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Timing along the cardiac cycle modulates neural signals of reward-based learning

Psychology

Timing along the cardiac cycle modulates neural signals of reward-based learning

E. F. Fouragnan, B. Hosking, et al.

This groundbreaking study by Elsa F. Fouragnan and colleagues explores the intriguing interplay between the cardiac cycle and learning-related internal representations. Utilizing advanced EEG and machine learning techniques, the research reveals that our sensitivity to prediction errors varies with cardiac phases, influencing learning rates and accuracy. Discover how the heart might play a pivotal role in shaping our learning experiences!

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Playback language: English
Abstract
This study investigates the relationship between the cardiac cycle and learning-related internal representations (absolute and signed prediction errors). Combining machine learning techniques with EEG, the researchers found that sensitivity to low-magnitude absolute prediction errors is higher during certain cardiac phases, even with suprathreshold sensory events. Participants exhibiting stronger differences in prediction error representations between cardiac cycles showed higher learning rates and accuracy.
Publisher
Nature Communications
Published On
Apr 06, 2024
Authors
Elsa F. Fouragnan, Billy Hosking, Yin Cheung, Brooke Prakash, Matthew Rushworth, Alejandra Sel
Tags
cardiac cycle
learning
EEG
prediction errors
machine learning
sensitivity
learning rates

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