ArticleImaging neuroscience (Cambridge, Mass.)2024
The GLM-spectrum: A multilevel framework for spectrum analysis with covariate and confound modelling.
Article in Imaging neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Individual cases of Parkinson's disease can be robustly classified using magnetoencephalography.NPJ Parkinson's disease · 2026Article
- Varying patterns of association between cortical large-scale networks and subthalamic nucleus activity in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Divergence of cortical neurophysiology across different neurodegenerative disorders compared to healthy ageing.Progress in neurobiology · 2026Article
- Stroke recovery beyond initial severity: the complementary roles of brain structure and brain function in acute stroke.Brain communications · 2026Article
- MEG state dynamics of sentence generation: evidence for a compensatory segmentation mechanism in healthy aging.Frontiers in computational neuroscience · 2026Article
- Divergent Brain Network Activity in Asymptomatic C9orf72 and SOD1 Variant Carriers Compared With Established Amyotrophic Lateral Sclerosis.Human brain mapping · 2025Article
- Higher baseline alpha power is associated with faster responses in visual search.bioRxiv : the preprint server for biology · 2025Article
- Guided visual search is associated with target boosting and distractor suppression in early visual cortex.Communications biology · 2025Article
- Current and Future Spatial Distribution of theInsects · 2025Article
- BSD: A Bayesian Framework for Parametric Models of Neural Spectra.The European journal of neuroscience · 2025Article
- Temporal autocorrelation is predictive of age-An extensive MEG time-series analysis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Human motor cortical gamma activity relates to GABAergic intracortical inhibition and motor learning.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- osl-ephys: a Python toolbox for the analysis of electrophysiology data.Frontiers in neuroscience · 2025Article
- Functional magnetic resonance spectroscopy of prolonged motor activation using conventional and spectral GLM analyses.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Combining video telemetry and wearable MEG for naturalistic imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Reduced beta bursting underpins loss of corticomuscular coherence in amyotrophic lateral sclerosis.Brain communications · 2025Article
- Comparison between EEG and MEG of static and dynamic resting-state networks.Human brain mapping · 2024Article
- Article
- Modelling variability in functional brain networks using embeddings.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The frequency spectrum is a central method for representing the dynamics within electrophysiological data. Some widely used spectrum estimators make use of averaging across time segments to reduce noise in the final spectrum. The core of this approach has not changed substantially since the 1960s, though many advances in the field of regression modelling and statistics have been made during this time. Here, we propose a new approach, the General Linear Model (GLM) Spectrum, which reframes time averaged spectral estimation as multiple regression. This brings several benefits, including the ability to do confound modelling, hierarchical modelling, and significance testing via non-parametric statistics. We apply the approach to a dataset of EEG recordings of participants who alternate between eyes-open and eyes-closed resting state. The GLM-Spectrum can model both conditions, quantify their differences, and perform denoising through confound regression in a single step. This application is scaled up from a single channel to a whole head recording and, finally, applied to quantify age differences across a large group-level dataset. We show that the GLM-Spectrum lends itself to rigorous modelling of within- and between-subject contrasts as well as their interactions, and that the use of model-projected spectra provides an intuitive visualisation. The GLM-Spectrum is a flexible framework for robust multilevel analysis of power spectra, with adaptive covariate and confound modelling.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.