Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone.
paper
Cited
Public
Unavailable
- Authors
- De Vos, M; Vergult, A; De Lathauwer, L; De Clercq, W; Van Huffel, S; Dupont, P; Palmini, A; Van Paesschen, W
- Year
- 2007
- Journal
- NeuroImage
- PMID
- 17618128
- DOI
- 10.1016/j.neuroimage.2007.04.041
Long-term electroencephalographic (EEG) recordings are important in the presurgical evaluation of refractory partial epilepsy for the delineation of the irritative and ictal onset zones. In this paper we introduce a new algorithm for an automatic, fast and objective localizing of the ictal onset zone in ictal EEG recordings. We extracted the potential distribution of the ictal activity from EEG using the higher order canonical decomposition method, also referred to as the CP model. The CP model decomposes in a unique way a higher order tensor in a minimal sum of rank-1 'atoms'. We showed that only one atom is related to the seizure activity. Simulation experiments demonstrated that the method correctly extracted the potential distribution of the ictal activity even with low signal-to-noise ratios. In 37 ictal EEGs, the CP method correctly localized the seizure onset zone in 34 (92%) and visual assessment in 21 cases (57%) (p=0.00024). The CP method is a fast method to delineate the ictal onset zone in ictal EEGs and is more sensitive than visual interpretation of the ictal EEGs.
No figures extracted from this document.
No chunks β full text not yet ingested.
No entities extracted from this document yet.
No uploaded files.
Not in any collection.
No citations found.
In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Advances in Electrophysiological Research. | 2015 | 26259089 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| A New Perspective in Epileptic Seizure Classification: Applying the Taxonomy of Seizure Dynamotypes to Noninvasive EEG and Examining Dynamical Changes across Sleep Stages. | Guendelman M et al. | β | 2025 | β |
| A Review of EEG-based Localization of Epileptic Seizure Foci: Common Points with Multimodal Fusion of Brain Data. | Tajmirriahi M et al. | β | 2024 | β |
| Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases. | Li W et al. | β | 2024 | β |
| Tracing Evolving Networks Using Tensor Factorizations vs. ICA-Based Approaches. | Acar E et al. | β | 2022 | β |
| Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data. | Van Eyndhoven S et al. | β | 2021 | β |
| Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG. | Barborica A et al. | β | 2021 | β |
| Improvement in EEG Source Imaging Accuracy by Means of Wavelet Packet Transform and Subspace Component Selection. | Wang D et al. | β | 2021 | β |
| On Koopman mode decomposition and tensor component analysis. | Redman WT | β | 2021 | β |
| Development of temporal lobe epilepsy during maintenance electroconvulsive therapy: A case of human kindling? | Schotte C et al. | β | 2019 | β |
| Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis. | Liu Q et al. | β | 2019 | β |
| Scalable and Robust Tensor Decomposition of Spontaneous Stereotactic EEG Data. | Jian Li et al. | β | 2019 | β |
| Tensor decomposition of TMS-induced EEG oscillations reveals data-driven profiles of antiepileptic drug effects. | Tangwiriyasakul C et al. | β | 2019 | β |
| Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data | Acar E et al. | β | 2019 | β |
| Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data. | Acar E et al. | β | 2019 | β |
| Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection. | Qian D et al. | β | 2017 | β |
| Canonical Polyadic Decomposition With Auxiliary Information for Brain-Computer Interface. | Li J et al. | β | 2017 | β |
| Fine Structure of Posterior Alpha Rhythm in Human EEG: Frequency Components, Their Cortical Sources, and Temporal Behavior. | Barzegaran E et al. | β | 2017 | β |
| The Frontal Area with Higher Frequency Response Is the Principal Feature of Laser-Evoked Potentials in Rats with Chronic Inflammatory Pain: A Parallel Factor Analysis Study. | Wang J et al. | β | 2017 | β |
| Evaluation of Hospitalized Intractable Epileptic Children with SPECT Scan in Ahvaz, South West of Iran. | Momen AA et al. | β | 2016 | β |
| Spectrum of Renal and Urinary Tract Diseases in Kashmiri Children. | Ashraf M et al. | β | 2016 | β |
| Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains. | Onken A et al. | β | 2016 | β |
| Advances in Electrophysiological Research. | Kamarajan C et al. | β | 2015 | β |
| Multiscale entropy analysis of resting-state magnetoencephalogram with tensor factorisations in Alzheimer's disease. | Escudero J et al. | β | 2015 | β |
| Tensor based singular spectrum analysis for automatic scoring of sleep EEG. | Kouchaki S et al. | β | 2015 | β |
| Tensor decomposition of EEG signals: a brief review. | Cong F et al. | β | 2015 | β |
| EEG extended source localization: tensor-based vs. conventional methods. | Becker H et al. | β | 2014 | β |
| Holistic approach for automated background EEG assessment in asphyxiated full-term infants. | Matic V et al. | β | 2014 | β |
| Low-rank approximation based non-negative multi-way array decomposition on event-related potentials. | Cong F et al. | β | 2014 | β |
| Comparison of the AMICA and the InfoMax algorithm for the reduction of electromyogenic artifacts in EEG data. | Leutheuser H et al. | β | 2013 | β |
| Multi-domain feature extraction for small event-related potentials through nonnegative multi-way array decomposition from low dense array EEG. | Cong F et al. | β | 2013 | β |
| Parafac and go/no-go: disentangling CNV return from the P3 complex by trilinear component analysis. | Verleger R et al. | β | 2013 | β |
| Relationship of EEG sources of neonatal seizures to acute perinatal brain lesions seen on MRI: a pilot study. | Despotovic I et al. | β | 2013 | β |
| Single trial ERP reading based on parallel factor analysis. | Vanderperren K et al. | β | 2013 | β |
| Benefits of multi-domain feature of mismatch negativity extracted by non-negative tensor factorization from EEG collected by low-density array. | Cong F et al. | β | 2012 | β |
| Characteristics of evoked potential multiple EEG recordings in patients with chronic pain by means of parallel factor analysis. | Wang J et al. | β | 2012 | β |
| Incorporating structural information from the multichannel EEG improves patient-specific seizure detection. | Hunyadi B et al. | β | 2012 | β |
| Signal subspace integration for improved seizure localization. | Stamoulis C et al. | β | 2012 | β |
| The "why" and "how" of JointICA: results from a visual detection task. | MijoviΔ B et al. | β | 2012 | β |
| Automated artifact removal as preprocessing refines neonatal seizure detection. | De Vos M et al. | β | 2011 | β |
| Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram. | Hassan M et al. | β | 2011 | β |
| Unraveling superimposed EEG rhythms with multi-dimensional decomposition. | Orekhova EV et al. | β | 2011 | β |
| Combining EMD with ICA for extracting independent sources from single channel and two-channel data. | Mijovic B et al. | β | 2010 | β |
| Source separation from single-channel recordings by combining empirical-mode decomposition and independent component analysis. | MijoviΔ B et al. | β | 2010 | β |
| Neonatal seizure localization using PARAFAC decomposition. | Deburchgraeve W et al. | β | 2009 | β |
| Shift-invariant multilinear decomposition of neuroimaging data. | MΓΈrup M et al. | β | 2008 | β |
| Canonical decomposition of ictal scalp EEG and accurate source localisation: principles and simulation study. | De Vos M et al. | β | 2007 | β |