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Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
Published on: December 18, 2016
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Functional Source Separation-Identified Epileptic Network: Analysis Pipeline
Elzbieta Olejarczyk1, Filippo Zappasodi2, Lorenzo Ricci3
1Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 02-109 Warsaw, Poland.
Brain Sciences
|September 23, 2022
Summary
This study introduces a new pipeline to analyze brain networks in epilepsy. Real transcranial Direct Current Stimulation (tDCS) normalized brain signal complexity in an epilepsy patient.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Epilepsy Research
Background:
- Epileptogenic network identification and neurodynamics analysis are crucial for understanding epilepsy.
- Existing methods lack a comprehensive approach to study network activity and its modulation.
Observation:
- A novel pipeline combining Functional Source Separation (FSS), Higuchi Fractal Dimension (HFD), and Directed Transfer Function (DTF) was developed.
- Data from a single drug-resistant epilepsy patient before and after real and sham transcranial Direct Current Stimulation (tDCS) were analyzed.
Findings:
- Signal complexity of the epileptogenic network, initially reduced, normalized to brain levels after real tDCS.
- Functional connectivity changes observed post-real tDCS persisted for one month.
Implications:
- The developed pipeline offers a valuable tool for understanding brain neurodynamics in epilepsy.
- This approach can enhance insights into the effects of non-invasive brain stimulation on epileptic symptoms.
Keywords:
Directed Transfer Function (DTF)EEGFunctional Source Separation (FSS)Higuchi Fractal Dimension (HFD)focal epilepsytranscranial Direct Current Stimulation (tDCS)
