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A social differential outcomes learning task: Performance, EEG, and questionnaire data

This article contains performance data, questionnaire ratings, and EEG data from a differential outcomes learning task from two experiments. In both experiments, the standard differential outcomes learning task was extended to involve a social dimension, in order to capture how people can learn from...

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Detalles Bibliográficos
Autores principales: Gander, Pierre, Rittmo, Jonathan, Carlsson, Rickard, Lowe, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726659/
https://www.ncbi.nlm.nih.gov/pubmed/33318977
http://dx.doi.org/10.1016/j.dib.2020.106590
Descripción
Sumario:This article contains performance data, questionnaire ratings, and EEG data from a differential outcomes learning task from two experiments. In both experiments, the standard differential outcomes learning task was extended to involve a social dimension, in order to capture how people can learn from others by observation. In Experiment 1 (N = 20), using a within-subjects design, participants learned pairings of image stimuli in four conditions: 1) individual-differential outcomes, 2) individual-non-differential outcomes, 3) social-differential outcomes, and 4) social-non-differential outcomes. The social condition had a screen-captured video recording of the outcomes (but not the actions themselves) of another person performing the task. During the task, the performance of the participants was measured. After the task, participants rated their experience in a questionnaire. The procedure for Experiment 2 (N = 33) was similar to Experiment 1, but with a stronger social manipulation using a video of another person's face showing facial expressions reflecting the outcomes. In addition, EEG was measured while performing the task. For more insight, please see Vicarious value learning: Knowledge transfer through affective processing on a social differential outcomes task (Rittmo et al., 2020).