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Updated: Jan 20, 2026
12:09
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
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Computation of Brain Functional Connectivity Network Measures in Epilepsy: A Web-Based Platform for EEG Signal Data
Vimig Socrates1,2, Arthur Gershon1, Satya S Sahoo1,2
1Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
Studies in Health Technology and Informatics
|August 24, 2019
Summary
This study introduces a web application for analyzing epilepsy seizure networks using Stereotactic Electroencephalogram (SEEG) data. The tool efficiently processes large datasets, aiding neuroscientists in understanding brain network function in epilepsy.
Area of Science:
- Neuroscience
- Computational Biology
- Medical Informatics
Background:
- Epilepsy affects 60 million worldwide, characterized by recurrent seizures.
- Functional brain network analysis is crucial for understanding epileptogenic networks.
- Graph theory offers methods for analyzing complex brain networks.
Purpose of the Study:
- To develop a web-based application for processing high-resolution Stereotactic Electroencephalogram (SEEG) data.
- To enable computation of signal coupling measures for epilepsy seizure network studies.
- To provide an intuitive user interface for neuroscientists.
Main Methods:
- Development of a web-based application.
- Processing of high-resolution Stereotactic Electroencephalogram (SEEG) signal data.
- Computation of signal coupling measures using graph theoretic approaches.
- Systematic evaluation of application scalability.
Main Results:
- The developed web application successfully processes SEEG data.
- The application computes various signal coupling measures.
- Scalability testing confirmed the application handles increasing data volumes efficiently.
Conclusions:
- The new web application is a valuable tool for neuroscientists studying epilepsy.
- It facilitates the analysis of functional brain networks in epilepsy using SEEG data.
- The application demonstrates efficient data processing and scalability for research.
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