ReviewExperimental brain research2022
Novel approaches for quantifying beta synchrony in Parkinson's disease.
Review in Experimental brain research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 15 citations in OpenAlex.
- Cortical beta power modulation is asymmetric and reduced during movement execution and inhibition in Parkinson's disease.Neurobiology of disease · 2025Article
- Non-invasive brain stimulation to modulate neural activity in Parkinson's disease.NPJ Parkinson's disease · 2025Review
- Medication improves velocity, reaction time, and movement time but not amplitude or error during memory-guided reaching in Parkinson's disease.Physiological reports · 2024Article
- Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease.Brain : a journal of neurology · 2023Article
- Contribution of inter-trial phase coherence at theta, alpha, and beta frequencies in auditory change detection.Frontiers in 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
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30 Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50 Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.
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.