A utomated P rotocol for E RP C omponent S eparation (APECS): Effects of Spatial Sampling on Blink Removal using Independent Components Analysis R. M. Frank 1 G. A. Frishkoff 1, 2 J. Dien 3
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Automated Protocol for ERP Component Separation (APECS):
Effects of Spatial Sampling on Blink Removal using Independent Components Analysis
R. M. Frank 1 G. A. Frishkoff 1, 2 J. Dien 3
1 Neurinformatics Center, University of Oregon 2 University of Pittsburgh 3 University of Kansas
Figure 3. Mean negentropy for 111,000 dataset as a function of channel density.
Figure 4. Number of template matches and BERP correlations as a function of channel density and number of samples/channel2 density.
Figure 5. Relationships between number of template matches, BERP correlations and blink splitting as a function of channel density and number of samples/channel2 density.
Figure 6. Blink splitting illustration: L) Topography for IC #02. Blink template correlation = 0.965. R) BERP for IC#02.
Figure 7. Illustration of how reliance on spatial metric can lead to false positives: L) Topography for IC #27. Blink template correlation = 0.912. R) BERP for IC#27.
ANATOMY OF A BLINK
Figure 2. (A) Timecourse of a blink (1sec); (B) Topography of an average blink (red = positive; blue = negative)
ACKNOWLEDGEMENTS & CONTACTINFORMATION
This research was supported by the NSF, grant no. BCS-0321388 and by the DoD Telemedicine Advanced Technology Research Command (TATRC), grant no. DAMD170110750.
For poster reprints, please contact Dr. Frishkoff ([email protected]).