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. 2025 Mar;32(3):e70098.
doi: 10.1111/ene.70098.

Genetic Etiology Influences the Low-Frequency Components of Globus Pallidus Internus Electrophysiology in Dystonia

Ahmet Kaymak  1   2 , Luigi M Romito  3 , Fabiana Colucci  3   4 , Nico Golfrè Andreasi  3 , Roberta Telese  3 , Sara Rinaldo  3 , Vincenzo Levi  5 , Giovanna Zorzi  6 , Zvi Israel  7   8 , David Arkadir  8   9 , Hagai Bergman  7   10   11 , Miryam Carecchio  12 , Holger Prokisch  13   14 , Michael Zech  13   14   15 , Barbara Garavaglia  16 , Alberto Mazzoni  1   2 , Roberto Eleopra  3
Affiliations

Genetic Etiology Influences the Low-Frequency Components of Globus Pallidus Internus Electrophysiology in Dystonia

Ahmet Kaymak et al. Eur J Neurol. 2025 Mar.

Abstract

Background: Elevated low-frequency activity (4-12 Hz) within the globus pallidus internus (GPi) has been consistently associated with dystonia. However, the impacts of the genetic etiology of dystonia on low-frequency GPi activity remain unclear; yet it holds importance for adaptive deep brain stimulation (DBS) treatment.

Methods: We compared the properties of GPi electrophysiology acquired from 70 microelectrode recordings (MER) trajectories of DYT-GNAL, DYT-KMT2B, DYT-SGCE, DYT-THAP1, DYT-TOR1A, DYT-VPS16, and idiopathic dystonia (iDYT) patients who underwent GPi-DBS surgery across standard frequency bands.

Results: DYT-SGCE patients exhibited significantly lower alpha band activity (2.97%) compared to iDYT (4.44%, p = 0.006) and DYT-THAP1 (4.51%, p = 0.011). Additionally, theta band power was also significantly reduced in DYT-SGCE (4.42%) compared to iDYT and DYT-THAP1 (7.91% and 7.00%, p < 0.05). Instead, the genetic etiology of dystonia did not affect the spatial characteristics of GPi electrophysiology along MER trajectories.

Conclusion: Considering the genetic etiology of dystonia in closed-loop DBS treatments and utilizing theta and alpha activity for GPi stimulation may optimize clinical outcomes. MER-based DBS lead placement can proceed independently of the underlying genetic cause.

Keywords: alpha oscillations; deep brain stimulation; dystonia; electrophysiology; genetics.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Electrophysiological characterization of power spectral properties of GPi for genetic and idiopathic dystonia syndromes. (A) Reconstruction of MER trajectories in MNI space, color‐coded according to genetic etiology. (B) Statistical comparison of power spectral features was performed with Dunn's test with Holm–Bonferroni correction; significant results are indicated by color coding. (C) Box plots displaying the distributions of theta and alpha power fraction across dystonia groups. (D) Correlation matrix depicting linear relationship between spectral and clinical features, as determined by Spearman's correlation coefficient. The magnitude of each correlation score is indicated by the size and color of the marker. Regression plots highlight significant correlations between selected feature pairs, with scatter color‐coded based on the genetic etiology. (E) Heatmap showing the correlation between normalized depth levels and electrophysiological features across patient groups. Regression plots depict the behavior of selected electrophysiological features along normalized depth levels, with the degree of correlation indicated by Spearman's correlation coefficient.
See this image and copyright information in PMC

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