Brain representations of affective valence and intensity in sustained pleasure and pain

  • Soo Ahn Lee
  • , Jae Joong Lee
  • , Jisoo Han
  • , Myunghwan Choi
  • , Tor D. Wager
  • , Choong Wan Woo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Pleasure and pain are two fundamental, intertwined aspects of human emotions. Pleasurable sensations can reduce subjective feelings of pain and vice versa, and we often perceive the termination of pain as pleasant and the absence of pleasure as unpleasant. This implies the existence of brain systems that integrate them into modality-general representations of affective experiences. Here, we examined representations of affective valence and intensity in an functional MRI (fMRI) study (n = 58) of sustained pleasure and pain. We found that the distinct subpopulations of voxels within the ventromedial and lateral prefrontal cortices, the orbitofrontal cortex, the anterior insula, and the amygdala were involved in decoding affective valence versus intensity. Affective valence and intensity predictive models showed significant decoding performance in an independent test dataset (n = 62). These models were differentially connected to distinct large-scale brain networks—the intensity model to the ventral attention network and the valence model to the limbic and default mode networks. Overall, this study identified the brain representations of affective valence and intensity across pleasure and pain, promoting a systems-level understanding of human affective experiences.

Original languageEnglish
Article numbere2310433121
Pages (from-to)2-10
Number of pages9
JournalProceedings of the National Academy of Sciences of the United States of America
Volume121
Issue number25
DOIs
StatePublished - 18 Jun 2024

Keywords

  • affective neuroscience
  • functional MRI
  • pain and pleasure
  • predictive modeling

Fingerprint

Dive into the research topics of 'Brain representations of affective valence and intensity in sustained pleasure and pain'. Together they form a unique fingerprint.

Cite this