Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity

Wiesman, Alex I.; Castanheira, Jason da Silva; Baillet, Sylvain

doi:10.1016/j.neuroimage.2021.118823

Cited by 32 publications

(42 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, a very recent (2022) publication by Wiesman et al shows that the stability of spectral resting-state MEG measurements can be robustly estimated in most cortical regions when derived from relatively short segments of 30–120 s of resting-state data. We have used a minimum of 5 * 13 s (Wiesman et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

et al. 2022

View full text Add to dashboard Cite

BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.

show abstract

Section: Discussionmentioning

confidence: 99%

State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Noise-cancellation was applied using CTF’s software-based built-in third-order spatial gradient noise filters. Recordings lasted a minimum of 5 min 90 and were conducted with participants in the seated position as they fixated on a centrally-presented crosshair. Participants were monitored during data acquisition via real-time audio-video feeds from inside the shielded room, and continuous head position was recorded for each session.…”

Section: Methodsmentioning

confidence: 99%

Aberrant neurophysiological signaling underlies speech impairments in Parkinson’s disease

Wiesman

Donhauser

Degroot

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Difficulty producing intelligible speech is a common and debilitating symptom of Parkinson's disease (PD). Yet, both the robust evaluation of speech impairments and the identification of the affected brain systems are challenging. We examine the spectral and spatial definitions of the functional neuropathology underlying reduced speech quality in patients with PD using a new approach to characterize speech impairments and a novel brain-imaging marker. We found that the interactive scoring of speech impairments in PD (N=59) is reliable across non-expert raters, and better related to the hallmark motor and cognitive impairments of PD than automatically-extracted acoustical features. By relating these speech impairment ratings to neurophysiological deviations from healthy adults (N=65), we show that articulation impairments in patients with PD are robustly predicted from aberrant activity in the left inferior frontal cortex, and that functional connectivity of this region with somatomotor cortices mediates the influence of cognitive decline on speech deficits.

show abstract

“…The minimum duration of resting-state data across participants was 120 s, so the first two minutes of data were used for all participants. A recent study by Wiesman et al. (2021) showed that spectral properties of intrinsic brain activity can be robustly estimated from such short segments of resting-state data.…”

Section: Methodsmentioning

confidence: 99%

“…More direct measures of neural activity can be obtained by Electroencephalography (EEG) and Magnetoencephalography (MEG), which measure the electromagnetic fields produced by dendritic dipoles within active neurons ( Hari and Puce, 2017 ; Stam, 2010 ). These can be sampled at a resolution of milliseconds, revealing a rich repertoire of neural dynamics, including oscillatory rhythms that occur at frequencies between 2 and 100 Hz, such as “alpha” (8–12 Hz) and “gamma” (30+Hz), some of which have also been implicated in AD ( Engels et al., 2017 ; Giovannetti et al., 2021 ; López-Sanz et al., 2018 ; Mandal et al., 2018 ; Osipova et al., 2005 ; Stam et al., 2009 , 2006 ; Wang et al., 2017 ; Wiesman et al., 2021 ). MEG offers an advantage over EEG in that the magnetic fields are less distorted and smoothed by the brain-skull interface than are electric fields, resulting in higher spatial resolution ( Maestú et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Late combination shows that MEG adds to MRI in classifying MCI versus controls

2022

View full text Add to dashboard Cite

Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity

Cited by 32 publications

References 81 publications

State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

Aberrant neurophysiological signaling underlies speech impairments in Parkinson’s disease

Late combination shows that MEG adds to MRI in classifying MCI versus controls

Contact Info

Product

Resources

About