Evidence map›Paper›PMID 37121375›Full record

ArticleNeuroImage2023

The integration of continuous audio and visual speech in a cocktail-party environment depends on attention.

Farhin Ahmed, Aaron R Nidiffer, Aisling E O'Sullivan, Nathaniel J Zuk, Edmund C Lalor

Abstract read
In one paragraph

Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

15 citing papers in PubMed.

  1. Trial
  2. Top-Down Attention Modulates Phase Effects on Audio-Tactile Processing.Annals of the New York Academy of Sciences · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Primitive audiovisual integration of speech.Attention, perception & psychophysics · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Attention Drives Visual Processing and Audiovisual Integration During Multimodal Communication.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  11. Article
  12. Dissociable Neural Correlates of Multisensory Coherence and Selective Attention.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  13. Article
  14. Article
  15. 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

5 authors.

Farhin AhmedDepartment of Biomedical Engineering, Department of Neuroscience, and Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY 14627, USA.
Aaron R NidifferDepartment of Biomedical Engineering, Department of Neuroscience, and Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY 14627, USA.
Aisling E O'SullivanDepartment of Biomedical Engineering, Department of Neuroscience, and Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY 14627, USA; School of Engineering, Trinity Centre for Biomedical Engineering, and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland.
Nathaniel J ZukEdmond & Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.
Edmund C LalorDepartment of Biomedical Engineering, Department of Neuroscience, and Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY 14627, USA; School of Engineering, Trinity Centre for Biomedical Engineering, and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland. Electronic address: Edmund_Lalor@urmc.rochester.edu.

Funding

Natural audiovisual speech encoding in the early stages of the human cortical hierarchyR01DC016297 · NIDCD · UNIVERSITY OF ROCHESTER · PI Matthew William Geoffrey Dye, Edmund Lalor · 2018 to 2026
$2.9M
NIDCD NIH HHS R01 DC016297
6 · The paper itself

Abstract

In noisy environments, our ability to understand speech benefits greatly from seeing the speaker's face. This is attributed to the brain's ability to integrate audio and visual information, a process known as multisensory integration. In addition, selective attention plays an enormous role in what we understand, the so-called cocktail-party phenomenon. But how attention and multisensory integration interact remains incompletely understood, particularly in the case of natural, continuous speech. Here, we addressed this issue by analyzing EEG data recorded from participants who undertook a multisensory cocktail-party task using natural speech. To assess multisensory integration, we modeled the EEG responses to the speech in two ways. The first assumed that audiovisual speech processing is simply a linear combination of audio speech processing and visual speech processing (i.e., an A + V model), while the second allows for the possibility of audiovisual interactions (i.e., an AV model). Applying these models to the data revealed that EEG responses to attended audiovisual speech were better explained by an AV model, providing evidence for multisensory integration. In contrast, unattended audiovisual speech responses were best captured using an A + V model, suggesting that multisensory integration is suppressed for unattended speech. Follow up analyses revealed some limited evidence for early multisensory integration of unattended AV speech, with no integration occurring at later levels of processing. We take these findings as evidence that the integration of natural audio and visual speech occurs at multiple levels of processing in the brain, each of which can be differentially affected by attention.

Indexed as

Speech PerceptionAcoustic StimulationAttentionAuditory PerceptionBrainHumansSpeechVisual PerceptionCocktail partyHierarchical processingMultisensory integrationSpeech

Identifiers

PMID37121375
PMCPMC12956257

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.