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研究生(外文):Shu-Yu Huang
論文名稱(外文):A method of concurrent high quality measurement of hemodynamic and electrophysiological signals of the human brain
指導教授(外文):Hsiao-Wen ChungFa-Hsuan Lin
口試委員(外文):Wen-Jui KuoShang-Yueh TsaiTeng-Yi Huang
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腦電圖以及功能性核磁共振影像都是非侵入式神經顯影方式,它們分別提供了毫秒等級的時間解析度的神經反應以及毫米等級的空間解析度。在測量兩者資料時,可以是分開量測或同時量測。在實驗需要特別排除因記憶或學習效應造成的影響時,同時量測腦電圖和功能性磁振影像可以排除因兩次量測間差異造成的偏差。可是在同時收錄腦電圖及功能性磁振影像時腦電圖會受到在高磁場下的心搏產生的心搏假影及梯度線圈開關產生的梯度假影劇烈影響。因梯度假影的大小百倍於神經反應,並且梯度假影對受試者移動敏感,在經過信號處理減除梯度假影後,其殘值仍會影響腦電圖的品質。為降低梯度假影影響,我們提出將快速的simultaneous multi-slice inverse imaging(SMS-InI)序列和腦電圖間歇掃描。可預期在沒有掃描的區間(每2秒鐘內的1.9秒)可以提升腦電圖的品質,同時SMS-InI也維持與傳統Echo Planar Image(EPI)同等級的靈敏度及空間解析度。經由時頻分析我們知道使用傳統EPI序列造成的梯度假影會在固定頻率有最大的影響,所以我們激發15赫茲穩態視覺相關電位以比較間歇同時量測SMS-InI的腦電圖與同時量測傳統EPI的腦電圖及的品質。我們使用SMS-InI及腦電圖的間歇掃描量測到可以與在磁振造影室外量測的腦電圖相比的15赫茲穩態視覺相關電位以及可以與EPI相提並論的血動力反應圖。此種間歇式掃描腦電圖及SMS-InI 可適用於對腦電圖品質較有要求的實驗,例如讓功能性磁振影像使用發作間期癲癇樣放電(inter-ictal discharges, IID)時間點定位癲癇病患在大腦中激發放電的位置。
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be combined to provide millisecond resolution and millimeter resolution of neuronal and hemodynamic activity. EEG and fMRI can be recorded concurrently or separately for data integration. In experiments considering memory or learning effects, concurrent EEG-fMRI is preferable to avoid bias due to separate measurements. In concurrent EEG-MRI recording, EEG is heavily distorted by pulse artifacts, which are caused by heartbeats in a strong magnetic field, and gradient artifacts, which are caused by repetitive gradient coil switching during MRI acquisition. Because GA is hundreds times larger than typical evoked neuronal responses and GA is very sensitive to movements, the residue of GA after GA suppression can significantly degrade EEG quality.
We propose to interleave simultaneous multi-slice inverse imaging (SMS-InI) concurrently with EEG. In this way, EEG recorded with gradient-artifact-free intervals (1.9-s in every 2-s) is expected to have high quality, while SMS-InI provides comparable sensitivity and spatiotemporal resolution like EPI. We used SMS-InI-EEG to measure 15-Hz steady-state visual evoked potentials comparable with EEG recorded outside MRI and the hemodynamic responses comparable with EPI. The interleaved SMS-InI-EEG can be applied to measurements sensitive to EEG quality, such as localizing irritative zones of inter-ictal discharges (IID) in epilepsy patients using fMRI based on IID timing.
論文審定書 #
Acknowledgment 1
中文摘要 2
Abstract 3
List of Figures 6
List of Tables 6
Chapter 1. Introduction 7
Chapter 2. Methods 14
2-1. MRI acquisition 14
2-2. EEG acquisition 16
2-3. Participant and Instructions 16
2-4. EEG preprocessing 17
2-5. EEG source estimation 18
2-6. Functional MRI preprocessing 19
2-7. EEG evaluation 19
2-8. Data analysis of EPI and SMS-InI 20
Chapter 3. Results 22
3-1. EEG results 22
3-2. Functional MRI results 28
Chapter 4. Discussions and Conclusions 31
Chapter 5. Appendices 36
5-A. Average artifact subtraction [25] 36
5-B. Heartbeat detection 37
5-C. Optimal basis set (OBS) subtraction for pulse artifact [36] 38
References 41
[1]E. Niedermeyer, and F. H. L. da Silva, Electroencephalography: Basic Principles, Clinical Applications, and Related Fields: Lippincott Williams & Wilkins, 2005.
[2]A. W. Toga, and J. C. Mazziotta, Brain Mapping: The Methods: Elsevier Science, 2002.
[3]P. L. Nunez, Electric Fields of the Brain: The Neurophysics of EEG: Oxford University Press, 1981.
[4]R. Ordidge, P. Mansfield, and R. Coupland, “Rapid biomedical imaging by NMR,” The British journal of radiology, vol. 54, no. 646, pp. 850-855, 1981.
[5]N. K. Logothetis, “What we can do and what we cannot do with fMRI,” Nature, vol. 453, no. 7197, pp. 869-878, 2008.
[6]R. J. Huster, S. Debener, T. Eichele, and C. S. Herrmann, “Methods for simultaneous EEG-fMRI: an introductory review,” The Journal of neuroscience, vol. 32, no. 18, pp. 6053-6060, 2012.
[7]C. Mulert, and L. Lemieux, EEG - fMRI: Physiological Basis, Technique, and Applications: Springer Berlin Heidelberg, 2009.
[8]G. Lantz, R. G. De Peralta, L. Spinelli, M. Seeck, and C. Michel, “Epileptic source localization with high density EEG: how many electrodes are needed?,” Clinical neurophysiology, vol. 114, no. 1, pp. 63-69, 2003.
[9]M. A. Lindquist, J. M. Loh, L. Y. Atlas, and T. D. Wager, “Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling,” Neuroimage, vol. 45, no. 1, pp. S187-S198, 2009.
[10]R. B. Buxton, E. C. Wong, and L. R. Frank, “Dynamics of blood flow and oxygenation changes during brain activation: The balloon model,” Magnetic Resonance in Medicine, vol. 39, no. 6, pp. 855-864, 1998.
[11]M. G. Philiastides, and P. Sajda, “EEG-informed fMRI reveals spatiotemporal characteristics of perceptual decision making,” Journal of Neuroscience, vol. 27, no. 48, pp. 13082-13091, 2007.
[12]H. Laufs, A. Kleinschmidt, A. Beyerle, E. Eger, A. Salek-Haddadi, C. Preibisch, and K. Krakow, “EEG-correlated fMRI of human alpha activity,” Neuroimage, vol. 19, no. 4, pp. 1463-1476, 2003.
[13]M. Ullsperger, and S. Debener, Simultaneous EEG and fMRI: Recording, Analysis, and Application: Oxford University Press, 2010.
[14]F. Babiloni, F. Carducci, C. Del Gratta, C. Babiloni, G. Roberti, G. Romani, C. Caltagirone, P. Rossini, and A. Urbano, "Combined high resolution EEG and functional MRI data for modeling of cortical sources of human movement-related potentials." pp. 2135-2138.
[15]F. Babiloni, F. Carducci, F. Cincotti, C. Del Gratta, G. Roberti, G. Romani, P. Rossini, and C. Babiloni, “Integration of high resolution EEG and functional magnetic resonance in the study of human movement-related potentials,” Methods Archive, vol. 39, no. 2, pp. 179-182, 2000.
[16]W. Ou, A. Nummenmaa, J. Ahveninen, J. W. Belliveau, M. S. Hämäläinen, and P. Golland, “Multimodal functional imaging using fMRI-informed regional EEG/MEG source estimation,” Neuroimage, vol. 52, no. 1, pp. 97-108, 2010.
[17]P. A. Valdes‐Sosa, J. M. Sanchez‐Bornot, R. C. Sotero, Y. Iturria‐Medina, Y. Aleman‐Gomez, J. Bosch‐Bayard, F. Carbonell, and T. Ozaki, “Model driven EEG/fMRI fusion of brain oscillations,” Human brain mapping, vol. 30, no. 9, pp. 2701-2721, 2009.
[18]M. Rosa, J. Daunizeau, and K. Friston, “EEG-fMRI integration: a critical review of biophysical modeling and data analysis approaches,” Journal of integrative neuroscience, vol. 9, no. 04, pp. 453-476, 2010.
[19]J. J. Riera, and A. Sumiyoshi, “Brain oscillations: ideal scenery to understand the neurovascular coupling,” Current opinion in neurology, vol. 23, no. 4, pp. 374-381, 2010.
[20]S. Debener, M. Ullsperger, M. Siegel, and A. K. Engel, “Single-trial EEG–fMRI reveals the dynamics of cognitive function,” Trends in cognitive sciences, vol. 10, no. 12, pp. 558-563, 2006.
[21]G. Sammer, C. Blecker, H. Gebhardt, P. Kirsch, R. Stark, and D. Vaitl, “Acquisition of typical EEG waveforms during fMRI: SSVEP, LRP, and frontal theta,” Neuroimage, vol. 24, no. 4, pp. 1012-1024, 2005.
[22]J. A. Caldwell, B. Prazinko, and J. L. Caldwell, “Body posture affects electroencephalographic activity and psychomotor vigilance task performance in sleep-deprived subjects,” Clinical Neurophysiology, vol. 114, no. 1, pp. 23-31, 2003.
[23]J. Jorge, F. Grouiller, Ö. Ipek, R. Stoermer, C. M. Michel, P. Figueiredo, W. Van Der Zwaag, and R. Gruetter, “Simultaneous EEG–fMRI at ultra-high field: Artifact prevention and safety assessment,” NeuroImage, vol. 105, pp. 132-144, 2015.
[24]P. J. Allen, G. Polizzi, K. Krakow, D. R. Fish, and L. Lemieux, “Identification of EEG events in the MR scanner: the problem of pulse artifact and a method for its subtraction,” Neuroimage, vol. 8, no. 3, pp. 229-39, Oct, 1998.
[25]P. J. Allen, O. Josephs, and R. Turner, “A method for removing imaging artifact from continuous EEG recorded during functional MRI,” Neuroimage, vol. 12, no. 2, pp. 230-9, Aug, 2000.
[26]X. Wan, K. Iwata, J. Riera, M. Kitamura, and R. Kawashima, “Artifact reduction for simultaneous EEG/fMRI recording: Adaptive FIR reduction of imaging artifacts,” Clinical Neurophysiology, vol. 117, no. 3, pp. 681-692, 3//, 2006.
[27]R. Ordidge, P. Mansfield, M. Doyle, and R. Coupland, “Real time movie images by NMR,” The British journal of radiology, vol. 55, no. 658, pp. 729-733, 1982.
[28]H. Berger, “Über das Elektrenkephalogramm des Menschen,” European Archives of Psychiatry and Clinical Neuroscience, vol. 94, no. 1, pp. 16-60, 1931.
[29]A. I. Klistorner, S. L. Graham, J. R. Grigg, and F. A. Billson, “Multifocal topographic visual evoked potential: improving objective detection of local visual field defects,” Investigative ophthalmology & visual science, vol. 39, no. 6, pp. 937-950, 1998.
[30]R. G. Eason, “Visual evoked potential correlates of early neural filtering during selective attention,” Bulletin of the Psychonomic Society, vol. 18, no. 4, pp. 203-206, 1981.
[31]F. Di Russo, A. Martínez, M. I. Sereno, S. Pitzalis, and S. A. Hillyard, “Cortical sources of the early components of the visual evoked potential,” Human brain mapping, vol. 15, no. 2, pp. 95-111, 2002.
[32]E. Courchesne, S. A. Hillyard, and R. Galambos, “Stimulus novelty, task relevance and the visual evoked potential in man,” Electroencephalography and Clinical Neurophysiology, vol. 39, no. 2, pp. 131-143, 8//, 1975.
[33]V. P. Clark, S. Fan, and S. A. Hillyard, “Identification of early visual evoked potential generators by retinotopic and topographic analyses,” Human brain mapping, vol. 2, no. 3, pp. 170-187, 1994.
[34]A. Hoffmann, L. Jäger, K. Werhahn, M. Jaschke, S. Noachtar, and M. Reiser, “Electroencephalography during functional echo‐planar imaging: detection of epileptic spikes using post‐processing methods,” Magnetic resonance in medicine, vol. 44, no. 5, pp. 791-798, 2000.
[35]G. Bonmassar, P. L. Purdon, I. P. Jääskeläinen, K. Chiappa, V. Solo, E. N. Brown, and J. W. Belliveau, “Motion and ballistocardiogram artifact removal for interleaved recording of EEG and EPs during MRI,” Neuroimage, vol. 16, no. 4, pp. 1127-1141, 2002.
[36]R. K. Niazy, C. F. Beckmann, G. D. Iannetti, J. M. Brady, and S. M. Smith, “Removal of FMRI environment artifacts from EEG data using optimal basis sets,” NeuroImage, vol. 28, no. 3, pp. 720-737, 11/15/, 2005.
[37]D. Maziero, T. R. Velasco, N. Hunt, E. Payne, L. Lemieux, C. E. Salmon, and D. W. Carmichael, “Towards motion insensitive EEG-fMRI: Correcting motion-induced voltages and gradient artefact instability in EEG using an fMRI prospective motion correction (PMC) system,” NeuroImage, vol. 138, pp. 13-27, 2016.
[38]G. Bonmassar, D. P. Schwartz, A. K. Liu, K. K. Kwong, A. M. Dale, and J. W. Belliveau, “Spatiotemporal brain imaging of visual-evoked activity using interleaved EEG and fMRI recordings,” Neuroimage, vol. 13, no. 6 Pt 1, pp. 1035-43, Jun, 2001.
[39]R. I. Goldman, J. M. Stern, J. Engel Jr, and M. S. Cohen, “Simultaneous EEG and fMRI of the alpha rhythm,” Neuroreport, vol. 13, no. 18, pp. 2487, 2002.
[40]W. X. Yan, K. J. Mullinger, M. J. Brookes, and R. Bowtell, “Understanding gradient artefacts in simultaneous EEG/fMRI,” Neuroimage, vol. 46, no. 2, pp. 459-471, 2009.
[41]H. Mandelkow, P. Halder, P. Boesiger, and D. Brandeis, “Synchronization facilitates removal of MRI artefacts from concurrent EEG recordings and increases usable bandwidth,” Neuroimage, vol. 32, no. 3, pp. 1120-1126, 2006.
[42]P. Ritter, F. Freyer, G. Curio, and A. Villringer, “High-frequency (600 Hz) population spikes in human EEG delineate thalamic and cortical fMRI activation sites,” Neuroimage, vol. 42, no. 2, pp. 483-490, 2008.
[43]M. Barth, F. Breuer, P. J. Koopmans, D. G. Norris, and B. A. Poser, “Simultaneous multislice (SMS) imaging techniques,” Magnetic resonance in medicine, vol. 75, no. 1, pp. 63-81, 2016.
[44]F. H. Lin, L. L. Wald, S. P. Ahlfors, M. S. Hämäläinen, K. K. Kwong, and J. W. Belliveau, “Dynamic magnetic resonance inverse imaging of human brain function,” Magnetic resonance in medicine, vol. 56, no. 4, pp. 787-802, 2006.
[45]L. Chen, A. T. Vu, J. Xu, S. Moeller, K. Ugurbil, E. Yacoub, and D. A. Feinberg, “Evaluation of highly accelerated simultaneous multi-slice EPI for fMRI,” NeuroImage, vol. 104, pp. 452-459, 2015/01/01/, 2015.
[46]K. P. Pruessmann, M. Weiger, M. B. Scheidegger, and P. Boesiger, “SENSE: Sensitivity encoding for fast MRI,” Magnetic Resonance in Medicine, vol. 42, no. 5, pp. 952-962, 1999.
[47]D. A. Feinberg, and K. Setsompop, “Ultra-fast MRI of the human brain with simultaneous multi-slice imaging,” Journal of Magnetic Resonance, vol. 229, pp. 90-100, 2013/04/01/, 2013.
[48]A. M. Norcia, L. G. Appelbaum, J. M. Ales, B. R. Cottereau, and B. Rossion, “The steady-state visual evoked potential in vision research: a review,” Journal of vision, vol. 15, no. 6, pp. 4-4, 2015.
[49]C. S. Herrmann, “Human EEG responses to 1–100 Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena,” Experimental brain research, vol. 137, no. 3-4, pp. 346-353, 2001.
[50]A. Bayram, Z. Bayraktaroglu, E. Karahan, B. Erdogan, B. Bilgic, M. Özker, I. Kasikci, A. D. Duru, A. Ademoglu, C. Öztürk, K. Arikan, N. Tarhan, and T. Demiralp, “Simultaneous EEG/fMRI Analysis of the Resonance Phenomena in Steady-State Visual Evoked Responses,” Clinical EEG and Neuroscience, vol. 42, no. 2, pp. 98-106, April 1, 2011, 2011.
[51]K. J. Mullinger, P. Castellone, and R. Bowtell, “Best current practice for obtaining high quality EEG data during simultaneous fMRI,” Journal of visualized experiments: JoVE, no. 76, 2013.
[52]B. Fischl, “FreeSurfer,” Neuroimage, vol. 62, no. 2, pp. 774-781, 2012.
[53]A. Gramfort, M. Luessi, E. Larson, D. A. Engemann, D. Strohmeier, C. Brodbeck, L. Parkkonen, and M. S. Hämäläinen, “MNE software for processing MEG and EEG data,” NeuroImage, vol. 86, pp. 446-460, 2014/02/01/, 2014.
[54]M. Stenroos, V. Mäntynen, and J. Nenonen, “A Matlab library for solving quasi-static volume conduction problems using the boundary element method,” Computer methods and programs in biomedicine, vol. 88, no. 3, pp. 256-263, 2007.
[55]M. Stenroos, and A. Nummenmaa, “Incorporating and Compensating Cerebrospinal Fluid in Surface-Based Forward Models of Magneto- and Electroencephalography,” PLOS ONE, vol. 11, no. 7, pp. e0159595, 2016.
[56]K. J. Friston, “Functional and Effective Connectivity: A Review,” Brain Connectivity, vol. 1, no. 1, pp. 13-36, 2011/01/01, 2011.
[57]N. Roehri, J.-M. Lina, J. C. Mosher, F. Bartolomei, and C.-G. Bénar, “Time-frequency strategies for increasing high-frequency oscillation detectability in intracerebral EEG,” IEEE Transactions on Biomedical Engineering, vol. 63, no. 12, pp. 2595-2606, 2016.
[58]S. Burnos, P. Hilfiker, O. Sürücü, F. Scholkmann, N. Krayenbühl, T. Grunwald, and J. Sarnthein, “Human intracranial high frequency oscillations (HFOs) detected by automatic time-frequency analysis,” PLoS One, vol. 9, no. 4, pp. e94381, 2014.
[59]P. Goupillaud, A. Grossmann, and J. Morlet, “Cycle-octave and related transforms in seismic signal analysis,” Geoexploration, vol. 23, no. 1, pp. 85-102, 1984/10/01/, 1984.
[60]C. F. Beckmann, M. Jenkinson, and S. M. Smith, “General multilevel linear modeling for group analysis in FMRI,” Neuroimage, vol. 20, no. 2, pp. 1052-1063, 2003.
[61]Y. Benjamini, and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” Journal of the royal statistical society. Series B (Methodological), pp. 289-300, 1995.
[62]S. Zhang, X. Han, X. Chen, Y. Wang, S. Gao, and X. Gao, “A study on dynamic model of steady-state visual evoked potentials,” Journal of neural engineering, vol. 15, no. 4, pp. 046010, 2018.
[63]B. A. Wandell, S. O. Dumoulin, and A. A. Brewer, “Visual field maps in human cortex,” Neuron, vol. 56, no. 2, pp. 366-383, 2007.
[64]S. Warach, J. Ives, G. Schlaug, M. Patel, D. Darby, V. Thangaraj, R. Edelman, and D. Schomer, “EEG-triggered echo-planar functional MRI in epilepsy,” Neurology, vol. 47, no. 1, pp. 89-93, 1996.
[65]K. Krakow, F. Woermann, M. Symms, P. Allen, L. Lemieux, G. Barker, J. Duncan, and D. Fish, “EEG-triggered functional MRI of interictal epileptiform activity in patients with partial seizures,” Brain, vol. 122, no. 9, pp. 1679-1688, 1999.
[66]F. Lazeyras, O. Blanke, S. Perrig, I. Zimine, X. Golay, J. Delavelle, C. M. Michel, N. De Tribolet, J. G. Villemure, and M. Seeck, “EEG‐triggered functional MRI in patients with pharmacoresistant epilepsy,” Journal of Magnetic Resonance Imaging, vol. 12, no. 1, pp. 177-185, 2000.
[67]L. Lemieux, K. Krakow, and D. R. Fish, “Comparison of spike-triggered functional MRI BOLD activation and EEG dipole model localization,” Neuroimage, vol. 14, no. 5, pp. 1097-1104, 2001.
[68]G. Bonmassar, K. Anami, J. Ives, and J. W. Belliveau, “Visual evoked potential (VEP) measured by simultaneous 64-channel EEG and 3T fMRI,” NeuroReport, vol. 10, no. 9, pp. 1893-1897, 1999.
[69]F. Kruggel, C. J. Wiggins, C. S. Herrmann, and D. Y. von Cramon, “Recording of the event‐related potentials during functional MRI at 3.0 Tesla field strength,” Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, vol. 44, no. 2, pp. 277-282, 2000.
[70]F. Kruggel, C. S. Herrmann, C. J. Wiggins, and D. Y. von Cramon, “Hemodynamic and electroencephalographic responses to illusory figures: recording of the evoked potentials during functional MRI,” Neuroimage, vol. 14, no. 6, pp. 1327-1336, 2001.
[71]R. I. Goldman, J. M. Stern, J. Engel Jr, and M. S. Cohen, “Acquiring simultaneous EEG and functional MRI,” Clinical Neurophysiology, vol. 111, no. 11, pp. 1974-1980, 2000.
[72]K. Anami, T. Mori, F. Tanaka, Y. Kawagoe, J. Okamoto, M. Yarita, T. Ohnishi, M. Yumoto, H. Matsuda, and O. Saitoh, “Stepping stone sampling for retrieving artifact-free electroencephalogram during functional magnetic resonance imaging,” Neuroimage, vol. 19, no. 2, pp. 281-295, 2003.
[73]F. Freyer, R. Becker, K. Anami, G. Curio, A. Villringer, and P. Ritter, “Ultrahigh-frequency EEG during fMRI: pushing the limits of imaging-artifact correction,” Neuroimage, vol. 48, no. 1, pp. 94-108, 2009.
[74]N. K. Logothetis, “What we can do and what we cannot do with fMRI,” Nature, vol. 453, pp. 869, 06/12/online, 2008.
[75]D. Needell, and J. A. Tropp, “CoSaMP: Iterative signal recovery from incomplete and inaccurate samples,” Applied and Computational Harmonic Analysis, vol. 26, no. 3, pp. 301-321, 2009/05/01/, 2009.
[76]C. Michel, D. Lehmann, B. Henggeler, and D. Brandeis, “Localization of the sources of EEG delta, theta, alpha and beta frequency bands using the FFT dipole approximation,” Electroencephalography and clinical neurophysiology, vol. 82, no. 1, pp. 38-44, 1992.
[77]C. Haenschel, T. Baldeweg, R. J. Croft, M. Whittington, and J. Gruzelier, “Gamma and beta frequency oscillations in response to novel auditory stimuli: a comparison of human electroencephalogram (EEG) data with in vitro models,” Proceedings of the National Academy of Sciences, vol. 97, no. 13, pp. 7645-7650, 2000.
[78]A. K. Roopun, S. J. Middleton, M. O. Cunningham, F. E. N. LeBeau, A. Bibbig, M. A. Whittington, and R. D. Traub, “A beta2-frequency (20–30 Hz) oscillation in nonsynaptic networks of somatosensory cortex,” Proceedings of the National Academy of Sciences, vol. 103, no. 42, pp. 15646-15650, 2006.
[79]S. R. Jones, C. E. Kerr, Q. Wan, D. L. Pritchett, M. Hämäläinen, and C. I. Moore, “Cued Spatial Attention Drives Functionally-Relevant Modulation of The Mu Rhythm in Primary Somatosensory Cortex,” The Journal of neuroscience : the official journal of the Society for Neuroscience, vol. 30, no. 41, pp. 13760-13765, 2010.
[80]N. Swann, H. Poizner, M. Houser, S. Gould, I. Greenhouse, W. Cai, J. Strunk, J. George, and A. R. Aron, “Deep brain stimulation of the subthalamic nucleus alters the cortical profile of response inhibition in the beta frequency band: a scalp EEG study in Parkinson''s disease,” Journal of Neuroscience, vol. 31, no. 15, pp. 5721-5729, 2011.
[81]G. H. Glover, “Overview of functional magnetic resonance imaging,” Neurosurgery Clinics, vol. 22, no. 2, pp. 133-139, 2011.
[82]J. Gotman, and F. Pittau, “Combining EEG and fMRI in the study of epileptic discharges,” Epilepsia, vol. 52, no. s4, pp. 38-42, 2011.
[83]I. I. Christov, “Real time electrocardiogram QRS detection using combined adaptive threshold,” Biomedical engineering online, vol. 3, no. 1, pp. 28, 2004.
[84]K. H. Kim, H. W. Yoon, and H. W. Park, “Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI,” Journal of neuroscience methods, vol. 135, no. 1, pp. 193-203, 2004.
[85]P. Maragos, J. F. Kaiser, and T. F. Quatieri, “On amplitude and frequency demodulation using energy operators,” IEEE Transactions on signal processing, vol. 41, no. 4, pp. 1532-1550, 1993.
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