Journal article
Motor beta oscillations contribute to the temporal binding effect
- Abstract:
- Agency, the feeling of controlling one's actions and their consequences, is closely linked to temporal binding, a phenomenon where the interval between a voluntary action and its outcome is subjectively compressed. While prior research has linked temporal binding to sensorimotor processes, the role of neural oscillations remains unclear. In this study, we combined electroencephalography with an automatic imitation task to examine how trial-by-trial variations in motor-related brain rhythms predict temporal binding. Twenty-eight participants performed lifting finger movements in response to visual imperative stimuli. Following each response, they estimated the interval between their action and a subsequent tone. Time-frequency analysis and linear mixed-effects modeling revealed that reduced beta desynchronization predicted stronger temporal binding, independent of action congruency. These results suggest that motor beta oscillations reflects the temporal experience of action-effect coupling, likely reflecting predictive motor processes involved in the construction of voluntary actions.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Supplementary materials, pdf, 161.7KB, Terms of use)
-
(Preview, Accepted manuscript, pdf, 631.5KB, Terms of use)
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- Publisher copy:
- 10.1016/j.bandc.2025.106362
Authors
+ Agencia Nacional de Investigación y Desarrollo
More from this funder
- Funder identifier:
- https://ror.org/02ap3w078
- Grant:
- 11190673
- Publisher:
- Elsevier
- Journal:
- Brain and Cognition More from this journal
- Volume:
- 190
- Article number:
- 106362
- Place of publication:
- United States
- Publication date:
- 2025-09-30
- Acceptance date:
- 2025-09-22
- DOI:
- EISSN:
-
1090-2147
- ISSN:
-
0278-2626
- Pmid:
-
41032924
- Language:
-
English
- Keywords:
- Pubs id:
-
2296081
- Local pid:
-
pubs:2296081
- Deposit date:
-
2026-04-16
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Inc.
- Copyright date:
- 2025
- Rights statement:
- © 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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