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Influence of time-series normalization, number of nodes, connectivity and graph measure selection on seizure-onset zone localization from intracranial EEG
- Source :
- BRAIN TOPOGRAPHY, Brain Topography, Brain Topography, Vol. 31, No 5 (2018) pp. 753-766
- Publication Year :
- 2018
-
Abstract
- We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25–35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred. Electronic supplementary material The online version of this article (10.1007/s10548-018-0646-7) contains supplementary material, which is available to authorized users.
- Subjects :
- Male
Multivariate statistics
Computer science
Electroencephalography/methods
02 engineering and technology
Seizure onset zone
Signal-To-Noise Ratio
0302 clinical medicine
Theoretical
Models
Number of connectivity nodes
EPILEPTOGENIC NETWORKS
Radiological and Ultrasound Technology
Functional connectivity
Brain
Seizures/physiopathology
Electroencephalography
Electrodes, Implanted
Causality
Neurology
Area Under Curve
Granger causality
Female
Anatomy
Algorithms
Normalization (statistics)
Adult
FUNCTIONAL BRAIN CONNECTIVITY
Technology and Engineering
0206 medical engineering
Electrocorticography/methods
03 medical and health sciences
Seizures
Humans
Radiology, Nuclear Medicine and imaging
Ictal
Computer Simulation
Time-series normalization
Electrodes
Original Paper
Epilepsy
Intracranial EEG
Brain/physiopathology
business.industry
Pattern recognition
Graph theory
Models, Theoretical
020601 biomedical engineering
Intracranial eeg
ddc:616.8
Multivariate directed functional connectivity
Shortest path problem
PATTERNS
Neurology (clinical)
Artificial intelligence
Implanted
Electrocorticography
business
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 08960267 and 15736792
- Database :
- OpenAIRE
- Journal :
- BRAIN TOPOGRAPHY, Brain Topography, Brain Topography, Vol. 31, No 5 (2018) pp. 753-766
- Accession number :
- edsair.doi.dedup.....e4730619fd493b574cd7bed02be94308