title: Optimal set of EEG electrodes for rapid serial visual presentation.
abstract: In our application, the goal is to search through a large image to find all instances of a pre-specified, high-valued target. One approach taken to increase the throughput of this image search task is to: chop the large image into numerous small images, display them to a user at high rates one-at-a-time, and then search the simultaneously-recorded EEG data for neural activity that signifies that the user detected an instance of the target. The temporal efficiency of this EEG-based system is reduced by the overhead, which increases as the number of electrodes increases. Hence, we wish to find a minimal set of electrodes that ideally maintains the detection performance. In order to inform the design of future EEG-based image search systems, in this paper we find the 12 out of 32/64 most important electrodes for detection using 5 different feature selection methods. The optimal set includes all 5 occipital and the 2 most frontal electrodes.
authors.affiliation: Dept. of Biomedical Engineering, Oregon Health & Science University, Portland, OR 97239, USA. k.hild@ieee.org
authors.forename: Kenneth E
authors.initials: KE
authors.lastname: Hild
authors.forename: Santosh
authors.initials: S
authors.lastname: Mathan
authors.forename: Yonghong
authors.initials: Y
authors.lastname: Huang
authors.forename: Deniz
authors.initials: D
authors.lastname: Erdogmus
authors.forename: Misha
authors.initials: M
authors.lastname: Pavel
mesh_terms: D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation*; D006801:Humans; D025341:Principal Component Analysis; D014785:Vision, Ocular