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Local Field Potential Recordings Using Deep Brain Stimulation: A Practical Workflow and Open-Source Signal Processing

Albert Guillemette^1,2,3,4,5, Marc-Antoine Gobeil^2,5, Adan-Ulises Dominguez-Vargas^3,4,6

¹Département de Pharmacologie et Physiologie, Faculté de Médecine, Université de Montréal, Montreal, Qc, Canada.

Brain Topography

|June 28, 2026

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Summary

This study introduces BrainWave-DBS, an open-source pipeline for analyzing local field potentials (LFP) from deep brain stimulation (DBS) systems. It simplifies LFP data processing for adaptive neuromodulation and Parkinson's disease research.

Area of Science:

Neuroscience
Biomedical Engineering

Background:

Deep brain stimulation (DBS) systems can record local field potentials (LFP) for neural monitoring.
Translating raw LFP data into clinical biomarkers is complex due to technical challenges.

Purpose of the Study:

To provide a practical guide and an open-source pipeline (BrainWave-DBS) for LFP data analysis.
To facilitate the development of adaptive neuromodulation strategies using chronic LFP recordings.

Main Methods:

Developed BrainWave-DBS, an open-source pipeline for LFP data import, preprocessing, spectral analysis, and visualization.
Created a practical guide for conducting LFP experiments.
Validated the pipeline using a Parkinson's disease dataset.

Main Results:

Keywords:

Closed loop Deep Brain Stimulation Local Field Potentials Parkinson’s Disease Signal Processing

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The BrainWave-DBS pipeline offers a reproducible framework for analyzing patient-derived LFP data.
Key technical insights for LFP acquisition and analysis were identified.
Demonstrated pipeline functionality with a Parkinson's disease dataset.

Conclusions:

BrainWave-DBS enhances access to neural signal acquisition and analysis.
The pipeline aims to foster broader adoption of LFP analysis for advanced neuromodulation.
This work supports the advancement of closed-loop neuromodulation in deep brain structures.