TY - JOUR
T1 - A novel method for extracting interictal epileptiform discharges in multi-channel MEG
T2 - Use of fractional type of blind source separation
AU - Matsubara, Teppei
AU - Hironaga, Naruhito
AU - Uehara, Taira
AU - Chatani, Hiroshi
AU - Tobimatsu, Shozo
AU - Kishida, Kuniharu
N1 - Funding Information:
We thank Dr. J Gotman (Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada) for his important suggestions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (Non-linear Neuro-oscillology: Towards Integrative Understanding of Human Nature, KAKENHI Grant Number 15H05875) from the Ministry of Education, Culture, Sports, Science and Technology, Japan, by the Hara Research Foundation and by the Hans Berger Award from The Japan Epilepsy Society. We thank Benjamin Knight, MSc. from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript. We also thank Associate Prof. Junji Kishimoto (Department of Research and Development of Next Generation Medicine, Faculty of Medical Sciences, Kyushu University) for statistical assistance. None.
Funding Information:
We thank Dr. J Gotman (Montreal Neurological Institute, McGill University , Montreal, Quebec, Canada) for his important suggestions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (Non-linear Neuro-oscillology: Towards Integrative Understanding of Human Nature, KAKENHI Grant Number 15H05875 ) from the Ministry of Education, Culture, Sports, Science and Technology , Japan, by the Hara Research Foundation and by the Hans Berger Award from The Japan Epilepsy Society. We thank Benjamin Knight, MSc., from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript. We also thank Associate Prof. Junji Kishimoto (Department of Research and Development of Next Generation Medicine, Faculty of Medical Sciences , Kyushu University ) for statistical assistance.
Publisher Copyright:
© 2019 International Federation of Clinical Neurophysiology
PY - 2020/2
Y1 - 2020/2
N2 - Objective: Visual inspection of interictal epileptiform discharges (IEDs) in multi-channel MEG requires a time-consuming evaluation process and often leads to inconsistent results due to variability of IED waveforms. Here, we propose a novel extraction method for IEDs using a T/k type of blind source separation (BSST/k). Methods: We applied BSST/k with seven patients with focal epilepsy to test the accuracy of identification of IEDs. We conducted comparisons of the results of BSS components with those obtained by visual inspection in sensor-space analysis. Results: BSST/k provided better signal estimation of IEDs compared with sensor-space analysis. Importantly, BSST/k was able to uncover IEDs that could not be detected by visual inspection. Furthermore, IED components were clearly extracted while preserving spike and wave morphology. Variable IED waveforms were decomposed into one dominant component. Conclusions: BSST/k was able to visualize the spreading signals over multiple channels into a single component from a single epileptogenic zone. BSST/k can be applied to focal epilepsy with a simple parameter setting. Significance: Our novel method was able to highlight IEDs with increased accuracy for identification of IEDs from multi-channel MEG data.
AB - Objective: Visual inspection of interictal epileptiform discharges (IEDs) in multi-channel MEG requires a time-consuming evaluation process and often leads to inconsistent results due to variability of IED waveforms. Here, we propose a novel extraction method for IEDs using a T/k type of blind source separation (BSST/k). Methods: We applied BSST/k with seven patients with focal epilepsy to test the accuracy of identification of IEDs. We conducted comparisons of the results of BSS components with those obtained by visual inspection in sensor-space analysis. Results: BSST/k provided better signal estimation of IEDs compared with sensor-space analysis. Importantly, BSST/k was able to uncover IEDs that could not be detected by visual inspection. Furthermore, IED components were clearly extracted while preserving spike and wave morphology. Variable IED waveforms were decomposed into one dominant component. Conclusions: BSST/k was able to visualize the spreading signals over multiple channels into a single component from a single epileptogenic zone. BSST/k can be applied to focal epilepsy with a simple parameter setting. Significance: Our novel method was able to highlight IEDs with increased accuracy for identification of IEDs from multi-channel MEG data.
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U2 - 10.1016/j.clinph.2019.11.032
DO - 10.1016/j.clinph.2019.11.032
M3 - Article
C2 - 31887614
AN - SCOPUS:85076933802
SN - 1388-2457
VL - 131
SP - 425
EP - 436
JO - Clinical Neurophysiology
JF - Clinical Neurophysiology
IS - 2
ER -