Neural coding of continuous speech in auditory cortex during monaural and dichotic listening
Nai Ding,Jonathan Z. Simon +1 more
TLDR
These findings characterize how the spectrotemporal features of speech are encoded in human auditory cortex and establish a single-trial-based paradigm to study the neural basis underlying the cocktail party phenomenon.Abstract:
The cortical representation of the acoustic features of continuous speech is the foundation of speech perception. In this study, noninvasive magnetoencephalography (MEG) recordings are obtained from human subjects actively listening to spoken narratives, in both simple and cocktail party-like auditory scenes. By modeling how acoustic features of speech are encoded in ongoing MEG activity as a spectrotemporal response function, we demonstrate that the slow temporal modulations of speech in a broad spectral region are represented bilaterally in auditory cortex by a phase-locked temporal code. For speech presented monaurally to either ear, this phase-locked response is always more faithful in the right hemisphere, but with a shorter latency in the hemisphere contralateral to the stimulated ear. When different spoken narratives are presented to each ear simultaneously (dichotic listening), the resulting cortical neural activity precisely encodes the acoustic features of both of the spoken narratives, but slightly weakened and delayed compared with the monaural response. Critically, the early sensory response to the attended speech is considerably stronger than that to the unattended speech, demonstrating top-down attentional gain control. This attentional gain is substantial even during the subjects' very first exposure to the speech mixture and therefore largely independent of knowledge of the speech content. Together, these findings characterize how the spectrotemporal features of speech are encoded in human auditory cortex and establish a single-trial-based paradigm to study the neural basis underlying the cocktail party phenomenon.read more
Citations
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Journal ArticleDOI
Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research
Michael J. Crosse,Nathaniel J. Zuk,Nathaniel J. Zuk,Giovanni M. Di Liberto,Giovanni M. Di Liberto,Aaron R. Nidiffer,Sophie Molholm,Edmund C. Lalor,Edmund C. Lalor +8 more
TL;DR: In this paper, the authors focus on experimental design, data preprocessing and stimulus feature extraction, model design, training and evaluation, and interpretation of model weights, and demonstrate how to implement each stage in MATLAB using the mTRF toolbox.
Journal ArticleDOI
Attention to natural auditory signals.
TL;DR: The role of selective attention in modulating auditory responses to complex natural stimuli in humans is reviewed, and how the current understanding can be applied to the study of selective auditory attention in the context natural signal processing at the level of single neurons and populations in animal models amenable to invasive neuroscience techniques is suggested.
Journal ArticleDOI
Machine Learning Approaches to Analyze Speech-Evoked Neurophysiological Responses
TL;DR: It is proposed that ML-based approaches can complement traditional analysis approaches to analyze neurophysiological responses to speech signals and provide a deeper understanding of natural speech and language processing using ecologically valid paradigms in both typical and clinical populations.
Posted ContentDOI
Late cortical tracking of ignored speech facilitates neural selectivity in acoustically challenging conditions
TL;DR: This work recorded and modelled the electroencephalographic response of 18 participants who attended to one of two simultaneously presented stories, while the SNR between the two talkers varied dynamically, and showed an increasing early-to-late attention-biased selectivity.
Journal ArticleDOI
The Effects of Audiovisual Inputs on Solving the Cocktail Party Problem in the Human Brain: An fMRI Study.
Yuanqing Li,Fangyi Wang,Yongbin Chen,Andrzej Cichocki,Andrzej Cichocki,Terrence J. Sejnowski +5 more
TL;DR: It is found that audiovisual inputs enhanced the neural representations of emotion features of the attended objects instead of the unattended objects, which might partially explain the benefits of audiovISual inputs for the brain to solve the cocktail party problem.
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