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A meta-analysis of periodic and aperiodic electrophysiological features in Parkinson's disease.

Overview

Authors: Hamzeh Norouzi1, Magdalena Ietswaart1, Jason Adair2, Gemma Learmonth1
ORCID iDs: Hamzeh Norouzi, Magdalena Ietswaart, Jason Adair, Gemma Learmonth
  1. School of Psychology, University of Stirling, Stirling FK9 4LA, Scotland, UK
  2. School of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, Scotland, UK
Institutions: University of Stirling (United Kingdom)
Journal: Brain communications, volume 8, issue 5, article fcag329
Dates: received 4 August 2025; accepted 27 July 2026; published online 28 August 2026
Type: Review · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag329 · PMID 42724388 · PMCID PMC13559478 · OpenAlex W7204602077
Open access: gold, a free copy (OpenAlex)
Status: data only (how the code is found and verified)
Categories: EEG (modality), MEG (modality), human (organism), Parkinson's (population)
Methods: Connectivity, Spectral & time-frequency, Smoothing, state filtering, decompositions, Preprocessing, Statistics, fMRI & imaging
Keywords: alpha oscillations, beta oscillations, EEG, MEG, specparam
Topic: Deep Brain Stimulation and Movement Disorders (Clinical Neurology, Medicine), according to OpenAlex
Funding: McGill University; University of Oregon; University of Stirling; Karolinska Institutet; Turun Yliopisto
Citations: cited by 1 paper (Europe PMC); 141 references in the paper

Abstract

Parkinson’s disease is characterized by a range of motor and non-motor changes that can negatively impact quality of life. Many studies have identified potential clinical electrophysiological correlates of Parkinson’s disease with an aim of developing new methods of identifying at-risk patients and forming the basis of therapeutic interventions. However, these studies do not present consistent results, and a formal meta-analysis is warranted to identify reliable EEG or magnetoencephalography (M/EEG) characteristics across datasets. In this meta-analysis of open-access M/EEG datasets (n = 6; 4 EEG and 2 MEG), we compared periodic and aperiodic characteristics of resting-state recordings in 368 patients with Parkinson’s disease and 570 age-matched healthy controls. Specifically, we compared the power and peak frequency of unadjusted and aperiodic-adjusted alpha- and beta-band oscillations, and the exponent and offset, across the two groups. Parkinson’s patients had a consistently elevated aperiodic exponent and offset. Patients also had higher unadjusted beta-band power, but this was no longer present when the aperiodic features were removed, suggesting that previous findings of elevated beta activity in Parkinson’s disease could be confounded by aperiodic activity rather than reflecting true oscillatory differences. Patients also had higher adjusted and unadjusted alpha-band power and a slower alpha peak frequency compared with controls, whereas no group difference in beta peak frequency was identified. In conclusion, this large cohort meta-analysis points to a broadly consistent pattern of both periodic and aperiodic changes in Parkinson’s patients in M/EEG signals that may be used to develop diagnostics and targeted interventions in the future.

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

Code

The paper links to its data and to no code of its authors: see the Data section.

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

Tracing map

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Data

Datasets cited

Data availability

The full analysis scripts are available at https://github.com/HamzehNorouzi/Meta_Reanalysis. The data for five datasets were publicly available from the following locations: New Mexico (https://openneuro.org/datasets/ds003490/versions/1.1.0), Iowa (https://openneuro.org/datasets/ds004584/versions/1.0.0), Turku (https://osf.io/pehj9/), San Diego (https://openneuro.org/datasets/ds002778/versions/1.0.2) and NatMEG (https://search.kg.ebrains.eu/instances/d55146e8-fc86-44dd-95db-7191fdca7f30). The data for the OMEGA dataset were obtained directly from the original study authors upon request.

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 2, 28 September 2026

  • Funding: added McGill University; University of Oregon; University of Stirling; Karolinska Institutet; Turun Yliopisto

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 5 keywords, 127 references.

Cite

This paper

Norouzi, H., Ietswaart, M., Adair, J., & Learmonth, G. (2026). A meta-analysis of periodic and aperiodic electrophysiological features in Parkinson's disease. Brain communications, 8(5), fcag329. https://doi.org/10.1093/braincomms/fcag329

BibTeX

@article{norouzi2026meta,
author = {Norouzi, Hamzeh and Ietswaart, Magdalena and Adair, Jason and Learmonth, Gemma},
title = {{A meta-analysis of periodic and aperiodic electrophysiological features in Parkinson's disease}},
journal = {Brain communications},
year = {2026},
month = aug,
volume = {8},
number = {5},
pages = {fcag329},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag329},
url = {https://doi.org/10.1093/braincomms/fcag329},
pmid = {42724388},
pmcid = {PMC13559478}
}

RIS

TY - JOUR
AU - Norouzi, Hamzeh
AU - Ietswaart, Magdalena
AU - Adair, Jason
AU - Learmonth, Gemma
TI - A meta-analysis of periodic and aperiodic electrophysiological features in Parkinson's disease
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/08/28
VL - 8
IS - 5
SP - fcag329
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag329
UR - https://doi.org/10.1093/braincomms/fcag329
LA - en
ER -

CSL-JSON

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