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Workshop Program
This Talk -- Scott Makeig, Director of the Swartz Center for Computational Neuroscience (SCCN), UCSD, founder and co-developer of the EEGLAB project, begins the Workshop with a (November 2010) overview of EEG research, its motivation, biology, analysis, and potential future applications, and an overview of the original EEG data processing approach that EEGLAB enables.
You may download all the (.pdf) slides used in the talk here. Press FS on the lower right corner of each video image to view the talk in full screen display.Chapter 5 (10:49) discusses the 3-D EEG inverse source imaging problem, and the historical drawbacks of reducing recorded data to one or more average event-related potentials (ERPs). Currently, a unified field of brain electrophysiology does not yet really exist. Mining the wealth of information that may be obtained from the unaveraged data by measuring and modeling more of its rich and complex relationship to behavior and experience will in future contribute to the emergence of such a model and understanding. Download the slides for this chapter.
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Study the slides for this chapter here. |
Chapter 6 (12:56) gives the goal, rationale, and a first overview of results obtained from spatial source filtering high-density EEG data to obtain underlying cortical (and other) EEG source processes using Independent Component Analysis (ICA). Download the slides for this chapter.
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Study the slides for this chapter here. |
Chapter 7 (3:44) presents some results suggesting that the places that independent source processes appear in cortex depend in part on the task the subject is performing, bearing on the basic and yet unanswered question for EEG research, 'Where do (appreciably large) EEG source processes appear -- and why?' This inevitably raises deep questions about the stationarity of the EEG source distribution, a problem we are working on tools to better measure and characterize. Download the slides for this chapter.
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Study the slides for this chapter here. |
Chapter 8 (21:02) summarizes the approach to analyzing event-related brain dynamics that EEGLAB enables and was first developed to facilitate. This involves ICA decomposition, trial-by-trial analysis, and time/frequency analysis. The basic time/frequency measures available in EEGLAB -- the Event-Related Spectral Perturbation (ERSP), Inter-Trial Coherence (ITC), and Event-Related Coherence (ERC) are defined, and the value of modeling EEG source network dynamics is illustrated with a data example. Download the slides for this chapter.
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Study the slides for this chapter here. |
Chapter 9 (9:44) discusses emerging uses for EEG-based functional imaging, for cognitive monitoring of alertness, attention, arousal, anticipation, affect, awareness, agency -- and Aha! Research examples are shown of extracting some of these types of information from scalp EEG data. Paradigm shift alert! EEG is becoming something to use in a variety of settings, not just something to analyze in the laboratory! Download the slides for this chapter.
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Study the slides for this chapter here. |
Return to the Workshop Program, to the Makeig home page, or to the EEGLAB home page.