Projects per year
Abstract
Objective: Diseases affecting sensorimotor function impair physical independence. Reliable functional clinical biomarkers allowing early diagnosis or targeting treatment and rehabilitation could reduce this burden. Magnetoencephalography (MEG) non-invasively measures brain rhythms such as the somatomotor ‘rolandic’ rhythm which shows intermittent high-amplitude beta (14–30 Hz) ‘events’ that predict behavior across tasks and species and are altered by sensorimotor neurological diseases. Methods: We assessed test–retest stability, a prerequisite for biomarkers, of spontaneous sensorimotor aperiodic (1/f) signal and beta events in 50 healthy human controls across two MEG sessions using the intraclass correlation coefficient (ICC). Beta events were determined using an amplitude-thresholding approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition. Results: Resting sensorimotor characteristics showed good to excellent test–retest stability. Aperiodic component (ICC 0.77–0.88) and beta event amplitude (ICC 0.74–0.82) were very stable, whereas beta event duration was more variable (ICC 0.55–0.7). 2–3 minute recordings were sufficient to obtain stable results. Analysis automatization was successful in 86%. Conclusions: Sensorimotor beta phenotype is a stable feature of an individual's resting brain activity even for short recordings easily measured in patients. Significance: Spontaneous sensorimotor beta phenotype has potential as a clinical biomarker of sensorimotor system integrity.
Original language | English |
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Pages (from-to) | 244-254 |
Number of pages | 11 |
Journal | Clinical Neurophysiology |
Volume | 163 |
DOIs | |
Publication status | Published - Jul 2024 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Aperiodic (1/f) activity
- Beta oscillatory activity
- Magnetoencephalography
- Resting state
- Sensorimotor
- Test–retest reliability
Fingerprint
Dive into the research topics of 'Human sensorimotor resting state beta events and aperiodic activity show good test–retest reliability'. Together they form a unique fingerprint.Projects
- 1 Finished
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Combine and compute: Combine and compute: Boost for neurological diagnostics and prognostic evaluation by combining computational modelling to functional neuroimaging
01/09/2019 → 31/08/2023
Project: Academy of Finland: Other research funding
Equipment
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Aalto Neuroimaging Infrastructure
Veikko Jousmäki (Manager)
School of ScienceFacility/equipment: Facility