

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“…As such, they could serve as critical neural read-outs in novel brain–computer interfaces such as neurally steered hearing aids ( Van Eyndhoven et al, 2017 ; Ceolini et al, 2020 ; O’Sullivan et al, 2017 ). At the same time, however, their non-stationarity over time limits their potential as translational targets for diagnosis and therapeutic intervention ( Panela et al, 2024 ; Gillis et al, 2021 ; Di Liberto et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan

Tune,

Obleser

2024

eLife

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Preserved communication abilities promote healthy aging. To this end, the age-typical loss of sensory acuity might in part be compensated for by an individual’s preserved attentional neural filtering. Is such a compensatory brain–behaviour link longitudinally stable? Can it predict individual change in listening behaviour? We here show that individual listening behaviour and neural filtering ability follow largely independent developmental trajectories modelling electroencephalographic and behavioural data of N=105 aging individuals (39–82 yrs). First, despite the expected decline in sensory acuity, listening-task performance proved remarkably stable over 2 years. Second, neural filtering and behaviour were correlated only within each separate measurement (T1, T2). Longitudinally, however, our results raise caution on attention-guided neural filtering metrics as predictors of individual trajectories in listening behaviour: Neither neural filtering at T1 nor its T1–T2 change could predict individual two-year behavioural change, under a combination of modelling strategies.

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Section: Discussionmentioning

confidence: 99%

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan

Tune,

Obleser

2024

eLife

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“…As such, they could serve as critical neural read-outs in novel brain-computer interfaces such as neurally-steered hearing aids [53][54][55] . At the same time, however, their non-stationarity over time limits their potential as translational targets for diagnosis and therapeutic intervention 45,56,57 .…”

Section: Neural Filtering Fidelity As a Trait-like Neural Marker Of I...mentioning

confidence: 99%

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult life span

Tune,

Obleser

2023

Preprint

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Preserved communication abilities promote healthy aging. To this end, the age-typical loss of sensory acuity might in part be compensated for by an individual's preserved attentional neural filtering. Is such a compensatory brain-behaviour link longitudinally stable? Can it predict individual change in listening behaviour? We here show that individual listening behaviour and neural filtering ability follow largely independent developmental trajectories modelling electroencephalographic and behavioural data of N=105 aging individuals (39-82 yrs). First, despite the expected decline in sensory acuity, listening-task performance proved remarkably stable over 2 years. Second, neural filtering and behaviour were correlated only within each separate measurement (T1, T2). Longitudinally, however, our results raise caution on attention-guided neural filtering metrics as predictors of individual trajectories in listening behaviour: Neither neural filtering at T1 nor its T1-T2 change could predict individual two-year behavioural change, under a combination of modelling strategies.

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“…More importantly, when listening to speech, large-scale theta-band cortical activity measured by MEG and EEG is more strongly driven by the speech envelope (Ding and Simon, 2012;Lalor and Foxe, 2010) than phonemic and lexical features (Brodbeck et al, 2018;Daube et al, 2019). Such theta-band envelope-tracking response is also often interpreted as a neural marker for the syllable processing (Ding et al, 2016;Doelling et al, 2014) and is widely employed to probe the neural mechanisms underlying the speech encoding (Brodbeck and Simon, 2020;Ding and Simon, 2014) and to characterize the speech processing in special populations (Di Liberto et al, 2022;Palana et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Acoustic Correlates of the Syllabic Rhythm of Speech: Modulation Spectrum or Local Features of the Temporal Envelope

Zhang¹,

Zou

Ding

2022

Preprint

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The speech envelope is considered as a major acoustic correlate of the syllable rhythm since the peak frequency in the speech modulation spectrum matches the mean syllable rate. Nevertheless, it has not been quantified whether the peak modulation frequency can track the syllable rate of individual utterances and how much variance of the speech envelope can be explained by the syllable rhythm. Here, we address these problems by analyzing large speech corpora (>1000 hours of recording of multiple languages) using advanced sequence-to-sequence modeling. It is found that, only when averaged over minutes of speech recordings, the peak modulation frequency of speech reliably correlates with the syllable rate of a speaker. In contrast, the phase-locking between speech envelope and syllable onsets is robustly observed within a few seconds of recordings. Based on speaker-independent linear and nonlinear models, the timing of syllable onsets explains about 13% and 46% variance of the speech envelope, respectively. These results demonstrate that local temporal features in the speech envelope precisely encodes the syllable onsets but the modulation spectrum is not always dominated by the syllable rhythm.

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Editorial: Neural Tracking: Closing the Gap Between Neurophysiology and Translational Medicine

Cited by 13 publications

References 50 publications

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult life span

Acoustic Correlates of the Syllabic Rhythm of Speech: Modulation Spectrum or Local Features of the Temporal Envelope

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