logo
ResearchBunny Logo
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!... show more
Abstract
Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations – absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task 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
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny