ArticleHearing research2019
Differential responses to spectrally degraded speech within human auditory cortex: An intracranial electrophysiology study.
Article in Hearing research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
- Neural Dynamics of the Processing of Speech Features: Evidence for a Progression of Features from Acoustic to Sentential Processing.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Neural Dynamics of the Processing of Speech Features: Evidence for a Progression of Features from Acoustic to Sentential Processing.bioRxiv : the preprint server for biology · 2024Article
- Article
- Intracranial electrophysiology of spectrally degraded speech in the human cortex.Frontiers in human neuroscience · 2023Article
- Article
- Speech Computations of the Human Superior Temporal Gyrus.Annual review of psychology · 2022Review
- The Precentral Gyrus Contributions to the Early Time-Course of Grapheme-to-Phoneme Conversion.Neurobiology of language (Cambridge, Mass.) · 2022Article
- Difficulties with Speech-in-Noise Perception Related to Fundamental Grouping Processes in Auditory Cortex.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Electrophysiology of the Human Superior Temporal Sulcus during Speech Processing.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Cortical responses to auditory novelty across task conditions: An intracranial electrophysiology study.Hearing research · 2021Article
- Auditory Selectivity for Spectral Contrast in Cortical Neurons and Behavior.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Article
- Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Understanding cortical processing of spectrally degraded speech in normal-hearing subjects may provide insights into how sound information is processed by cochlear implant (CI) users. This study investigated electrocorticographic (ECoG) responses to noise-vocoded speech and related these responses to behavioral performance in a phonemic identification task. Subjects were neurosurgical patients undergoing chronic invasive monitoring for medically refractory epilepsy. Stimuli were utterances /aba/ and /ada/, spectrally degraded using a noise vocoder (1-4 bands). ECoG responses were obtained from Heschl's gyrus (HG) and superior temporal gyrus (STG), and were examined within the high gamma frequency range (70-150 Hz). All subjects performed at chance accuracy with speech degraded to 1 and 2 spectral bands, and at or near ceiling for clear speech. Inter-subject variability was observed in the 3- and 4-band conditions. High gamma responses in posteromedial HG (auditory core cortex) were similar for all vocoded conditions and clear speech. A progressive preference for clear speech emerged in anterolateral segments of HG, regardless of behavioral performance. On the lateral STG, responses to all vocoded stimuli were larger in subjects with better task performance. In contrast, both behavioral and neural responses to clear speech were comparable across subjects regardless of their ability to identify degraded stimuli. Findings highlight differences in representation of spectrally degraded speech across cortical areas and their relationship to perception. The results are in agreement with prior non-invasive results. The data provide insight into the neural mechanisms associated with variability in perception of degraded speech and potentially into sources of such variability in CI users.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.