Event-Related Potentials, Emotion, and Emotion Regulation: An Integrative Review
Abstract
Progress in the study of emotion and emotion regulation has increasingly been informed by neuroscientific methods. This article focuses on two components of the event-related potential (ERP)--the P300 and the late positive potential (LPP)--and how they can be used to understand the interaction between the more automatic and controlled processing of emotional stimuli. Research is reviewed exploring: the dynamics of emotional response as indexed at early and late latencies; neurobiological correlates of emotional response; individual and developmental differences; ways in which the LPP can be utilized as a measure of emotion regulation. Future directions for the application of ERP/electroencephalogram (EEG) in achieving a more complete understanding of emotional processing and its regulation are presented.
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Suppression seems to be the most commonly employed method to deal with undesired emotions.
“Simultaneously, suppression seems to be the most commonly employed method to deal with undesired emotions (e.g., [6,7]).”
From Effects of differential strategies of emotion regulation (2019) · cites this paper as [7]
Decreased LPP amplitudes might reflect neuromodulatory activity, e.g., downstreaming processes in response to increased activation of the amygdala.
“decreased LPP amplitudes might reflect neuromodulatory activity, e.g., downstreaming processes in response to increased activation of the amygdala (e.g., [7]).”
From Effects of differential strategies of emotion regulation (2019) · cites this paper as [7]
P300 amplitudes are associated with subjective stimulus salience and closely linked to frontal top-down attentional mechanisms and temporo-parietal processes of updating and recognition performance.
“It was repeatedly shown that P300 amplitudes are associated with subjective stimulus salience and seem to be closely linked to frontal top-down attentional mechanisms as well as to temporo-parietal processes of updating and recognition performance (e.g., [7,33]).”
From Effects of differential strategies of emotion regulation (2019) · cites this paper as [7]
This is the first study to show differential P300 mean amplitudes during reappraisal.
“Although several authors predict reduced P300 amplitudes during reappraisal (e.g., [7]), this is to our knowledge, the first study which showed these differential P300 mean amplitudes.”
From Effects of differential strategies of emotion regulation (2019) · cites this paper as [7]
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BackgroundResultInfluentialNeural correlates of emotional intelligence in a visual emotional oddball task: An ERP study
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- Authors
- Hajcak, G., MacNamara, A., & Olvet, D. M.
- Affiliations
- Stony Brook University (US)
- Northwell Health (US)
- Venue
- Developmental Neuropsychology
- Publisher
- Informa UK Limited
- Published
- 2010-02-12
- Volume
- 35
- Issue
- 2
- Pages
- 129-155
- ISSN
- 1532-6942 (ISSN-L)
- 8756-5641
- OpenAlex
- W2147996559
- Cited by
- 1,370
- References
- 182
- Citations by year
- 2026: 127 · 2025: 116 · 2024: 95 · 2023: 90 · 2022: 120 · 2021: 125 · 2020: 103 · 2019: 104 · 2018: 75 · 2017: 70 · 2016: 74 · 2015: 71 · 2014: 52 · 2013: 59 · 2012: 49
- FWCI
- 27.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Developmental Neuropsychology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Clinical Psychology › Child and Adolescent Psychosocial and Emotional Development
- Social Sciences › Psychology › Social Psychology › Emotions and Moral Behavior
- Keywords
- event-related potentials, emotion regulation, P300, late positive potential, emotional processing, automatic and controlled processing, individual differences, developmental differences, EEG
- MeSH terms
- Attention, Brain Mapping, Electroencephalography, Emotions, Evoked Potentials, Humans, Emotional Intelligence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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