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PubMed Publications| Keyword search (4,163 papers available) |  |
"electroencephalography" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking | Gagné N; Greenlaw KM; Coffey EBJ; | 40412301 PSYCHOLOGY |
| 2 | Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains | Cross N; O' Byrne J; Weiner OM; Giraud J; Perrault AA; Dang-Vu TT; | 40214027 PERFORM |
| 3 | PreVISE: an efficient virtual reality system for SEEG surgical planning | Spiegler P; Abdelsalam H; Hellum O; Hadjinicolaou A; Weil AG; Xiao Y; | 39735694 ENCS |
| 4 | Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology | Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B; | 39608298 SOH |
| 5 | A protocol for trustworthy EEG decoding with neural networks | Borra D; Magosso E; Ravanelli M; | 39549492 ENCS |
| 6 | SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals | Borra D; Paissan F; Ravanelli M; | 39265481 ENCS |
| 7 | The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study | Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; | 37675803 CONCORDIA |
| 8 | 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 |
| 9 | Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data | Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; | 37385392 IMAGING |
| 10 | 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 |
| 11 | Electroencephalographic characteristics of children and adolescents with chronic musculoskeletal pain | Ocay DD; Teel EF; Luo OD; Savignac C; Mahdid Y; Blain-Moraes S; Ferland CE; | 36601627 HKAP |
| 12 | Alpha and beta neural oscillations differentially reflect age-related differences in bilateral coordination | Shih PC; Steele CJ; Nikulin VV; Gundlach C; Kruse J; Villringer A; Sehm B; | 33979705 PSYCHOLOGY |
| 13 | 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 |
| 14 | PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research | Parent M; Albuquerque I; Tiwari A; Cassani R; Gagnon JF; Lafond D; Tremblay S; Falk TH; | 33363449 PERFORM |
| 15 | 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 |
| 16 | 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 |
| 17 | Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia | Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; | 29157588 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. |
