MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable

Tan, H.-R.M. , Gross, J. and Uhlhaas, P. (2016) MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable. NeuroImage, 137, pp. 34-44. (doi: 10.1016/j.neuroimage.2016.05.006) (PMID:27153980) (PMCID:PMC5405052)

[img]
Preview
Text
119094.pdf - Published Version
Available under License Creative Commons Attribution.

1MB

Abstract

High frequency brain oscillations are associated with numerous cognitive and behavioral processes. Non-invasive measurements using electro-/magnetoencephalography (EEG/MEG) have revealed that high frequency neural signals are heritable and manifest changes with age as well as in neuropsychiatric illnesses. Despite the extensive use of EEG/MEG-measured neural oscillations in basic and clinical research, studies demonstrating test–retest reliability of power and frequency measures of neural signals remain scarce. Here, we evaluated the test–retest reliability of visually induced gamma (30–100 Hz) oscillations derived from sensor and source signals acquired over two MEG sessions. The study required participants (N = 13) to detect the randomly occurring stimulus acceleration while viewing a moving concentric grating. Sensor and source MEG measures of gamma-band activity yielded comparably strong reliability (average intraclass correlation, ICC = 0.861). Peak stimulus-induced gamma frequency (53–72 Hz) yielded the highest measures of stability (ICCsensor = 0.940; ICCsource = 0.966) followed by spectral signal change (ICCsensor = 0.890; ICCsource = 0.893) and peak frequency bandwidth (ICCsensor = 0.856; ICCsource = 0.622). Furthermore, source-reconstruction significantly improved signal-to-noise for spectral amplitude of gamma activity compared to sensor estimates. Our assessments highlight that both sensor and source derived estimates of visually induced gamma-band oscillations from MEG signals are characterized by high test–retest reliability, with source derived oscillatory measures conferring an improvement in the stability of peak-frequency estimates. Importantly, our finding of high test–retest reliability supports the feasibility of pharma-MEG studies and longitudinal aging or clinical studies.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Uhlhaas, Professor Peter and Tan, Dr Heng-Ru May and Gross, Professor Joachim
Authors: Tan, H.-R.M., Gross, J., and Uhlhaas, P.
College/School:College of Medical Veterinary and Life Sciences > Institute of Neuroscience and Psychology
Journal Name:NeuroImage
Publisher:Elsevier
ISSN:1053-8119
ISSN (Online):1095-9572
Published Online:03 May 2016
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in NeuroImage 137:34-44
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
597051Natural and modulated neural communication: State-dependent decoding and driving of human Brain Oscillations.Joachim GrossWellcome Trust (WELLCOME)098433/Z/12/ZINP - CENTRE FOR COGNITIVE NEUROIMAGING