期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 116, 期 10, 页码 4732-4737出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1810180116
关键词
social learning; decision making; Pavlovian instrumental transfer; fear; reinforcement learning
资金
- Knut and Alice Wallenberg Foundation [KAW 2014.0237]
- Riksbankens Jubileumsfond Grant [P11-1017]
- European Research Council [284366]
- Forte Grant [COFAS2: 2014-2785 FOIP]
- Swedish Research Council [2015-00312]
- Swiss National Science Foundation [100014_165884, 100019_176016]
- Swedish Research Council [2015-00312] Funding Source: Swedish Research Council
- Vinnova [2015-00312] Funding Source: Vinnova
In today's world, mass-media and online social networks present us with unprecedented exposure to second-hand, vicarious experiences and thereby the chance of forming associations between previously innocuous events (e.g., being in a subway station) and aversive outcomes (e.g., footage or verbal reports from a violent terrorist attack) without direct experience. Such social threat, or fear, learning can have dramatic consequences, as manifested in acute stress symptoms and maladaptive fears. However, most research has so far focused on socially acquired threat responses that are expressed as increased arousal rather than active behavior. In three experiments (n = 120), we examined the effect of indirect experiences on behaviors by establishing a link between social threat learning and instrumental decision making. We contrasted learning from direct experience (i.e., Pavlovian conditioning) (experiment 1) against two common forms of social threat learning-social observation (experiment 2) and verbal instruction (experiment 3)-and how this learning transferred to subsequent instrumental decision making using behavioral experiments and computational modeling. We found that both types of social threat learning transfer to decision making in a strong and surprisingly inflexible manner. Notably, computational modeling indicated that the transfer of observational and instructed threat learning involved different computational mechanisms. Our results demonstrate the strong influence of others' expressions of fear on one's own decisions and have important implications for understanding both healthy and pathological human behaviors resulting from the indirect exposure to threatening events.
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