Prime and probability: causal knowledge affects inferential and predictive effects on self-agency experiences.

Area of Science:

• Cognitive Neuroscience
• Psychology

Background:

• Sense of self-agency arises from action-outcome predictions and causal inferences.
• The interplay between prediction and inference in self-agency experiences remains unclear.
• Prior research suggests prediction and inference effects on self-agency are influenced by causal knowledge.

Purpose of the Study:

• To investigate how motor predictions and causal inferences combine to affect self-agency.
• To determine the role of relevant causal knowledge in modulating these effects.
• To explore the conditions under which prediction and inference contribute to self-agency.

Main Methods:

• Manipulated causal knowledge by varying action-outcome co-occurrence probabilities (50% vs. 80%).
• Measured self-agency experiences in an action-outcome task.
• Varied outcome priming to assess prediction and inference effects.

Main Results:

• Motor prediction influenced self-agency only when relevant causal relationships between actions and outcomes were learned.
• Inference effects on self-agency were observed even without relevant causal knowledge acquisition.
• The relevance of causal knowledge critically impacts the contribution of motor prediction to self-agency.

Conclusions:

• Self-agency experiences are shaped by both predictive and inferential processes.
• Learned causal relationships are crucial for prediction-based self-agency.
• Inference mechanisms contribute to self-agency independently of learned causal relevance.