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PLoS Biol. 2015 Jun 22;13(6):e1002180. doi: 10.1371/journal.pbio.1002180. eCollection 2015 Jun.

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect.

Author information

1
Department of Psychology & Neuroscience, University of Colorado, Boulder, Colorado, United States of America.
2
Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.

Abstract

Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emotional responses to aversive images. This signature predicted the intensity of negative emotion in individual participants in cross validation (n =121) and test (n = 61) samples (high-low emotion = 93.5% accuracy). It was unresponsive to physical pain (emotion-pain = 92% discriminative accuracy), demonstrating that it is not a representation of generalized arousal or salience. The signature was comprised of mesoscale patterns spanning multiple cortical and subcortical systems, with no single system necessary or sufficient for predicting experience. Furthermore, it was not reducible to activity in traditional "emotion-related" regions (e.g., amygdala, insula) or resting-state networks (e.g., "salience," "default mode"). Overall, this work identifies differentiable neural components of negative emotion and pain, providing a basis for new, brain-based taxonomies of affective processes.

PMID:
26098873
PMCID:
PMC4476709
DOI:
10.1371/journal.pbio.1002180
[Indexed for MEDLINE]
Free PMC Article

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