Research Scientist & Director, Swartz Center for Computational Neuroscience Institute for Neural Computation University of California San Diego La Jolla CA 92093-0961

My primary research interest is in analysis and modeling of cognitive event-related brain dynamics as captured by high-dimensional EEG, MEG and other brain imaging modalities using Independent Component Analysis, time-frequency and machine learning methods. In particular, I have studied the dynamics of performance and electrophysiology accompanying alertness lapses during sustained monitoring tasks, and have used the results of this research to design real-time alertness monitoring systems, one application in the emerging field of neural human-system interface technology. Currently, I am working to apply Independent Component Analysis to EEG, ERP and fMRI data to open wider windows for noninvasive observation of cognitive brain dynamics. I now direct the new Swartz Center for Computational Neuroscience of the Institute for Neural Computation, UCSD. The Center is housed in a suite of offices at the edge of the UCSD campus and includes two EEG laboratory spaces and a workstation cluster. We are looking to build collaborations with researchers wanting to apply new analytic methods to EEG, fMRI and other types of cognitive neuroscience data, as well as with physicists and mathematicians wanting to model human brain dyanmics underlying brain cognitive capacities, including attention, memory, emotion, social interaction and creativity. Current projects include concurrent EEG / fMRI, EEG / motion capture, EEG / emotional, advanced ICA imaging, EEG / social neuroscience, EEG / sudden insight, fMRI group analysis, and the dynamics of EEG biofeedback.

Contact: smakeigucsd.edu Swartz Center for Computational Neuroscience Institute for Neural Computation University of California San Diego 0961 La Jolla CA 92093-0961 (858) 458-1927 x11 (858) 458-1847 fax

Selected Publications Makeig S et al. Current meeting abstracts. Makeig S, Moving from 2-D to 3-D EEG-based brain imaging. Powerpoint pdf (7 MB) from a workshop talk, Sept. 2008 Palmer J, Makeig S, Kreutz-Delgado K, Rao BD Newton method for the ICA mixture model ICASSP, 2008 Huang R-S, Jung T-P, Delorme A, Makeig S, Tonic and phasic electroencephalographic dynamics during continuous compensatory tracking. Neuroimage, 2008 Delorme A, Westerfield M, Makeig S, Medial prefrontal theta bursts precede rapid motor responses during visual selective attention. J Neurosci 27:11949-59, 2007 (DOI:10.1523/JNEUROSCI.3477-07.2007). Mobile high-definition EEG brain imaging. Makeig A talk at the UCSD Temporal Dynamics of Learning Center meeting (17 min, Real player) Jan., 2007 Wipf D, Ramirez R, Palmer J, Makeig S., Rao B. Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization , NIPS 2007, in press. Hsu J-L, Jung T-P, Hsu C-Y, Hsu W-C, Chen Y-K, Duann J-R, Wang H-C, Makeig S. Regional CBF Changes in Parkinsons Disease: A Correlation with Motor Dysfunction. Europ J Nuclear Medicine & Molecular Imaging, 2007. Dyrholm, M, Makeig S, Hansen, LK, Convolutive ICA for spatiotemporal analysis of EEG. Neural Computation 19, 934-955, 2007. W Einhaeuser, Koch C, Makeig S. The duration of the attentional blink in natural scenes depends on stimulus category. Vision Research 47:597-607, 2007. Delorme A., Sejnowski T., Makeig S. Improved rejection of artifacts from EEG data using high-order statistics and independent component analysis. NeuroImage, 2007. Miller KJ, Makeig S, Hebb A, Rao R, denNijs M, Ojemann GJ. Cortical electrode localization from X-rays and simple mapping for electrocorticographic research: The Location on Cortex (LOC) package for MATLAB, J Neurosci Methods 162:303-308, 2007. Onton J, Westerfield M, Townsend J, Makeig S. Interpreting EEG brain dynamics using independent component analysis. In: Neuroscience and Behavioral Reviews Special Issue: Development Through the Life Cycle, Eds: Ulman Lindenberger and Shu-Chen Li, 30:808-822, 2006. Tsai, AC, Liou, M, Jung, T-P, Onton J, Cheng PE., Huang C-C, Duann, J-R, Makeig S. Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality. NeuroImage 32:195-207, 2006. Dyrholm M, Makeig S, Hansen LK, Model structure selection in covolutive mixtures. Lecture Notes in Computer Science 3889:74-81, 2006 Palmer J, Kreutz-Delgado K, Makeig S. Super-gaussian mixture models for ICA. Lecture Notes in Computer Science 3889:854-861, 2006 Graphic example and overview chapter: Onton J. Makeig S., Why use ICA to decompose EEG/MEG data?, Progress in Brain Research (2006). Tsai, AC, Liou, M, Jung, T-P, Onton J, Cheng PE., Huang C-C, Duann, J-R, Makeig S. Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality, NeuroImage 32:195-207, 2006. Onton J, Delorme A, Makeig S., Frontal midline EEG dynamics during working memory. NeuroImage 27:341-56, 2005. Makeig S., Brain decisions have consequences! from a talk at Banbury Center, Long Island June, 2005 (0.8 MB, .pdf). Makeig S., A 'handwaving' explanation of ICA from a talk at Dollnsee, Germany Sept., 2004. Makeig S Multiscale evidence of multiscale brain communication. Talk at Banbury Center (5MB, .pdf), May, 2004. Makeig S, Delorme A, Westerfield M, Townsend J, Courchense E, Sejnowski T, Electroencephalographic brain dynamics following visual targets requiring manual responses. PLOS Biology, 2(6):742-762, 2004. Makeig S, Debener S, Onton J, Delorme A, Mining event-related brain dynamics Trends in Cognitive Science, 8(5):204-210, 2004. Luu P, Tucker D, Makeig S, Frontal-midline theta and the ERN (4.3MB, .pdf) Clinical Neurophysiology, 115:1821-35, 2004. Delorme A and Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics J Neurosci Methods, 134:9-21, 2004. J. Anemuller, Sejnowski TJ, and Makeig S., Complex independent component analysis of frequency-domain EEG data, Neural Networks 16:1311-23, 2003. Delorme, A. and Makeig, S., EEG changes accompanying learned regulation of 12-Hz EEG activity (.pdf, 369 kB), IEEE Trans Neural Sys & Rehab Eng, 2(2):133-136, 2003. Makeig S, Event-related brain dynamics: Unifying brain electrophysiology (.pdf, 22k). Trends in Neurosciences 25,8: 390, August, 2002; Makeig S, Jung T-P, Sejnowski T.J. Having your voxels and timing them too? (.pdf, 721k). In: Exploratory Analysis and Data Modeling in Functional Neuroimaging (F. Sommer & A. Wichert, eds.), The MIT Press, 2002. Makeig S, Westerfield M, Jung T-P, Enghoff S, Townsend J, Courchesne E, Sejnowski TJ. Dynamic brain sources of visual evoked responses. Science, 295:690-694 (25 Jan 2002). J-R. Duann, T-P. Jung, W-J. Kuo, T-C.. Yeh, S. Makeig, J-C. Hsieh, TJ Sejnowski, Measuring the variability of event-related BOLD signals" (.pdfi, 72K),Neuroimage 15: 823-25, 2002. T-P. Jung, S. Makeig, M. Westerfield, J. Townsend, E. Courchesne and T. J. Sejnowski, " Independent component analysis of single-trial event-related potentials (1.1 Mb .pdf)," Human Brain Mapping, 14(3):168-85,2001. Jung, T-P, Makeig, S, McKeown, M. J., Bell, A. J., Lee, T-W, Sejnowski, T. J., Imaging brain dynamics using Independent Component Analysis (.pdf, 640k), Proceedings of the IEEE, 89(7):1107-22, 2001. Makeig S, Tzyy-Ping Jung, and Terrence J. Sejnowski, "Awareness during Drowsiness: Dynamics and Electrophysiological Correlates" (.html/.doc.gz), Can J Exp Psychol 54(4):266-73, 2000. Jung T-P, Makeig S, Westerfield W, Townsend J, Courchesne E, and Sejnowski TJ, " Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects (.pdf, 1.3Mb)," Clinical Neurophysiology, 111:10, 1745-58, 2000. Makeig S, Jung T-P and Sejnowski TJ, "An efficient basis for brain-actuated control" (.pdf, 111k), IEEE Trans Rehab Eng 8:208-11, 2000. Jung T-P, Makeig S, Humphries C , Lee TW, McKeown MJ, Iragui V, and Sejnowski TJ, Removing electroencephalographic artifacts by blind source separation (.HTML, .pdf.zip), Psychophysiology, 37:163-78, 2000. Jung T-P, Makeig S, Lee T-W, McKeown M.J., Brown G., Bell, A.J. and Sejnowski TJ, "Independent Component Analysis of Biomedical Signals," Second International Workshop on Independent Component Analysis and Signal Separation, Helsinki, pp. 633-44, 2000. Makeig S, M. Westerfield, J. Townsend, T-P. Jung, E. Courchesne, T. J. Sejnowski,. Functionally independent components of the early event-related potential in a visual spatial attention task (.pdf 450k). Philosophical Transactions of the Royal Society: Biological Sciences 354:1135-44, 1999. The evoked response data (.tar.gz 0.4Mb) Makeig S, Marissa Westerfield, Tzyy-Ping Jung, James Covington, Jeanne Townsend, Terrence J. Sejnowski and Eric Courchesne J. Neurosci. 19:2665-2680 (1999). Functionally independent components of the late positive event-related potential during visual spatial attention (.pdf, 1Mb) Soc. Neurosci. members (.html) The evoked response data (.tar.gz, 2Mb). MJ McKeown, Makeig S, Greg G. Brown, Tzyy-Ping Jung, Kindermann, and Terrence J. Sejnowski. Human Brain Mapping, 6(3):160-88 (1998). Analysis of fMRI by Blind Separation into Independent Spatial Components (.ps.Z, 4Mb). Makeig S, Anthony J. Bell, Tzyy-Ping Jung and Terrence J. Sejnowski, Independent component analysis of electroencephalographic data In: D. Touretzky, M. Mozer and M. Hasselmo (Eds). Advances in Neural Information Processing Systems 8:145-151 (1996). (.ps.gz, 488kB) (First paper applying ICA to EEG).

Workshops: SPR '00 Symposium: New insights into human brain dynamics SPR '96 Symposium: Time-frequency analysis of event-related brain dynamics NIPS '95 Workshop: Neural human-system interface technology

More: Frequently Asked Questions about ICA applied to EEG/MEG data. List of CNL publications on ICA applied to EEG and fMRI data ICA research at Computational Neurobiology Laboratory, Salk Institute

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