Evidence map›Paper›PMID 42400657›Full record

ArticleEuropean archives of psychiatry and clinical neuroscience2026

Abnormal emotional intensity processing in individuals at clinical high risk for psychosis: evidence from event-related potentials.

Anpei Wei, Mengmeng Fan, Ting Liu, Ronghong Gao, Peipei Luan, Shixiong Sun, Lihua Kong, Xiaoyan He

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In one paragraph

Article in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

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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.

Anpei WeiAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China.
Mengmeng FanSchool of Humanities and Management Science, Wannan Medical College, Wuhu City, China.
Ting LiuAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China.
Ronghong GaoAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China.
Peipei LuanAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China.
Shixiong SunAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China.
Lihua KongAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China. 13358117679@163.com.
Xiaoyan HeAffiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi City, China. shsh1014@sina.com.

Funding

Jiangsu Shuangchuang Talent Program JSSRC 2024597Wuxi "Light of Taihu Lake" Science and Technology Research Program (Medical and Health Technology Research) Y202232015
6 · The paper itself

Abstract

backgroundSocial cognitive impairment is a key vulnerability marker for psychosis and is commonly observed in individuals at clinical high risk (CHR). However, the neurophysiological mechanisms underlying abnormalities in emotional intensity processing remain unclear. This study investigated behavioral and electrophysiological responses to emotional intensity in CHR individuals using an event-related potential (ERP) paradigm.

methodsThirty CHR participants, 29 healthy controls (HCs), and an exploratory sample of 30 individuals with schizophrenia (SCZ) completed the Emotional Intensity Recognition Task (EIRT) during high-density EEG recording. Behavioral measures included reaction time (RT) and accuracy and were analyzed across six basic emotional categories. ERP components, including N100, N170, P200, P300, and LPP, were analyzed across predefined frontal, central, parietal, and occipital regions. ERP analyses also included neutral expressions because identifiable EEG event markers were available. Associations between ERP indices, behavioral performance, and clinical symptoms were also examined.

resultsCHR individuals showed significantly slower RTs than HCs across emotional conditions, while accuracy remained comparable. ERP analyses, including neutral expressions where EEG markers were available, revealed altered modulation of emotional face processing across multiple temporal stages. Group-related effects were most consistently observed for P300 amplitude and LPP latency, suggesting atypical attentional allocation and late evaluative processing in CHR individuals. Exploratory correlation analyses suggested associations between selected ERP indices and clinical symptoms; however, these findings were not corrected for multiple comparisons and should be interpreted cautiously. Exploratory unadjusted comparisons with the SCZ group suggested group differences in selected ERP measures, but these findings should be interpreted cautiously because the SCZ group was older and was not collected concurrently with the primary CHR and HC samples.

conclusionsIndividuals at clinical high risk for psychosis exhibit slowed behavioral responses and altered ERP modulation during emotional intensity processing. These findings suggest that the EIRT-ERP paradigm may help characterize social-cognitive and neurophysiological alterations in the psychosis prodrome. Larger longitudinal studies are needed to determine whether these ERP measures have predictive value for functional outcomes or transition to psychosis.

Indexed as

Cerebral CortexEmotionsEvoked PotentialsFacial RecognitionPsychotic DisordersSchizophreniaSocial PerceptionAdolescentAdultElectroencephalographyFemaleHumansMaleReaction TimeRiskYoung AdultClinical high risk for psychosisEmotional processingEvent-related potentialsSchizophreniaSocial cognition

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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.