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 human cognitive event-related brain dynamics as captured by high-dimensional EEG, MEG and other imaging modalities now including body motion capture. Brain imaging analysis approaches I and colleagues have pioneered include time-frequency analysis and independent component analysis (ICA), and neural network and machine learning methods. With Mark Inlow, Tzyy-Ping Jung and others, 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, an example of the rapidly emerging field of neural human-system interface technology. Currently, I am working to apply Independent Component Analysis to EEG and related data to open new windows for noninvasive observation of the relationship between brain dynamics, cognition, and behavior -- in effect working to develop a new brain imaging modality I call Mobile Brain/Body Imaging (MoBI). I direct the 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 EEG laboratory space and a computing cluster and network. 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, engineers, and mathematicians wanting to model human brain dynamics underlying brain cognitive capacities, including attention, memory, emotion, social interaction and creativity. Current projects include concurrent EEG/fMRI, EEG/motion capture, EEG/emotions, EEG/social neuroscience, EEG/insight, advanced ICA-based source localization and imaging, and EEG/cognitive monitoring and 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 and Presentations Makeig S et al. Current meeting abstracts. Makeig S. Mind Monitoring via Mobile Brain-Body Imaging (0.1MB pdf) Human-Computer Interface International 2009, San Diego CA, 2009 Huang R-S, Jung T-P, Makeig S. Tonic Changes in EEG Power Spectra during Simulated Driving (0.7MB pdf) Human-Computer Interface International 2009, San Diego CA, 2009 Wang Y, Makeig S. Predicting Intended Movement Direction Using EEG from Human Posterior Parietal Cortex (0.6MB pdf) Human-Computer Interface International 2009, San Diego CA, 2009 Groppe D, Makeig S, Kutas M. Identifying Reliable Independent Components via Split-Half Comparisons (0.8MB pdf) NeuroImage, http://dx.doi.org/10.1016/j.neuroimage.2008.12.038, 2009 Makeig S, Onton J. ERP features and EEG dynamics: An ICA perspective (2.6MB pdf) Oxford Handbook of Event-Related Potential Components, Ed. Luck S & Kappenman E, 2009 in press. Makeig S, Gramann K, Jung T-P, Sejnowski TJ, Poizner H. Linking brain, mind and behavior: The promise of mobile brain/body imaging (MoBI) (2.5 MB pdf) International Journal of Psychophysiology, 2009 in press. Bigdely-Shamlo N, Vankov A, Ramirez RR, Makeig S, Brain activity-based image classification from rapid serial visual presentation. (8.3 MB pdf) IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(4): 432-441, 2008 Makeig S, Mobile high-definition EEG brain imaging. Video of a talk at the UCSD Temporal Dynamics of Learning Center meeting (17 min, Real player) Jan., 2007 Makeig S, Moving from 2-D to 3-D EEG-based brain imaging. Powerpoint slides (7 MB pdf) 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). Onton J. Makeig S. ICA example and Overview chapter: Why use ICA to decompose EEG/MEG data?, Progress in Brain Research (2006). Wipf D, Ramirez R, Palmer J, Makeig S, Rao B. Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization , NIPS 2007 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 TJ, 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 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 TJ, 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, 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 (369 KB pdf), IEEE Trans Neural Sys & Rehab Eng, 2(2):133-136, 2003. Makeig S, Event-related brain dynamics: Unifying brain electrophysiology (22KB pdf). Trends in Neurosciences 25,8: 390, August, 2002; Makeig S, Jung T-P, Sejnowski TJ. Having your voxels and timing them too? (721KB pdf). 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). Duann J-R, Jung T-P, Kuo W-J, Yeh T-C, Makeig S, Hsieh J-C, Sejnowski TJ. Measuring the variability of event-related BOLD signals" (72KB pdf),Neuroimage 15: 823-25, 2002. Jung T-P, Makeig S, Westerfield M, Townsend J, Courchesne E, Sejnowski TJ. " 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 MJ, Bell AJ, Lee T-W, Sejnowski TJ. Imaging brain dynamics using Independent Component Analysis (640 KB pdf), Proceedings of the IEEE, 89(7):1107-22, 2001. Makeig S, Jung T-P, Sejnowski TJ. "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, Sejnowski TJ. " Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects (1.3MB pdf)," Clinical Neurophysiology, 111:10, 1745-58, 2000. Makeig S, Jung T-P, Sejnowski TJ. "An efficient basis for brain-actuated control" (111 KB pdf), IEEE Trans Rehab Eng 8:208-11, 2000. Jung T-P, Makeig S, Humphries C , Lee TW, McKeown MJ, Iragui V, 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 MJ, Brown G, Bell AJ, 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, Westerfield M, Townsend J, Jung T-P, Courchesne E, Sejnowski TJ. Functionally independent components of the early event-related potential in a visual spatial attention task (450 KB pdf). Philosophical Transactions of the Royal Society: Biological Sciences 354:1135-44, 1999. The evoked response data (0.4MB tar.gz) Makeig S, Westerfield M, Jung T-P, Covington J, Townsend J, Sejnowski, Courchesne E. J. Neurosci. 19:2665-2680 (1999). Functionally independent components of the late positive event-related potential during visual spatial attention (1 MB pdf) Soc. Neurosci. members (.html) The evoked response data (2Mb tar.gz). McKeown MJ, Makeig S, Brown GG, Jung T-P, Kindermann M, Sejnowski TJ. Human Brain Mapping, 6(3):160-88 (1998). Analysis of fMRI by Blind Separation into Independent Spatial Components ( 4MB ps.Z). Makeig S, Bell AJ, Jung T-P, Sejnowski TJ. 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). (488KB ps.gz) (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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