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A Mixed Longitudinal EEG Study of Sensorimotor Rhythm Modulation and Its Relationship with Language Development in Children Aged 3-10 Years.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches
  1. [1] § 2. Materials and Methods › 2.5. EEG Acquisition and Preprocessing ↔ scripts/scripts for CSD .ipynb, lines 36–47 · score 0.81 · n_legendre_terms, source density, auto, lambda2, sphere, stiffness
  2. [2] § 2. Materials and Methods › 2.5. EEG Acquisition and Preprocessing ↔ scripts/Fast Fourier Transform.ipynb, lines 31–48 · score 0.54 · Fast Fourier Transform, FFT, MNE, CSD, EEG

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Jupyter notebook · 68 lines · 1.2 KB · no license · 1 match

  1. # %%
  2. import mne
  3. from mne.preprocessing import ICA
  4. import matplotlib.pyplot as plt
  5. import numpy as np
  6. from scipy.stats import kurtosis
  7. from scipy.stats import skew , variation
  8. from scipy.signal import welch
  9. import pandas as pd
  10. from scipy.signal import hilbert
  11. import glob
  12. from mne.event import define_target_events
  13. import os
  15. # %%
  16. %matplotlib qt
  18. # %% [markdown]
  19. # # CSD for cycle
  21. # %%
  22. os.chdir('D:/all_eeg/mu_eeg/chernovik_2/mu preprocess left and right hand all age/')
  25. # %%
  27. filenames_mu_r = glob.glob('*_mu_r_epoch_1.1.fif')
  28. print(len(filenames_mu_r))
  31. # %%
  32. ID_mu_r_epoch = filenames_mu_r
  33. print(len(ID_mu_r_epoch))
  34. ID_mu_r_epoch
  36. # %%
  37. folder = "D:/all_eeg/mu_eeg/chernovik_2/mu preprocess left and right hand all age/"
  38. for i in range(len(ID_mu_r_epoch)):
  39. print(ID_mu_r_epoch[i])
  40. name = ID_mu_r_epoch[i]
  41. read = mne.read_epochs(name, proj=True, preload=True, verbose=None)
  42. CSD_mu_r = mne.preprocessing.compute_current_source_density(read, sphere='auto', lambda2=1e-05, stiffness=4, n_legendre_terms=50, copy=True, verbose=None)#считаем CSD
  43. ID = name
  44. print(ID)
  45. ID_name = ID[:8]
  46. print(ID_name)
  47. CSD_mu_r.save(folder + ID_name + '_mu_r_epoch_CSD_Cz.fif', overwrite=True)
  49. # %%
  52. # %%
  55. # %%
  58. # %%
  61. # %%
  64. # %%
  67. # %%

scripts for CSD .ipynb, no license · at the source

Overview

Authors: Vladimir Lipatov1, Anna Rebreikina1,2, Olga Sysoeva1,2
ORCID iDs: Vladimir Lipatov, Anna Rebreikina, Olga Sysoeva
  1. Centre for Research on Talent Development, Sirius University of Science and Technology, Sirius Federal Territory, 354340 Sochi, Russia; (V.L.); (O.S.)
  2. Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of RAS, 117485 Moscow, Russia
Institutions: Sirius University of Science and Technology (Russia); Institute of Higher Nervous Activity and Neurophysiology (Russia)
Journal: Brain sciences, volume 16, issue 8, article 880
Dates: received 14 July 2026; accepted 14 August 2026; published online 18 August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.3390/brainsci16080880 · PMID 42651188 · PMCID PMC13511290 · OpenAlex W7203682829
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: EEG (modality), human (organism), systems (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Preprocessing, Connectivity
Keywords: EEG, sensorimotor rhythm, longitudinal study, language development, preschool and primary school children
Topic: Action Observation and Synchronization (Social Psychology, Psychology), according to OpenAlex
Funding: Ministry of Science and Higher Education of the Russian Federation (075-10-2025-017)
Citations: not cited yet (Europe PMC); 48 references in the paper

Abstract

Background: Sensorimotor (mu) rhythms reflect the functional state of sensorimotor cortical networks and are of increasing interest for understanding typical and atypical neurodevelopment. However, the developmental trajectories of mu rhythm modulation in preschool and early school-age children remain poorly characterized. Objectives: We studied age-related changes in alpha (8–13 Hz) and beta (13–30 Hz) sensorimotor rhythms in children aged 3 to 10 years using a mixed longitudinal design and investigated their relationship with language development. Methods: EEG was recorded twice (interval ~1 year) in 44 typically developing children during three conditions: passive hand movement (PHM), video hand movement observation (VHM), and a control condition (video fractal movement, VFM). Language was assessed with the Preschool Language Scales—Fifth Edition (PLS-5) in a subset of 32 of the 44 participants at the first time point. Modulation indices (log10(experimental/control)) were computed, and repeated-measures ANOVAs and Spearman correlations were performed. Results: PHM elicited desynchronization in both alpha and beta bands, while VHM induced alpha synchronization only. Alpha desynchronization showed contralateral lateralization during right- and left-hand movements, without age-related changes. Beta desynchronization showed no lateralization. Beta desynchronization during PHM correlated negatively with Auditory Comprehension and Total Language scores (ρ up to −0.62, FDR-corrected p < 0.05), indicating that more pronounced desynchronization of sensorimotor rhythms relates to better language abilities. Conclusions: These findings support the involvement of sensorimotor networks in auditory language comprehension and suggest that beta mu rhythm may serve as a sensitive marker of individual differences in language development, though replication in larger samples is warranted.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

OSF mnuaz

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: Jupyter (3)
Size: 7 files, 3 scripts
Software Heritage: not checked
Found in: “Data Availability Statement”
Holds: 3 notebooks
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (3 files), MNE-Python (3 files), NumPy (3 files), pandas (3 files), SciPy (3 files), ICLabel (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
3 files
At the source: osf.io/mnuaz/overview

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 3 scripts, each with its path and the digest of its content;
  • 2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

The scripts and data used for this study can be found at the following link: https://osf.io/mnuaz/overview (accessed on 13 August 2026).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 1 funder, 45 references.

Cite

This paper

Lipatov, V., Rebreikina, A., & Sysoeva, O. (2026). A Mixed Longitudinal EEG Study of Sensorimotor Rhythm Modulation and Its Relationship with Language Development in Children Aged 3-10 Years. Brain sciences, 16(8), 880. https://doi.org/10.3390/brainsci16080880

BibTeX

@article{lipatov2026mixed,
author = {Lipatov, Vladimir and Rebreikina, Anna and Sysoeva, Olga},
title = {{A Mixed Longitudinal EEG Study of Sensorimotor Rhythm Modulation and Its Relationship with Language Development in Children Aged 3-10 Years}},
journal = {Brain sciences},
year = {2026},
month = aug,
volume = {16},
number = {8},
pages = {880},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
issn = {2076-3425},
doi = {10.3390/brainsci16080880},
url = {https://doi.org/10.3390/brainsci16080880},
pmid = {42651188},
pmcid = {PMC13511290}
}

RIS

TY - JOUR
AU - Lipatov, Vladimir
AU - Rebreikina, Anna
AU - Sysoeva, Olga
TI - A Mixed Longitudinal EEG Study of Sensorimotor Rhythm Modulation and Its Relationship with Language Development in Children Aged 3-10 Years
T2 - Brain sciences
J2 - Brain Sci
PY - 2026
DA - 2026/08/18
VL - 16
IS - 8
SP - 880
SN - 2076-3425
PB - Multidisciplinary Digital Publishing Institute (MDPI)
DO - 10.3390/brainsci16080880
UR - https://doi.org/10.3390/brainsci16080880
LA - en
ER -

CSL-JSON

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"PMCID": "PMC13511290",
"ISSN": "2076-3425",
"publisher": "Multidisciplinary Digital Publishing Institute (MDPI)",
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The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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