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.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Tan HM,Gross J,Uhlhaas PJ

doi

10.1016/j.neuroimage.2016.05.006

subject

Has Abstract

pub_date

2016-08-15 00:00:00

pages

34-44

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(16)30112-4

journal_volume

137

pub_type

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