PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG

<div>Scalp maps of the PWC-ICA <svg height="11.5564pt" id="M292" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 15.3928 11.5564" width="15.3928pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z" id="g113-41"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="346" vert-adv-y="346"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,4.498,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z" id="g113-50"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,10.738,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z" id="g113-42"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="346" vert-adv-y="346"></glyph.data></g></svg> Haar components with the best absolute time correlations above 0.8. The fitted dipole and moment are plotted in bold black on each scalp map, and the residual variance of the fitted dipole is included in parentheses above the scalp map.</div>

Computational Intelligence and Neuroscience

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Figure 6

Figure 6: PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG 