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PubMed Publications| Keyword search (4,163 papers available) |  |
"source imaging" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Sleep magnetoencephalography enhances detection and source imaging of seizures and fast oscillations in focal cortical dysplasia | Heers M; Afnan J; Braun C; Grova C; Altenmüller DM; Steinhoff BJ; Dümpelmann M; Demerath T; Urbach H; Ethofer S; Siegel M; Schulze-Bonhage A; Lerche H; Li Hegner Y; | 41804684 PERFORM |
| 2 | How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG | Wei X; Afnan J; Avigdor T; von Ellenrieder N; Delaire É; Royer J; Ho A; Minato E; Schiller K; Jaber K; Wang YL; Moye M; Bernhardt BC; Lina JM; Grova C; Frauscher B; | 41687693 SOH |
| 3 | EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy | Afnan J; Cai Z; Lina JM; Abdallah C; Delaire E; Avigdor T; Ros V; Hedrich T; von Ellenrieder N; Kobayashi E; Frauscher B; Gotman J; Grova C; | 38994740 SOH |
| 4 | Dynamic networks differentiate the language ability of children with cochlear implants | Koirala N; Deroche MLD; Wolfe J; Neumann S; Bien AG; Doan D; Goldbeck M; Muthuraman M; Gracco VL; | 37409105 PSYCHOLOGY |
| 5 | Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas | Afnan J; von Ellenrieder N; Lina JM; Pellegrino G; Arcara G; Cai Z; Hedrich T; Abdallah C; Khajehpour H; Frauscher B; Gotman J; Grova C; | 37149236 PERFORM |
| 6 | Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy | Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; | 37119580 PERFORM |
| 7 | Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. | Avigdor T, Abdallah C, von Ellenrieder N, Hedrich T, Rubino A, Lo Russo G, Bernhardt B, Nobili L, Grova C, Frauscher B | 33450578 PERFORM |
| 8 | Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter | Hamid L; Habboush N; Stern P; Japaridze N; Aydin Ü; Wolters CH; Claussen JC; Heute U; Stephani U; Galka A; Siniatchkin M; | 33250282 PERFORM |
| 9 | Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients | Pellegrino G, Xu M, Alkuwaiti A, Porras-Bettancourt M, Abbas G, Lina JM, Grova C, Kobayashi E, | 32582009 PERFORM |
| 10 | Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients. | Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E | 32386115 PERFORM |
| 11 | Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. | Heers M, Chowdhury RA, Hedrich T, Dubeau F, Hall JA, Lina JM, Grova C, Kobayashi E | 25609211 PERFORM |
| 12 | Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy. | Grova C, Aiguabella M, Zelmann R, Lina JM, Hall JA, Kobayashi E | 26931511 PERFORM |
| 13 | Source localization of the seizure onset zone from ictal EEG/MEG data. | Pellegrino G, Hedrich T, Chowdhury R, Hall JA, Lina JM, Dubeau F, Kobayashi E, Grova C | 27059157 PERFORM |
| 14 | Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method. | Pellegrino G, Hedrich T, Chowdhury RA, Hall JA, Dubeau F, Lina JM, Kobayashi E, Grova C | 29024165 PERFORM |
| 15 | Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. | Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C | 28619655 PERFORM |
| Title: | Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter | ||||
| Authors: | Hamid L, Habboush N, Stern P, Japaridze N, Aydin Ü, Wolters CH, Claussen JC, Heute U, Stephani U, Galka A, Siniatchkin M | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/33250282/ | ||||
| DOI: | 10.1016/j.cmpb.2020.105830 | ||||
| Publication: | Computer methods and programs in biomedicine | ||||
| Keywords: | Deep sources; Dynamical inverse solution; EEG; EEG inverse problem; EEG source imaging; Electroencephalography; Epilepsy; Epileptiform activity; Kalman filter; LORETA; RSTKF; STKF; Source reconstruction; Spatiotemporal Kalman filter; State space; Subcortical sources; | ||||
| PMID: | 33250282 | Category: | Date Added: | 2020-11-30 | |
| Dept Affiliation: |
PERFORM
1 Department of Medical Psychology and Medical Sociology, University of Kiel, D-24113 Kiel, Germany. Electronic address: laithalajeel@gmail.com. 2 Department of Medical Psychology and Medical Sociology, University of Kiel, D-24113 Kiel, Germany. 3 Institute of Theoretical Physics and Astrophysics, University of Kiel, D-24098 Kiel, Germany. 4 Department of Neuropediatrics, University of Kiel, D-24098 Kiel, Germany. 5 Institute for Biomagnetism and Biosignalanalysis, University of Münster, D-48149 Münster, Germany; Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Canada. 6 Institute for Biomagnetism and Biosignalanalysis, University of Münster, D-48149 Münster, Germany. 7 Institute of Theoretical Physics and Astrophysics, |
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Description: |
Background and objective: The human brain displays rich and complex patterns of interaction within and among brain networks that involve both cortical and subcortical brain regions. Due to the limited spatial resolution of surface electroencephalography (EEG), EEG source imaging is used to reconstruct brain sources and investigate their spatial and temporal dynamics. The majority of EEG source imaging methods fail to detect activity from subcortical brain structures. The reconstruction of subcortical sources is a challenging task because the signal from these sources is weakened and mixed with artifacts and other signals from cortical sources. In this proof-of-principle study we present a novel EEG source imaging method, the regional spatiotemporal Kalman filter (RSTKF), that can detect deep brain activity. Methods: The regional spatiotemporal Kalman filter (RSTKF) is a generalization of the spatiotemporal Kalman filter (STKF), which allows for the characterization of different regional dynamics in the brain. It is based on state-space modeling with spatially heterogeneous dynamical noise variances, since models with spatial and temporal homogeneity fail to describe the dynamical complexity of brain activity. First, RSTKF is tested using simulated EEG data from sources in the frontal lobe, putamen, and thalamus. After that, it is applied to non-averaged interictal epileptic spikes from a presurgical epilepsy patient with focal epileptic activity in the amygdalo-hippocampal complex. The results of RSTKF are compared to those of low-resolution brain electromagnetic tomography (LORETA) and of standard STKF. Results: Only RSTKF is successful in consistently and accurately localizing the sources in deep brain regions. Additionally, RSTKF shows improved spatial resolution compared to LORETA and STKF. Conclusions: RSTKF is a generalization of STKF that allows for accurate, focal, and consistent localization of sources, especially in the deeper brain areas. In contrast to standard source imaging methods, RSTKF may find application in the localization of the epileptogenic zone in deeper brain structures, such as mesial frontal and temporal lobe epilepsies, especially in EEG recordings for which no reliable averaged spike shape can be obtained due to lack of the necessary number of spikes required to reach a certain signal-to-noise ratio level after averaging. |
