Emotion regulation strategies differentially modulate neural activity across affective prediction stages : An HD-EEG investigation

Copyright © 2022 Del Popolo Cristaldi, Mento, Buodo and Sarlo..

Emotion regulation (ER) strategies can influence how affective predictions are constructed by the brain (generation stage) to prearrange action (implementation stage) and update internal models according to incoming stimuli (updating stage). However, neurocomputational mechanisms by which this is achieved are unclear. We investigated through high-density EEG if different ER strategies (expressive suppression vs. cognitive reappraisal) predicted event-related potentials (ERPs) and brain source activity across affective prediction stages, as a function of contextual uncertainty. An S1-S2 paradigm with emotional faces and pictures as S1s and S2s was presented to 36 undergraduates. Contextual uncertainty was manipulated across three blocks with 100, 75, or 50% S1-S2 affective congruency. The effects of ER strategies, as assessed through the Emotion Regulation Questionnaire, on ERP and brain source activity were tested for each prediction stage through linear mixed-effects models. No ER strategy affected prediction generation. During implementation, in the 75% block, a higher tendency to suppress emotions predicted higher activity in the left supplementary motor area at 1,500-2,000 ms post-stimulus, and smaller amplitude of the Contingent Negative Variation at 2,000-2,500 ms. During updating, in the 75% block, a higher tendency to cognitively reappraise emotions predicted larger P2, Late Positive Potential, and right orbitofrontal cortex activity. These results suggest that both ER strategies interact with the levels of contextual uncertainty by differently modulating ERPs and source activity, and that different strategies are deployed in a moderately predictive context, supporting the efficient updating of affective predictive models only in the context in which model updating occurs.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:16

Enthalten in:

Frontiers in behavioral neuroscience - 16(2022) vom: 20., Seite 947063

Sprache:

Englisch

Beteiligte Personen:

Del Popolo Cristaldi, Fiorella [VerfasserIn]
Mento, Giovanni [VerfasserIn]
Buodo, Giulia [VerfasserIn]
Sarlo, Michela [VerfasserIn]

Links:

Volltext

Themen:

Affective prediction
ERPs
Emotion Regulation
High-density EEG
Journal Article
S1-S2 paradigm

Anmerkungen:

Date Revised 23.08.2022

published: Electronic-eCollection

figshare: 10.6084/m9.figshare.13560569

Citation Status PubMed-not-MEDLINE

doi:

10.3389/fnbeh.2022.947063

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM345092538