Evidence map›Paper›PMID 42779782›Full record

ArticlebioRxiv : the preprint server for biology2026

Voice and linguistic features support early attentional filtering of irrelevant stimuli.

Sahil Luthra, Eric Parker, Marysia Brown, Gidey Gezae, Hee So Kim, Wusheng Liang, Abigail Noyce, Barbara G Shinn-Cunningham

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Sahil LuthraStony Brook University, Stony Brook, NY, USA 11790.ORCID 0000-0002-3517-2609
Eric ParkerCarnegie Mellon University, Pittsburgh, PA, USA 15213.ORCID 0009-0009-7744-1166
Marysia BrownUniversity of Pittsburgh, Pittsburgh, PA, USA 15260.
Gidey GezaePennsylvania State University, University Park, PA, USA 16802.ORCID 0000-0001-5566-7951
Hee So KimCarnegie Mellon University, Pittsburgh, PA, USA 15213.ORCID 0009-0002-4532-4618
Wusheng LiangCarnegie Mellon University, Pittsburgh, PA, USA 15213.ORCID 0000-0003-0264-8276
Abigail NoyceCarnegie Mellon University, Pittsburgh, PA, USA 15213.ORCID 0000-0002-4339-4113
Barbara G Shinn-CunninghamCarnegie Mellon University, Pittsburgh, PA, USA 15213.ORCID 0000-0002-5096-5914

Funding

Mechanisms of auditory selective attention for speech and non-speech stimuliF32DC020625 · NIDCD · CARNEGIE-MELLON UNIVERSITY · PI LUTHRA, SAHIL · 2022 to 2025
$197k
NIDCD NIH HHS F32 DC020625
6 · The paper itself

Abstract

In cocktail party-type environments, listeners must segregate simultaneous acoustic sources and select one for processing. Behavioral studies have established that both low-level voice differences (e.g., pitch) and high-level linguistic differences (e.g., word content) aid these processes. Electroencephalography (EEG) studies have demonstrated that the brain filters voices based on low-level features early in sensory processing, but it is unclear whether linguistic differences also support early filtering. In this EEG study, listeners attended to a lateralized auditory stream of target syllables while ignoring distractor stimuli from the opposite hemifield. In contrast to previous auditory attention studies, target stimuli were always attended and statistically identical across conditions; instead, we manipulated the distractors. Specifically, we manipulated whether targets and distractors were spoken in the same voice or different voices, as well as whether they were composed of the same or different linguistic content. Critically, distractors were temporally offset from targets, enabling an investigation of whether acoustically matched, always attended target stimuli are differentially encoded as a function of surrounding context. Differences in either voice or linguistic features supported target recall: Recall was poor only when both streams were in the same voice and had similar linguistic content. However, voice and linguistic features had independent, additive effects on neural processing. Specifically, target dissimilarity in acoustics and linguistic content both contributed to more robust, larger-magnitude target-evoked EEG responses. Overall, results demonstrate that both linguistic dissimilarity and low-level acoustic dissimilarity improve early attentional filtering of distractors in multi-source acoustic scenes.

Indexed as

AttentionEEGERPsspeechtalker

Identifiers

PMID42779782
PMCPMC13596454

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.