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

Elsa F. Fouragnan (), Billy Hosking, Yin Cheung, Brooke Prakash, Matthew Rushworth and Alejandra Sel
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Elsa F. Fouragnan: University of Oxford
Billy Hosking: University of Plymouth
Yin Cheung: University of Oxford
Brooke Prakash: University of Oxford
Matthew Rushworth: University of Oxford
Alejandra Sel: University of Oxford

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-46921-5

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