Evidence map›Paper›PMID 36694007›Full record

ArticleJournal of autism and developmental disorders2024

Vocal Emotion Recognition in Autism: Behavioral Performance and Event-Related Potential (ERP) Response.

Talena C Day, Isha Malik, Sydney Boateng, Kathryn M Hauschild, Matthew D Lerner

Abstract read
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In one paragraph

Article in Journal of autism and developmental disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

5 authors.

Talena C DayPsychology Department, Stony Brook University, Stony Brook, Psychology B-354, Stony Brook, NY, 11794-2500, USA.ORCID http://orcid.org/0000-0001-5774-4738
Isha MalikPsychology Department, Stony Brook University, Stony Brook, Psychology B-354, Stony Brook, NY, 11794-2500, USA.
Sydney BoatengPsychology Department, Stony Brook University, Stony Brook, Psychology B-354, Stony Brook, NY, 11794-2500, USA.
Kathryn M HauschildFarmingdale State College, Farmingdale, NY, 11735, USA.
Matthew D LernerPsychology Department, Stony Brook University, Stony Brook, Psychology B-354, Stony Brook, NY, 11794-2500, USA. matthew.lerner@stonybrook.edu.

Funding

Optimizing Prediction of Social Deficits in Autism Spectrum DisordersR01MH110585 · NIMH · STATE UNIVERSITY NEW YORK STONY BROOK · PI LERNER, MATTHEW DANIEL · 2016 to 2020
$2.2M
NIMH NIH HHS 1R01MH110585
6 · The paper itself

Abstract

Autistic youth display difficulties in emotion recognition, yet little research has examined behavioral and neural indices of vocal emotion recognition (VER). The current study examines behavioral and event-related potential (N100, P200, Late Positive Potential [LPP]) indices of VER in autistic and non-autistic youth. Participants (N = 164) completed an emotion recognition task, the Diagnostic Analyses of Nonverbal Accuracy (DANVA-2) which included VER, during EEG recording. The LPP amplitude was larger in response to high intensity VER, and social cognition predicted VER errors. Verbal IQ, not autism, was related to VER errors. An interaction between VER intensity and social communication impairments revealed these impairments were related to larger LPP amplitudes during low intensity VER. Taken together, differences in VER may be due to higher order cognitive processes, not basic, early perception (N100, P200), and verbal cognitive abilities may underlie behavioral, yet occlude neural, differences in VER processing.

Indexed as

Autism Spectrum DisorderAutistic DisorderAdolescentElectroencephalographyEmotionsEvoked PotentialsHumansAutismEEGEmotionERPLate positive potentialLPPN100P200ProsodyRecognitionVocalVoice

Identifiers

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Registered trials

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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.