16th EEGLAB Workshop,

Beijing, China

Mining Event-Related Brain Dynamics



June 16-18, 2012

Scott Makeig , Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA

Mining Event-Related Brain Dynamics

Electroencephalography (EEG) is the recording of electric potentials produced by the local collective partial synchrony of electrical field activity in cortical neuropile, today most commonly measured by an array of electrodes attached to the scalp using water-based gel. EEG is today the most widely known and studied portable non-invasive brain imaging modality. The first report of signals originating in the human brain and recorded non-invasively from the scalp was that of Berger in 1924. While today neurologists still typically review EEG 'squiggles' by visual inspection, half a century later (and over 35 years ago) both engineers and artists begin to seriously consider the possible use of EEG for active and automated information exchange between humans and machines. It is now generally accepted that the spatiotemporal EEG activity patterns correlate with changes in cognitive arousal, attention, intention, evaluation, and the like, thereby providing a potential âœwindow on the mind.❠However, the biological mechanisms that link EEG patterns to these or other aspects of cognition are not understood in much detail. We believe that in the coming decades adequate and more near real-time signal processing for feature extraction and state prediction or recognition, combined with new, non-invasive and even wearable electrophysiological sensing technologies can produce meaningful 3-D functional brain imaging and brain-computer interface (BCI) applications in a wide range of directions. Here, we will begin with a brief primer on the neuroscientific basis of cognitive state assessment, i.e. on the nature of the EEG itself, followed by a review of the history and current state of the use of signal processing in the relatively young 3-D EEG functional brain imaging and BCI design fields, and then will consider avenues for its short-term and medium-term technical advancement using the EEGLAB environment (Delorme & Makeig, 2004) and its ever-evolving range of plug-in toolboxes.

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