Neurophysiological biomarkers to optimize deep brain stimulation in movement disorders.

Neurodegener Dis Manag

Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.

Published: August 2021


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Intraoperative neurophysiological information could increase accuracy of surgical deep brain stimulation (DBS) lead placement. Subsequently, DBS therapy could be optimized by specifically targeting pathological activity. In Parkinson's disease, local field potentials (LFPs) excessively synchronized in the beta band (13-35 Hz) correlate with akinetic-rigid symptoms and their response to DBS therapy, particularly low beta band suppression (13-20 Hz) and high frequency gamma facilitation (35-250 Hz). In dystonia, LFPs abnormally synchronize in the theta/alpha (4-13 Hz), beta and gamma (60-90 Hz) bands. Phasic dystonic symptoms and their response to DBS correlate with changes in theta/alpha synchronization. In essential tremor, LFPs excessively synchronize in the theta/alpha and beta bands. Adaptive DBS systems will individualize pathological characteristics of neurophysiological signals to automatically deliver therapeutic DBS pulses of specific spatial and temporal parameters.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8977945PMC
http://dx.doi.org/10.2217/nmt-2021-0002DOI Listing

Publication Analysis

Top Keywords

deep brain
8
brain stimulation
8
dbs therapy
8
lfps excessively
8
beta band
8
symptoms response
8
response dbs
8
synchronize theta/alpha
8
dbs
6
neurophysiological biomarkers
4

Similar Publications

Awake surgery with direct electrical stimulation for safe resection of a deep posterior thalamic cavernous malformation.

Neurochirurgie

September 2025

Neurosurgery Department, Pasteur 2 Hospital, University Hospital of Nice, France; UR2CA PIN, Université Côte d'Azur, France. Electronic address:

Background: Treating symptomatic deep-seated cerebral cavernous malformations (CCMs) is challenging due to surgical risks.

Case Description: A 37-year-old man underwent awake craniotomy with direct electrical stimulation (DES) for excision of a left posterior thalamic CCM. A transcortical transventricular approach through the superior parietal lobe enabled safe navigation around critical associative and projection white matter tracts.

View Article and Find Full Text PDF

Background: Cortico-cortical evoked potentials (CCEPs), elicited via single-pulse electrical stimulation, are used to map brain networks. These responses comprise early (N1) and late (N2) components, which reflect direct and indirect cortical connectivity. Reliable identification of these components remains difficult due to substantial variability in amplitude, phase, and timing.

View Article and Find Full Text PDF

Enhancing reconstruction-based out-of-distribution detection in brain MRI with model and metric ensembles.

Comput Methods Programs Biomed

September 2025

Eindhoven University of Technology, Department of Biomedical Engineering, Medical Image Analysis Group, Eindhoven, The Netherlands. Electronic address:

Background And Objective: Out-of-distribution (OOD) detection is crucial for safely deploying automated medical image analysis systems, as abnormal patterns in images could hamper their performance. However, OOD detection in medical imaging remains an open challenge. In this study, we aim to optimize a reconstruction-based autoencoder specifically for OOD detection.

View Article and Find Full Text PDF

Feature binding in biological and artificial vision.

Trends Cogn Sci

September 2025

Department of Cognitive and Psychological Science, Brown University, Thayer Street, Providence, RI 02906, USA; Robert J. and Nancy D. Carney Institute for Brain Sciences, Brown University, Angell Street, Providence, RI 02906, USA.

View Article and Find Full Text PDF

Brain Tumor Segmentation (BTS) is crucial for accurate diagnosis and treatment planning, but existing CNN and Transformer-based methods often struggle with feature fusion and limited training data. While recent large-scale vision models like Segment Anything Model (SAM) and CLIP offer potential, SAM is trained on natural images, lacking medical domain knowledge, and its decoder struggles with accurate tumor segmentation. To address these challenges, we propose the Medical SAM-Clip Grafting Network (MSCG), which introduces a novel SC-grafting module.

View Article and Find Full Text PDF