Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Optimization of Docetaxel-Zedoary Turmeric Oil Magnetic Solid Lipid Nanoparticle Preparation by Central Composite Design-Response Surface Methodology.

Assay and drug development technologies·2025
Same author

Tumor Mutation Signature Reveals the Risk Factors of Lung Adenocarcinoma with <i>EGFR</i> or <i>KRAS</i> Mutation.

Cancer control : journal of the Moffitt Cancer Center·2025
Same author

A comprehensive analysis of vasculogenic mimicry related genes to predict the survival rate of HCC and its influence on the tumor microenvironment.

Frontiers in genetics·2025
Same author

Identification and knockout of rhamnose synthase CiRHM1 enhances accumulation of flavone aglycones in chrysanthemum flower.

Plant biotechnology journal·2024
Same author

Constructing Quasi-Localized High-Concentration Solvation Structures to Stabilize Battery Interfaces in Nonflammable Phosphate-Based Electrolyte.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2024
Same author

Low- and Intermediate-Grade Lateral Sinus Dural Arteriovenous Fistulas: Factors Affecting the Outcome of Endovascular Treatment over 18-Year Experience in a High-Volume Neurovascular Center.

AJNR. American journal of neuroradiology·2024
Same journal

Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.

Frontiers in neuroinformatics·2026
Same journal

Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinson's disease screening.

Frontiers in neuroinformatics·2026
Same journal

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease.

Frontiers in neuroinformatics·2026
Same journal

A 3D-printed phantom to validate subject orientation in 3D imaging and recordings.

Frontiers in neuroinformatics·2026
Same journal

IntegriLAB: a blockchain-enabled electronic lab notebook for reproducible neuroimaging research.

Frontiers in neuroinformatics·2026
Same journal

Long-range correlations in alpha-band of electroencephalogram: a nonlinear embedding and detrended fluctuation analysis.

Frontiers in neuroinformatics·2026
See all related articles

Related Experiment Video

Updated: Oct 5, 2025

Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

21.5K

BrainQuake: An Open-Source Python Toolbox for the Stereoelectroencephalography Spatiotemporal Analysis.

Fang Cai1, Kang Wang1, Tong Zhao1

  • 1Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.

Frontiers in Neuroinformatics
|January 24, 2022
PubMed
Summary
This summary is machine-generated.

BrainQuake is a new open-source Python software for analyzing intracranial stereoelectroencephalography (SEEG) data. It offers an end-to-end solution for presurgical epilepsy evaluation, streamlining complex workflows for neurosurgeons and researchers.

Keywords:
Epileptogenicity IndexHough Transformelectrode localizationepilepsyinterictal high-frequency oscillationstereoelectroencephalography

More Related Videos

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

2.3K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.2K

Related Experiment Videos

Last Updated: Oct 5, 2025

Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

21.5K
Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

2.3K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.2K

Area of Science:

  • Neuroscience
  • Medical Imaging
  • Computational Biology

Background:

  • Intracranial stereoelectroencephalography (SEEG) is crucial for presurgical evaluation of intractable epilepsy, offering high temporal and spatial resolution.
  • Current SEEG post-processing involves multimodal data integration (MRI, CT, EEG) and complex workflows like surface reconstruction and electrode localization.
  • Existing software solutions often lack an integrated, end-to-end approach for comprehensive SEEG analysis.

Purpose of the Study:

  • To introduce BrainQuake, an open-source Python software designed for end-to-end SEEG spatiotemporal analysis.
  • To provide neurosurgeons and researchers with an automated, user-friendly platform for SEEG data processing and seizure onset zone prediction.
  • To facilitate collaboration and efficient data management through remote server communication and standardized pipelines.

Main Methods:

  • Development of an integrated software package, BrainQuake, in Python.
  • Implementation of automated modules for brain surface reconstruction, electrode contact localization, and SEEG data analysis.
  • Integration of seizure onset zone (SOZ) prediction algorithms based on ictal and interictal SEEG data.
  • Inclusion of a graphical user interface (GUI) for user-friendliness and remote server communication capabilities.

Main Results:

  • BrainQuake offers a comprehensive, automated workflow for SEEG analysis from surface reconstruction to SOZ prediction.
  • The software integrates multimodal data processing with a user-friendly GUI, simplifying complex neurosurgical workflows.
  • Remote communication features enable standardized preprocessing, high-performance computing, and data management, saving time for clinicians and researchers.

Conclusions:

  • BrainQuake provides a novel, open-source, end-to-end solution for SEEG spatiotemporal analysis in epilepsy presurgical evaluation.
  • The software's automation, GUI, and remote capabilities enhance efficiency and accessibility for neurosurgeons and researchers.
  • BrainQuake represents a significant advancement in computational tools for epilepsy research and clinical practice.