ArticleFrontiers in aging neuroscience2016
Identifying Dysfunctional Cortex: Dissociable Effects of Stroke and Aging on Resting State Dynamics in MEG and fMRI.
Article in Frontiers in aging neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04375722 (Exogenous Tuning of Neural Oscillations as a Mode of Treatment in Post-stroke Aphasia), which is not on this map. Cited by 39 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Exogenous Tuning of Neural Oscillations as a Mode of Treatment in Post-stroke Aphasia
Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Exploring Representation of Diverse Samples in fMRI Studies Conducted in Patients With Cardiac-Related Chronic Illness: A Focused Systematic Review.Frontiers in human neuroscience · 2020Pooled it
- Dynamic Recovery: GABA Agonism Restores Neural Variability in Older, Poorer Performing Adults.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Trial
- Brain signal variability during rest as a neural mechanism underlying cognitive reserve.NeuroImage · 2026Article
- White Matter Infarct Detection with Transformer and Auto-ML-Derived Models.Brain sciences · 2026Article
- Decreased BOLD Signal Variability in Middle-Aged and Older Adults on the Autism Spectrum.Autism research : official journal of the International Society for Autism Research · 2026Article
- The Philadelphia Theta Burst Project: A novel fMRI-guided electric field modeling dataset with reliability metrics.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Enhancing cerebral infarct classification by automatically extracting relevant fMRI features.Brain informatics · 2025Article
- The curious case of the Cat Rescue: can picture narrative description inform visuospatial processing in aphasia?Frontiers in human neuroscience · 2025Article
- Exploring the feasibility of EEG for pre-hospital detection of medium and large vessel occlusion strokes: a proof-of-concept study.Frontiers in neurology · 2025Article
- Altered spontaneous brain activity in patients with progressive-stage and end-stage chronic kidney disease: insights from dALFF analysis.Metabolic brain disease · 2024Article
- Secondary thalamic dysfunction underlies abnormal large-scale neural dynamics in chronic stroke.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Altered static and dynamic spontaneous brain activity in patients with dysthyroid optic neuropathy: a resting-state fMRI study.Frontiers in neuroscience · 2024Article
- Neural variability in three major psychiatric disorders.Molecular psychiatry · 2023Article
- Altered dynamic brain activity and functional connectivity in thyroid-associated ophthalmopathy.Human brain mapping · 2023Article
- Targeted neurorehabilitation strategies in post-stroke aphasia.Restorative neurology and neuroscience · 2023Review
- Assessing blood oxygen level-dependent signal variability as a biomarker of brain injury in sport-related concussion.Brain communications · 2023Article
- Spectral slowing in chronic stroke reflects abnormalities in both periodic and aperiodic neural dynamics.NeuroImage. Clinical · 2023Article
- Altered directional functional connectivity underlies post-stroke cognitive recovery.Brain communications · 2023Article
- Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence.Frontiers in aging neuroscience · 2023Review
- The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment.Frontiers in human neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spontaneous signals in neuroimaging data may provide information on cortical health in disease and aging, but the relative sensitivity of different approaches is unknown. In the present study, we compared different but complementary indicators of neural dynamics in resting-state MEG and BOLD fMRI, and their relationship with blood flow. Participants included patients with post-stroke aphasia, age-matched controls, and young adults. The complexity of brain activity at rest was quantified in MEG using spectral analysis and multiscale entropy (MSE) measures, whereas BOLD variability was quantified as the standard deviation (SDBOLD), mean squared successive difference (MSSD), and sample entropy of the BOLD time series. We sought to assess the utility of signal variability and complexity measures as markers of age-related changes in healthy adults and perilesional dysfunction in chronic stroke. The results indicate that reduced BOLD variability is a robust finding in aging, whereas MEG measures are more sensitive to the cortical abnormalities associated with stroke. Furthermore, reduced complexity of MEG signals in perilesional tissue were correlated with hypoperfusion as assessed with arterial spin labeling (ASL), while no such relationship was apparent with BOLD variability. These findings suggest that MEG signal complexity offers a sensitive index of neural dysfunction in perilesional tissue in chronic stroke, and that these effects are clearly distinguishable from those associated with healthy aging.
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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.