ArticleCognitive neurodynamics2018
Influence of multiple action-outcome associations on the transition dynamics toward an optimal choice in rats.
Article in Cognitive neurodynamics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Design exploration predicts designer creativity: a deep learning approach.Cognitive neurodynamics · 2020Article
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3 authors.
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Abstract
When faced with familiar versus novel options, animals may exploit the acquired action-outcome associations or attempt to form new associations. Little is known about which factors determine the strategy of choice behavior in partially comprehended environments. Here we examine the influence of multiple action-outcome associations on choice behavior in the context of rewarding outcomes (food) and aversive outcomes (electric foot-shock). We used a nose-poke paradigm with rats, incorporating a dilemma between a familiar option and a novel, higher-value option. In Experiment 1, two groups of rats were trained with different outcome schedules: either a single action-outcome association ("Reward-Only") or dual action-outcome associations ("Reward-Shock"; with the added opportunity to avoid an electric foot-shock). In Experiment 2, we employed the same paradigm with two groups of rats performing the task under dual action-outcome associations, with different levels of threat (a low- or high-amplitude electric foot-shock). The choice behavior was clearly influenced by the action-outcome associations, with more efficient transition dynamics to the optimal choice with dual rather than single action-outcome associations. The level of threat did not affect the transition dynamics. Taken together, the data suggested that the strategy of choice behavior was modulated by the information complexity of the environment.
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