p176fig04.53 The on-center off-surround network within position and across depth helps to explain why brighter Kanizsa squares look closer.<BR>|| inhibition vs. depth. p176c1h0.25 "... to qualitatively understand how this example of proximity-luminance covariance works. It follows directly from the boundary pruning by surface contour feedback signals (<A HREF="http://www.BillHowell.ca/ProjMini/TrNNs_ART/images- Grossberg 2021/p174fig04.51 figure-ground separation, complementary consistency [boundaries, surfaces].png">Figure 4.51</a>) that achieves complementary consistency and initiates figure-ground perception. ...". p176c1h0.45 "... these inhibitory sigals are part of an off-surround network whose strength <I>decreases</i> as the depth difference <I>increases</i> between the surface that generates the signal and its recipient boundaries. ...". p176c1h0.8 "... Within FACADE theory, the perceived depth of a surface is controlled by the boundaries that act as its filling-in generators and barriers (<A HREF="http://www.BillHowell.ca/ProjMini/TrNNs_ART/images- Grossberg 2021/p105fig03.22 3D vision and figure-ground separation: [multiple-scale, depth-selective] boundary webs.png">Figure 3.22</a>), since these boundaries select the depth-sselective FIDOs within whin filling-in can occur, and thereby achieve surface capture.  These boundaries, in turn, are themselves strengthened after surface-to-boundary contour feedback eliminates redundant boundaries that cannot support sucessful filling-in (Figure 4.51). These surface contour feedback signals have precisely the properties that are needed to explain why brighter Kanizsa squares look closer! ..."