Perceptual Temporal Structure Supports Rhythm Learning and Enhances Theta Oscillations When Perception and Action Are Dissociated.
The 4 matches · 3 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
- [1] § 2. Materials and Methods › 2.4. Analysis › 2.4.2. Time-Frequency Magnitude ↔ codes/bs_codes_exp2/d_tf_wavelet.m, the whole file · a weak match · score 0.69 · Morlet wavelets, 1–30 Hz, Brainstorm, magnitude
- [2] § 3. Results › 3.1. Learning Slope ↔ codes/learning_slope_compar_exp1-3.R, lines 277–317 · score 0.60 · post hoc, Bonferroni corrected, learning slopes, Exp1, Exp2
- [3] § 2. Materials and Methods › 2.4. Analysis › 2.4.2. Time-Frequency Magnitude ↔ codes/bs_codes_exp2/j_t_map_overall.m, the whole file · a weak match · score 0.55 · 1–30 Hz, 4.8–5.2 Hz, 4.8 Hz, zero, magnitude, 0.8 s
- [4] § 2. Materials and Methods › 2.4. Analysis › 2.4.2. Time-Frequency Magnitude ↔ codes/bs_codes_exp1/j_t_map_overall.m, the whole file · a weak match · score 0.54 · 1–30 Hz, 4.8–5.2 Hz, 4.8 Hz, zero, magnitude, EEG
Paper
Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC
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The authors' code
MATLAB · 46 lines · 2.2 KB · no license · 1 match
- % Script generated by Brainstorm (26-Mar-2024)
- % Input files
- sFiles = [];
- SubjectNames = {...
- 'All'};
- % Start a new report
- bst_report('Start', sFiles);
- % Process: Select data files in: */*/AVG
- sFiles = bst_process('CallProcess', 'process_select_files_data', sFiles, [], ...
- 'subjectname', SubjectNames{1}, ...
- 'condition', '', ...
- 'tag', 'AVG', ...
- 'includebad', 0, ...
- 'includeintra', 0, ...
- 'includecommon', 0, ...
- 'source_abs', 0);
- % Process: Time-frequency (Morlet wavelets)
- sFiles = bst_process('CallProcess', 'process_timefreq', sFiles, [], ...
- 'sensortypes', 'EEG', ...
- 'edit', struct(...
- 'Comment', 'Magnitude,1-30Hz', ...
- 'TimeBands', [], ...
- 'Freqs', [1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3, 3.2, 3.4, 3.6, 3.8, 4, 4.2, 4.4, 4.6, 4.8, 5, 5.2, 5.4, 5.6, 5.8, 6, 6.2, 6.4, 6.6, 6.8, 7, 7.2, 7.4, 7.6, 7.8, 8, 8.2, 8.4, 8.6, 8.8, 9, 9.2, 9.4, 9.6, 9.8, 10, 10.2, 10.4, 10.6, 10.8, 11, 11.2, 11.4, 11.6, 11.8, 12, 12.2, 12.4, 12.6, 12.8, 13, 13.2, 13.4, 13.6, 13.8, 14, 14.2, 14.4, 14.6, 14.8, 15, 15.2, 15.4, 15.6, 15.8, 16, 16.2, 16.4, 16.6, 16.8, 17, 17.2, 17.4, 17.6, 17.8, 18, 18.2, 18.4, 18.6, 18.8, 19, 19.2, 19.4, 19.6, 19.8, 20, 20.2, 20.4, 20.6, 20.8, 21, 21.2, 21.4, 21.6, 21.8, 22, 22.2, 22.4, 22.6, 22.8, 23, 23.2, 23.4, 23.6, 23.8, 24, 24.2, 24.4, 24.6, 24.8, 25, 25.2, 25.4, 25.6, 25.8, 26, 26.2, 26.4, 26.6, 26.8, 27, 27.2, 27.4, 27.6, 27.8, 28, 28.2, 28.4, 28.6, 28.8, 29, 29.2, 29.4, 29.6, 29.8, 30], ...
- 'MorletFc', 1, ...
- 'MorletFwhmTc', 3, ...
- 'ClusterFuncTime', 'none', ...
- 'Measure', 'magnitude', ...
- 'Output', 'all', ...
- 'RemoveEvoked', 0, ...
- 'SaveKernel', 0), ...
- 'normalize2020', 1, ...
- 'normalize', 'none'); % None: Save non-standardized time-frequency maps
- % Save and display report
- ReportFile = bst_report('Save', sFiles);
- bst_report('Open', ReportFile);
- % bst_report('Export', ReportFile, ExportDir);
- % bst_report('Email', ReportFile, username, to, subject, isFullReport);
- % Delete temporary files
- % gui_brainstorm('EmptyTempFolder');
d_tf_wavelet.m, no license · at the source
Overview
- School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; (X.W.); (X.Z.)
- Fudan Institute on Ageing, Fudan University, Shanghai 200433, China; (Y.L.)
- Ministry of Education (MOE) Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China
- Silver-X MOE Philosophy & Social Sciences Laboratory, Fudan University, Shanghai 200433, China
Abstract
Highlights: What are the main findings?
Rhythm learning primarily relies on perceptual temporal input rather than motor execution alone.
Global theta oscillations are selectively enhanced during successful perceptual rhythm learning and index unconscious knowledge acquisition.
What are the implications of the main findings?
The paradigm enables independent manipulation of perceptual and motor rhythms, providing a new approach to studying sequence learning.
Perceptually driven rhythmic knowledge can be acquired implicitly and outperforms motor execution alone, with global theta oscillations as a key neural signature.
Abstract: Background: Rhythmic knowledge enables the precise timing of actions in dynamic environments. Although rhythm learning has been extensively studied, it remains debated whether such learning arises primarily from the perceptual encoding of rhythmic inputs or from the repetitive execution of periodic actions. Methods: To address this question, we developed a temporal-rhythm serial reaction time (TR-SRT) paradigm that dissociates rhythmic structures in perceptual inputs from the timing of motor responses. Across three experiments, participants learned rhythms under visuomotor (Experiment 1, N = 27), visual-only (Experiment 2, N = 26), or motor-only (Experiment 3, N = 26) conditions while electroencephalography was recorded. Results: Behavioral learning slopes revealed robust rhythm learning in both the visuomotor and visual-only conditions, whereas no learning emerged when rhythmic structure was confined to motor timing alone. Post-learning awareness tests further indicated that the acquired rhythmic knowledge was predominantly implicit. Consistently, global (whole-brain) theta-band magnitude (4.8–5.2 Hz) was enhanced only in the conditions that supported rhythm learning. Conclusions: These findings indicate that rhythm learning depends primarily on perceptual temporal structure rather than the repetition of rhythmic actions and identify increased global theta oscillations as a neural signature of this perceptually driven and largely implicit learning process.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repositories
Its files are read in the Code ↔ Paper reader above, with 4 matches between paragraphs and lines of code.
OSF wjvf6
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
- 30 September 2026: the link answers (HTTP 200)
16 files
- EEG_data/
theta_analysis_exp1.R , R, 308 lines - behavioral_data/
RT_analysis_code_exp1.R , R, 304 lines - codes/
Conditioning_TR_exp1_3.m , MATLAB, 119 lines - codes/
Merge_EEG_TR_exp1_sub27. , MATLAB, 29 linesm - codes/
bs_codes_exp1/ , MATLAB, 48 linesa_Import_datat.m - codes/
bs_codes_exp1/ , MATLAB, 38 linesb_Chan_locs.m - codes/
bs_codes_exp1/ , MATLAB, 36 linesc_Trial_Average.m - codes/
bs_codes_exp1/ , MATLAB, 46 linesd_tf_wavelet.m - codes/
bs_codes_exp1/ , MATLAB, 35 linese_tf_norm.m - codes/
bs_codes_exp1/ , MATLAB, 37 linesf_tf_cond_grand_average. m - codes/
bs_codes_exp1/ , MATLAB, 41 linesg_avg_corssCond_perSub.m - codes/
bs_codes_exp1/ , MATLAB, 47 linesh_test_overall.m - codes/
bs_codes_exp1/ , MATLAB, 47 linesi_tf_avg_cross_conds.m - codes/
bs_codes_exp1/ , MATLAB, 47 lines, 1 matchj_t_map_overall.m - codes/
eeg_preprocess_TR_exp1.m , MATLAB, 214 lines - codes/
prior_sample_size_decisi , R, 32 lineson.R
OSF 24ebu
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
- 30 September 2026: the link answers (HTTP 200)
17 files
- EEG_data/
theta_analysis_exp2.R , R, 307 lines - behavioral_data/
RT_analysis_code_exp2.R , R, 825 lines - codes/
Conditioning_TR_exp1_3.m , MATLAB, 119 lines - codes/
Merge_EEG_TR_exp2_sub11. , MATLAB, 23 linesm - codes/
bs_codes_exp2/ , MATLAB, 48 linesa_Import_datat.m - codes/
bs_codes_exp2/ , MATLAB, 38 linesb_Chan_locs.m - codes/
bs_codes_exp2/ , MATLAB, 36 linesc_Trial_Average.m - codes/
bs_codes_exp2/ , MATLAB, 46 lines, 1 matchd_tf_wavelet.m - codes/
bs_codes_exp2/ , MATLAB, 35 linese_tf_norm.m - codes/
bs_codes_exp2/ , MATLAB, 37 linesf_tf_cond_grand_average. m - codes/
bs_codes_exp2/ , MATLAB, 41 linesg_avg_corssCond_perSub.m - codes/
bs_codes_exp2/ , MATLAB, 47 linesh_test_overall.m - codes/
bs_codes_exp2/ , MATLAB, 47 linesi_tf_avg_cross_conds.m - codes/
bs_codes_exp2/ , MATLAB, 47 lines, 1 matchj_t_map_overall.m - codes/
bs_codes_exp2/ , MATLAB, 42 linesk_extract_vaules.m - codes/
bs_codes_exp2/ , MATLAB, 35 linesl_export_theta.m - codes/
eeg_preprocess_TR_exp2an , MATLAB, 207 linesd3.m
OSF j3sw9
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
- 30 September 2026: the link answers (HTTP 200)
18 files
- EEG_data/
theta_analysis_exp3.R , R, 298 lines - behavioral_data/
RT_analysis_code_exp3.R , R, 813 lines - codes/
Conditioning_TR_exp1_3.m , MATLAB, 119 lines - codes/
bs_codes_exp3/ , MATLAB, 47 linesa_Import_datat.m - codes/
bs_codes_exp3/ , MATLAB, 38 linesb_Chan_locs.m - codes/
bs_codes_exp3/ , MATLAB, 36 linesc_Trial_Average.m - codes/
bs_codes_exp3/ , MATLAB, 46 linesd_tf_wavelet.m - codes/
bs_codes_exp3/ , MATLAB, 35 linese_tf_norm.m - codes/
bs_codes_exp3/ , MATLAB, 37 linesf_tf_cond_grand_average. m - codes/
bs_codes_exp3/ , MATLAB, 41 linesg_avg_corssCond_perSub.m - codes/
bs_codes_exp3/ , MATLAB, 47 linesh_test_overall.m - codes/
bs_codes_exp3/ , MATLAB, 47 linesi_tf_avg_cross_conds.m - codes/
bs_codes_exp3/ , MATLAB, 47 linesj_t_map_overall.m - codes/
bs_codes_exp3/ , MATLAB, 42 linesk_extract_vaules.m - codes/
bs_codes_exp3/ , MATLAB, 35 linesl_export_theta.m - codes/
eeg_preprocess_TR_exp2an , MATLAB, 207 linesd3.m - codes/
learning_slope_compar_ex , R, 318 lines, 1 matchp1-3.R - codes/
theta_compare_exp1-3.R , R, 320 lines
The paper's code and data availability statement is in the Data section.
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Data
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Data Availability Statement
All data, analysis codes, and experimental materials of this study are available via the Open Science Framework, Experiment 1: https://
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Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 5 keywords, 1 funder, 57 references.
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This paper
Weng, X., Lu, Y., Zhao, X., Jiang, H., Li, L., & Guo, X. (2026). Perceptual Temporal Structure Supports Rhythm Learning and Enhances Theta Oscillations When Perception and Action Are Dissociated. Brain sciences, 16(5), 489. https://
BibTeX
@article{weng2026percept
author = {Weng, Xue and Lu, Yang and Zhao, Xinyue and Jiang, Haoran and Li, Lin and Guo, Xiuyan},
title = {{Perceptual Temporal Structure Supports Rhythm Learning and Enhances Theta Oscillations When Perception and Action Are Dissociated}},
journal = {Brain sciences},
year = {2026},
month = apr,
volume = {16},
number = {5},
pages = {489},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
issn = {2076-3425},
doi = {10.3390/
url = {https://
pmid = {42192800},
pmcid = {PMC13204124}
}
RIS
TY - JOUR
AU - Weng, Xue
AU - Lu, Yang
AU - Zhao, Xinyue
AU - Jiang, Haoran
AU - Li, Lin
AU - Guo, Xiuyan
TI - Perceptual Temporal Structure Supports Rhythm Learning and Enhances Theta Oscillations When Perception and Action Are Dissociated
T2 - Brain sciences
J2 - Brain Sci
PY - 2026
DA - 2026/
VL - 16
IS - 5
SP - 489
SN - 2076-3425
PB - Multidisciplinary Digital Publishing Institute (MDPI)
DO - 10.3390/
UR - https://
LA - en
ER -
CSL-JSON
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