Brain Recording Analysis and Visualization Online (BRAVO): An open-source visualization tool for deep brain stimulation data

Jackson N. Cagle, Kara A. Johnson, Leonardo Almeida, Joshua K. Wong, Adolfo Ramirez-Zamora, Michael S. Okun, Kelly D. Foote, Coralie de Hemptinne

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: Deep brain stimulation (DBS) devices with neural recording capabilities are commercially available and may potentially improve clinical care and advance research. However, tools, to visualize neural recording data have been limited. These tools in general, require custom-made software for processing and analysis. The development of new tools will be critical for clinicians and researchers to fully leverage the latest device capabilities. Objective: There is an urgent need for a user-friendly tool for in-depth visualization and analysis of brain signals and of DBS data. Methods and results: The Brain Recording Analysis and Visualization Online (BRAVO) platform was developed to easily import, visualize, and analyze brain signals. This Python-based web interface has been designed and implemented on a Linux server. The tool processes the session files from DBS programming generated by a clinical ‘programming’ tablet. The platform is capable of parsing and organizing neural recordings for longitudinal analysis. We present the platform and cases exemplifying its application and use. Conclusion: The BRAVO platform is an accessible easy-to-use, open-source web interface for clinicians and researchers to apply for analysis of longitudinal neural recording data. The tool can be used for both clinical and research applications.

Original languageEnglish (US)
Pages (from-to)793-797
Number of pages5
JournalBrain Stimulation
Issue number3
StatePublished - May 1 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 The Authors


  • Data visualization
  • Deep brain stimulation
  • Local field potentials
  • Online platform
  • Software

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't


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