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

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
Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0003-1485-0332
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0003-0517-7625
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Institution:
University of Oxford
Role:
Author
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-5578-9884


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Funder identifier:
10.13039/501100000268
Grant:
BB/Y001494/1
More from this funder
Funder identifier:
10.13039/100004440
Grant:
WT100973AIA
More from this funder
Funder identifier:
10.13039/501100009187
Grant:
MR/T023007/1


Publisher:
Nature Research
Journal:
Nature Communications More from this journal
Volume:
15
Issue:
1
Pages:
2976-2976
Article number:
2976
Publication date:
2024-04-06
DOI:
EISSN:
2041-1723
ISSN:
2041-1723


Language:
English
Keywords:
Pubs id:
1991418
Local pid:
pubs:1991418
Source identifiers:
W4394010883
Deposit date:
2026-06-10
ARK identifier:
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