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Projekt Druckansicht

Neurale Schätzung feindseliger Erwartungen

Fachliche Zuordnung Biologische Psychologie und Kognitive Neurowissenschaften
Kognitive und systemische Humanneurowissenschaften
Kognitive, systemische und Verhaltensneurobiologie
Förderung Förderung von 2020 bis 2021
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 431342690
 
Erstellungsjahr 2022

Zusammenfassung der Projektergebnisse

Aggressive individuals often “see red”: they assume that others want to harm them even in neutral or ambiguous situations. This makes them jump to conclusions and rashly act on their impulses. A better understanding of how these tendencies emerge might help us predict and manage antisocial behavior. Here, we crafted a virtual shooting task to measure how people develop hostile expectations. In the task, a sample of 256 healthy young adults had to either shoot or withhold their weapon depending on whether they expected another person to draw a gun or a phone. In this context, a tendency to shoot more often signals higher hostile expectations. Using computer algorithms, we were able to parse different aspects of hostile expectation learning and inspected whether they were linked with self-reported aggressive and psychopathic tendencies. As expected, persons with higher levels of aggressive and psychopathic traits developed more pronounced hostile expectations - i.e., they shot their gun more often. However, their hostile expectations were also more uncertain, meaning that they generally shot more indiscriminately. Surprisingly, persons with high levels of aggressiveness and psychopathy also showed more temporally stable hostility beliefs. This implies that their hostile expectations were more resistant to change once learned. As a result, they were more surprised when non-aggressive outcomes ensued (when their rival drew a phone instead of a gun). In sum, our study shows that persons with higher aggressiveness and psychopathy acquire strong and stable yet imprecise hostile expectations. Our findings thus provide fine-grained, mechanistic insight into the architecture of hostile thought and could potentially inform violence risk assessment and anger management therapy among others.

Projektbezogene Publikationen (Auswahl)

  • (2022). Acquiring hostile expectations through reinforcement learning: Computational, personality, and behavioural correlates
    Buades-Rotger, M., Smeijers, D., Gallardo-Pujol, D., Krämer, U. M., & Brazil, I.
    (Siehe online unter https://doi.org/10.31234/osf.io/2ydsz)
 
 

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