Our finding that brightness induction, or one form of brightness induction, is nearly instantaneous requires a reevaluation of the physiological mechanisms proposed to account for induction and its temporal characteristics. To explain their brightness masking data, Paradiso and Nakayama (
1991) proposed that filling-in signals travel at a rate of 6.7–9.2 ms/deg. In the GI stimulus it is test field height, rather than bar width (or spatial frequency), that determines the distance over which filling-in would need to propagate. We find that induction phase (time) lag is small and relatively constant across wide variations in test field height. These data, like the spatial pattern of brightness induced in the test field of the GI stimulus (Blakeslee & McCourt,
1997), cannot easily be explained as the outcome of an edge-dependent, homogeneous filling-in process (Rossi & Paradiso,
1996). The data, however, are consistent with an explanation of brightness induction based on spatial filtering by cortical simple cells (Blakeslee & McCourt,
1997,
1999). Cortical filtering predicts that induction will be nearly instantaneous since the ON and OFF subregions of these cells arise through excitatory inputs from ON and OFF center LGN cells, respectively, and have similar latencies (Ferster & Lindström,
1983; Hirsch & Martinez,
2006). Blakeslee and McCourt (
1997) parsimoniously accounted for SBC and GI with a linear multiscale difference-of-Gaussians (DOG) model. Both effects, however, occur over distances too large to be explained on the basis of retinal or geniculate receptive fields, making a cortical origin for these effects likely (Blakeslee & McCourt,
1997; DeValois et al.,
1986; Yund & Armington,
1975). The DOG model has since been elaborated to include both orientation selectivity and contrast normalization (gain control), response characteristics routinely observed at early cortical stages of visual processing in both cat and monkey (Albrecht, Geisler, Frazor, & Crane,
2002; Carandini, Heeger, & Movshon,
1997; Hirsch & Martinez,
2006). This newer oriented DOG (ODOG) model accounts for GI and SBC as well as for a number of additional brightness effects, including White's effect, which cannot be explained by the linear DOG model (Blakeslee & McCourt,
1999,
2001,
2004; Blakeslee, Pasieka, & McCourt,
2005).