Literature DB >> 24001457

Affective traits link to reliable neural markers of incentive anticipation.

Charlene C Wu1, Gregory R Samanez-Larkin, Kiefer Katovich, Brian Knutson.   

Abstract

While theorists have speculated that different affective traits are linked to reliable brain activity during anticipation of gains and losses, few have directly tested this prediction. We examined these associations in a community sample of healthy human adults (n=52) as they played a Monetary Incentive Delay task while undergoing functional magnetic resonance imaging (FMRI). Factor analysis of personality measures revealed that subjects independently varied in trait Positive Arousal and trait Negative Arousal. In a subsample (n=14) retested over 2.5years later, left nucleus accumbens (NAcc) activity during anticipation of large gains (+$5.00) and right anterior insula activity during anticipation of large losses (-$5.00) showed significant test-retest reliability (intraclass correlations>0.50, p's<0.01). In the full sample (n=52), trait Positive Arousal correlated with individual differences in left NAcc activity during anticipation of large gains, while trait Negative Arousal correlated with individual differences in right anterior insula activity during anticipation of large losses. Associations of affective traits with neural activity were not attributable to the influence of other potential confounds (including sex, age, wealth, and motion). Together, these results demonstrate selective links between distinct affective traits and reliably-elicited activity in neural circuits associated with anticipation of gain versus loss. The findings thus reveal neural markers for affective dimensions of healthy personality, and potentially for related psychiatric symptoms.
© 2013. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Accumbens; Affect; FMRI; Insula; Punishment; Reward

Mesh:

Year:  2013        PMID: 24001457      PMCID: PMC3849140          DOI: 10.1016/j.neuroimage.2013.08.055

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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