Evidence map›Paper›PMID 32936717›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2020

Electrophysiological Evidence of Early Cortical Sensitivity to Human Conspecific Mimic Voice as a Distinct Category of Natural Sound.

William J Talkington, Jeremy Donai, Alexandra S Kadner, Molly L Layne, Andrew Forino, Sijin Wen, Si Gao, Margeaux M Gray, Alexandria J Ashraf, Gabriela N Valencia and 9 more

Open access · greenAbstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 56% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 1 institution in 1 country.

William J TalkingtonDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Jeremy DonaiDepartment of Communication Sciences and Disorders, College of Education and Human Services, West Virginia University, Morgantown.
Alexandra S KadnerDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Molly L LayneDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Andrew ForinoDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Sijin WenDepartment of Biostatistics, West Virginia University, Morgantown.
Si GaoDepartment of Biostatistics, West Virginia University, Morgantown.
Margeaux M GrayDepartment of Biology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Alexandria J AshrafDepartment of Biology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Gabriela N ValenciaDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Brandon D SmithDepartment of Biology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Stephanie K KhooDepartment of Biology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Stephen J GrayDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Norman LassDepartment of Communication Sciences and Disorders, College of Education and Human Services, West Virginia University, Morgantown.
Julie A Brefczynski-LewisDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
Susannah EngdahlDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
David GrahamDepartment of Computer Science and Electrical Engineering, West Virginia University, Morgantown.
Chris A FrumDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
James W LewisDepartment of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown.
West Virginia University · US

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Sally Lynn Hodder · 2012 to 2026
$81.0M
WV INBRE: The Inhibitor of Growth Family Member 4 (ING4) inhibits L-Type Amino Acid Transporter 1 (LAT1) expression to suppress Breast CancerP20GM103434 · NIGMS · MARSHALL UNIVERSITY · PI GARY O RANKIN · 2012 to 2026
$61.1M
COBRE Transitional Center in NeuroscienceP30GM103503 · NIGMS · WEST VIRGINIA UNIVERSITY · PI SPIROU, GEORGE A · 2012 to 2014
$3.2M
NIGMS NIH HHS P20 GM103434NIGMS NIH HHS P30 GM103503NIGMS NIH HHS U54 GM104942
6 · The paper itself

Abstract

Purpose From an anthropological perspective of hominin communication, the human auditory system likely evolved to enable special sensitivity to sounds produced by the vocal tracts of human conspecifics whether attended or passively heard. While numerous electrophysiological studies have used stereotypical human-produced verbal (speech voice and singing voice) and nonverbal vocalizations to identify human voice-sensitive responses, controversy remains as to when (and where) processing of acoustic signal attributes characteristic of "human voiceness" per se initiate in the brain. Method To explore this, we used animal vocalizations and human-mimicked versions of those calls ("mimic voice") to examine late auditory evoked potential responses in humans. Results Here, we revealed an N1b component (96-120 ms poststimulus) during a nonattending listening condition showing significantly greater magnitude in response to mimics, beginning as early as primary auditory cortices, preceding the time window reported in previous studies that revealed species-specific vocalization processing initiating in the range of 147-219 ms. During a sound discrimination task, a P600 (500-700 ms poststimulus) component showed specificity for accurate discrimination of human mimic voice. Distinct acoustic signal attributes and features of the stimuli were used in a classifier model, which could distinguish most human from animal voice comparably to behavioral data-though none of these single features could adequately distinguish human voiceness. Conclusions These results provide novel ideas for algorithms used in neuromimetic hearing aids, as well as direct electrophysiological support for a neurocognitive model of natural sound processing that informs both neurodevelopmental and anthropological models regarding the establishment of auditory communication systems in humans. Supplemental Material https://doi.org/10.23641/asha.12903839.

Indexed as

Auditory CortexVoiceAcoustic StimulationAnimalsAuditory PerceptionEvoked Potentials, AuditoryHumans

Identifiers

PMID32936717
PMCPMC8060013
OpenAlexW3084874991

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.