Human sensorimotor resting state beta events and 1/f response show good test-retest reliability

Neurological conditions affecting the sensorimotor system have a profound impact on individuals' physical independence and are associated with a considerable socioeconomic burden. Reliable functional biomarkers allowing early diagnosis of these conditions or targeting treatment and rehabilitation can reduce this burden. Magnetoencephalography (MEG) can non-invasively measure the brain's salient rhythmic patterns such as the somatomotor ('rolandic') rhythm. This rhythm shows intermittent high amplitude 'events' in the beta (14-30 Hz) frequency range which predict behavior across tasks and species and are altered by neurological diseases affecting the sensorimotor system. Thus, the sensorimotor resting beta phenotype is a promising candidate biomarker of sensorimotor function. A prerequisite for use as a biomarker is that it can be quantified reliably across different measurement sessions. Here, using MEG, we assessed the test-retest stability of spontaneously occurring sensorimotor power spectral characteristics, including both aperiodic (1/f) as well as beta band fluctuations ('beta events') in a cohort of 50 healthy human controls. Test-retest reliability across two separate measurement sessions was assessed using the intraclass correlation coefficient (ICC). Beta events were determined using a thresholding-based approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition across a range of parameters (recording length, amplitude threshold and filtering bandwidth). We find that both aperiodic power spectral features as well as several beta event characteristics show good to excellent test-retest stability. Especially aperiodic component power spectral features (ICC 0.77-0.88), but also measures of beta event amplitude (ICC 0.74-0.82) were found to be very stable, while measures of individual beta event duration were less reliable, especially for the left hemisphere (ICC right ~0.7, left ~0.55). Recordings of 2-3 minutes were sufficient to obtain stable results for most parameters. Important for potential clinical applications, automatization of beta event extraction was successful in 86 % of cases. Beta event rate and duration measures were more sensitive to analysis parameters than the measures of event amplitude. The results suggest the sensorimotor beta phenotype is a stable feature of an individual's resting brain activity even for short, 2-3 minute recordings which can be easily measured in patient populations, facilitating its use as a potential clinical biomarker. ### Competing Interest Statement The authors have declared no competing interest.