Evidence map›Paper›PMID 34239430›Full record

ArticleFrontiers in human neuroscience2021

Neurofeedback Training of Auditory Selective Attention Enhances Speech-In-Noise Perception.

Subong Kim, Caroline Emory, Inyong Choi

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

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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

14 citing papers in PubMed.

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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

3 authors.

Subong KimDepartment of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, United States.
Caroline EmoryDepartment of Communication Sciences and Disorders, University of Iowa, Iowa City, IA, United States.
Inyong ChoiDepartment of Communication Sciences and Disorders, University of Iowa, Iowa City, IA, United States.

Funding

Speech Production &LanguageP50DC000242 · NIDCD · UNIVERSITY OF IOWA · PI Inyong Choi · 1989 to 2026
$58.8M
NIDCD NIH HHS P50 DC000242
6 · The paper itself

Abstract

Selective attention enhances cortical responses to attended sensory inputs while suppressing others, which can be an effective strategy for speech-in-noise (SiN) understanding. Emerging evidence exhibits a large variance in attentional control during SiN tasks, even among normal-hearing listeners. Yet whether training can enhance the efficacy of attentional control and, if so, whether the training effects can be transferred to performance on a SiN task has not been explicitly studied. Here, we introduce a neurofeedback training paradigm designed to reinforce the attentional modulation of auditory evoked responses. Young normal-hearing adults attended one of two competing speech streams consisting of five repeating words ("up") in a straight rhythm spoken by a female speaker and four straight words ("down") spoken by a male speaker. Our electroencephalography-based attention decoder classified every single trial using a template-matching method based on pre-defined patterns of cortical auditory responses elicited by either an "up" or "down" stream. The result of decoding was provided on the screen as online feedback. After four sessions of this neurofeedback training over 4 weeks, the subjects exhibited improved attentional modulation of evoked responses to the training stimuli as well as enhanced cortical responses to target speech and better performance during a post-training SiN task. Such training effects were not found in the Placebo Group that underwent similar attention training except that feedback was given only based on behavioral accuracy. These results indicate that the neurofeedback training may reinforce the strength of attentional modulation, which likely improves SiN understanding. Our finding suggests a potential rehabilitation strategy for SiN deficits.

Indexed as

attentional modulationbrain-computer interfaceeletroencephalographyneurofeedback trainingperceptual trainingselective attentionspeech-in-noise perception

Identifiers

PMID34239430
PMCPMC8258151

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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.