title: MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable.
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 (30-100Hz) 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 (53-72Hz) 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.
authors.affiliation: Centre for Cognitive Neuroimaging (CCNi), Institute of Neuroscience and Psychology (INP), College of Medical, Veterinary and Life Sciences, College of Science and Engineering, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, United Kingdom. Electronic address: Heng-RuMay.Tan@glasgow.ac.uk.
authors.forename: H-R M
authors.initials: HM
authors.lastname: Tan
authors.affiliation: Centre for Cognitive Neuroimaging (CCNi), Institute of Neuroscience and Psychology (INP), College of Medical, Veterinary and Life Sciences, College of Science and Engineering, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, United Kingdom.
authors.forename: J
authors.initials: J
authors.lastname: Gross
authors.affiliation: Centre for Cognitive Neuroimaging (CCNi), Institute of Neuroscience and Psychology (INP), College of Medical, Veterinary and Life Sciences, College of Science and Engineering, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, United Kingdom.
authors.forename: P J
authors.initials: PJ
authors.lastname: Uhlhaas
mesh_terms: D000328:Adult; D001683:Biological Clocks / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D065818:Gamma Rhythm / Q000502:physiology*; D006801:Humans; D015225:Magnetoencephalography; D008297:Male; D009039:Motion Perception / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014793:Visual Cortex / Q000502:physiology*
keywords: DICS beamforming; Magnetoencephalography (MEG); Test–retest reliability; Time-frequency analysis; Visually induced gamma (30–100Hz) response