Evidence map›Paper›PMID 40606835›Full record

ArticleFrontiers in neuroscience2025

Dominant twin peaks: a novel conjecture for the pathophysiologic basis of tremor frequency and fluctuation time in Parkinson's disease.

Furrukh Khan, David Novikov, Brian Dalm, Jessie Xiaoxi, Oliver Flouty, Evan Thomas

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. From continuous to adaptive deep brain stimulation: Personalized modulation improves motor complications and sleep in Parkinson's Disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Furrukh KhanDepartment of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States.
David NovikovDepartment of Computer Science and Engineering, The Ohio State University, Columbus, OH, United States.
Brian DalmDepartment of Neurosurgery, The Ohio State University, Columbus, OH, United States.
Jessie XiaoxiDepartment of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States.
Oliver FloutyDepartment of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, United States.
Evan ThomasDepartment of Radiation Oncology, The Ohio State University, Columbus, OH, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the commercial availability of deep brain stimulation neurostimulators and sensing leads capable of recording deep brain Local Field Potentials, researchers now commonly study the spectral characteristics of Local Field Potentials recorded from the subthalamic nucleus of patients with Parkinson's disease. Correlating subthalamic synchronized oscillatory activity with motor impairment in Parkinson's disease patients has recently gained attention in the literature. Objective: Based on the deep brain recordings of a Parkinson's disease patient our objective is to (i) Use actual measurements of the patient's tremor to support a hypothesis that connects the features of the Local Field Potential's beta-band spectrum (13-31 Hz), with the lower frequency (4-8 Hz) features of the patient's tremor, such as tremor frequency and tremor fluctuation time and (ii) Justify the hypothesis through theoretical reasoning based on communication theory in Electrical Engineering. Methods: Tremor characteristics (i.e., tremor frequency and tremor fluctuation time) derived from limb coordinate time-series were obtained from a video of the patient by using Google's MediaPipe Artificial Intelligence Framework. Spectra of the deep brain recordings and measured tremor time-series were analyzed using the Fast Fourier Transform. Burst trains in the deep brain signals and tremor bursts in the measured tremor signal were investigated by using Continuous Wave Transform scalograms. Results: Support for the hypothesis is provided by a close agreement between the measured results of the tremor (from a patient's video) and the predictions of the hypothesis based on the Local Filed Potential deep brain spectrum. We show that the defining features in the scalogram obtained from the deep brain signal are directly related to the features in the scalogram of the measured tremor. We provide a theoretical justification of the hypothesis by relating features of the deep brain beta-bursts, seen in the Local Field Potential scalogram, to a pair of beta-band dominant peaks found in the spectrum of the deep brain signal by leveraging the phenomena of "beating" (amplitude modulation) from communications theory. Conclusion: We conclude that tremor properties of a Parkinson's disease patient, like tremor frequency and tremor fluctuation duration, can be obtained from the patient's subthalamic nucleus beta-band spectrum.

Indexed as

deep brain stimulationfunctional neurosurgery borderlocal field potentialsParkinson’s diseasesubthalamic nucleustremor frequency

Identifiers

PMID40606835
PMCPMC12213638

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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.