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Updated: Apr 8, 2026

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Published on: February 15, 2015
Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity
Alva Appelgren1, Sara L Bengtsson1
1Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Positive trait feedback, like "you are clever," can hinder cognitive performance and motivation. Task-specific feedback improves performance by engaging self-reflection processes.
Area of Science:
- Cognitive Neuroscience
- Social Psychology
Background:
- Positive self-associations, such as believing oneself to be "clever," are often assumed to enhance cognitive performance.
- However, empirical evidence suggests this relationship is more complex than commonly perceived.
Purpose of the Study:
- To investigate the influence of different types of positive feedback (trait-based vs. task-based) on cognitive performance and neural activity.
- To explore how self-reflection, prompted by feedback, impacts motivation and task engagement.
Main Methods:
- A functional magnetic resonance imaging (fMRI) study involving 20 participants in a crossover design.
- Participants completed a rule-switching task receiving either "trait feedback" (e.g., "you are clever") or "task feedback" (e.g., "your choice was correct") after correct responses.
Main Results:
- Trait feedback was less beneficial for motivation and performance improvement compared to task feedback.
- Trait feedback led to increased neural activation in areas associated with uncertainty, such as the anterior caudate nucleus, during difficult trials.
- Task feedback promoted self-reflection that positively correlated with performance, unlike externally imposed trait-based self-reflection.
Conclusions:
- Feedback type significantly influences cognitive performance and motivation by modulating self-reflection and uncertainty processing.
- Trait-focused feedback may divert cognitive resources away from task-focused processing, potentially hindering performance.
- Understanding the impact of feedback on self-reflection is crucial for optimizing learning and performance.
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