# Exploring the impact of statistical methods for defining "sweet spots" in Deep Brain Stimulation

Vittoria Bucciarelli, Dorian Vogel, Marc Stawiski, Teresa Nordin, Karin Wardell, Jerome Coste, Jean-Jacques Lemaire, Simone Hemm-Ode

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## To cite this version:

Vittoria Bucciarelli, Dorian Vogel, Marc Stawiski, Teresa Nordin, Karin Wardell, et al. Exploring the impact of statistical methods for defining "sweet spots" in Deep Brain Stimulation. 11th Neuro-Engineering Workshop, Nov 2024, Linkoping, Sweden. 2024. [hal-04781591](https://uca.hal.science/hal-04781591v1)

HAL Id: hal-04781591

https://uca.hal.science/hal-04781591v1

Submitted on 20 Nov 2024

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# Exploring the impact of statistical methods for defining “sweet spots” in Deep Brain Stimulation

Bucciarelli V.¹, Vogel D.¹, Stawiski M. ¹, Nordin T.², Wårdell K.², Coste J.³, Lemaire JJ.⁴, Hemm S.¹, ²

## Introduction

* The precise location of the so-called Sweet spot (SS) or optimal target, for Deep Brain Stimulation (DBS) is still under investigation.
* Sweet spots can be generated by statistical analysis of patients' stimulation data.
* A comprehensive evaluation of the chosen statistical method's impact on the extracted sweet spot is still lacking.
* Aim: We applied six statistical methods to DBS patients' data and compared their outcomes.

## Materials and Methods

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FDR: False Discovery Rate

## Results

The statistical analyses revealed sweet spots of varying sizes for both hemispheres. The figure shows the results obtained for the left hemisphere superimposed to the patient's MRI and some anatomical structures.

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## Discussion and Conclusions

* The chosen statistical method strongly influences size and position of the extracted sweet spot in group analysis.

* Bayes, Tperm and WilcPerm generated sweet spots in realistic anatomical positions. Bayes also demonstrated higher robustness to input dataset variations.

## Acknowledgments

This work was financed by the Swiss National Science Foundation.

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**Contact:**
Vittoria Bucciarelli
FHNW, IM2, Neuroengineering group
4132 Muttenz, Switzerland
vittoria.bucciarelli@fhnw.ch

**Affiliations:**
¹Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
²Department of Biomedical Engineering, Linköping University, Linköping, Sweden
³Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal, Université Clermont Auvergne, Clermont Auvergne INP Clermont-Ferrand, France
⁴Université Clermont Auvergne, CNRS, CHU Clermont-Ferrand, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand, France

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Swiss National
Science Foundation

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UCA
Universität
Basel