Metacontrast, target recovery, and the magno- and parvocellular systems: A reply to the perspective

Backward masking refers to the reduced visibility of a target stimulus when it is followed in time by a second stimulus called the mask (reviews: Bachmann, 1994; Breitmeyer & Öğmen, 2000, 2006). The visibility of a target (T) masked by a primary mask (M1) can be recovered if an appropriately timed secondary mask, M2, is added to the T–M1 sequence. This phenomenon is known as ‘‘target disinhibition’’ or ‘‘target recovery’’ (e.g., Dember & Purcell, 1967; Robinson, 1966, 1968; Long & Gribben, 1969; Schiller & Greenfield, 1969; Purcell & Stewart, 1975; Dember et al., 1978; Kristofferson et al., 1979; Byron & Banks, 1980; Tenkink & Werner, 1981; Purcell et al., 1982; Briscoe et al., 1983). Metacontrast is a special type of backward masking where the target and mask stimuli do not spatially overlap. Breitmeyer et al. (1981) showed that maximum target recovery in metacontrast occurs when M2 temporally precedes M1. Furthermore, their results show that for the T–M2 stimulus onset asynchrony (SOA) range where target recovery occurs, there is no concomitant change in the visibility of the primary mask M1, indicating a dissociation between target recovery and the visibility of the primary mask M1. For the T–M2 SOA range where the visibility of M1 is suppressed, the opposite dissociative effect is observed, that is, there is no concomitant change in the visibility of the target. This double dissociation is taken as strong evidence against single-channel/single-process models of metacontrast, which attribute the visibility of a stimulus and its masking effectiveness to the same process. On the other hand, these findings can be explained by the dual-process REtino-COrtical Dynamics (RECOD) model (Öğmen, 1993; Breitmeyer & Öğmen, 2000, 2006). An extensive discussion of this model and its predictive scope can be found in Breitmeyer and Öğmen (2006, Chapter 5). In Öğmen et al. (2006a), we presented simulations showing that this model can account quantitatively for the double dissociation reported by Breitmeyer et al. (1981). In a recent study, published in Vision Research (Öğmen et al., 2006b), we analyzed further this model and derived the novel prediction that contrast dependence of metacontrast and target recovery should parallel the contrast dependence of afferent magnoand parvocellular pathways, respectively. In a psychophysical experiment, we tested this prediction by systematically varying M2’s contrast and the M1–M2 SOA. At the optimal M1–M2 SOA, the target recovery effect increased with M2’s contrast without saturating, but at the optimal M1–M2 metacontrast SOA, the reduction of M1’s visibility saturated very rapidly as M2’s contrast increased. Quantitative comparisons of model simulations with psychophysical results provided additional support for our prediction. We concluded that metacontrast masking is driven by signals originating from the magnocellular pathway and that target recovery in metacontrast is driven by signals originating from the parvocellular pathway. Recently, Skottun and Skoyles (2007) published in this Journal a commentary on our Vision Research paper. Here we are responding point by point to the issues raised by Skottun and Skoyles. Point 1: ‘‘because pure magnoand parvocellular streams do not exist beyond the primary cortex, any interactions between pure magnoand parvocellular inputs (such as, e.g., inhibition between the systems) should not be sought at a level beyond the primary visual cortex. ’’ This is not an objection to our model but rather an effort by Skottun and Skoyles to identify the locus of the interactions between the two streams posited in our model. The absence of pure parvoand magnocellular systems beyond V1 does not rule out the possibility that the interactions put forward in our model could occur beyond V1 because we do not postulate interactions between pure magnoand parvocellular inputs. Rather, as we stated in our paper, we postulate interactions between systems that receive their dominant input from magnoand parvocellular pathways (see, e.g., Öğmen et al., 2006b, p. 4728, line 15). Hence, we consider the suggestion that the interactions between the two streams in our model cannot occur beyond V1 to be inconsequential to our results. Skottun and Skoyles arrive at the conclusion that the interactions between the two pathways, as described in our model, cannot occur beyond the primary visual cortex based on the findings indicating a certain level of mixing of these inputs in V1. As evidence for the absence of ‘‘pure’’ parvoand magnocellular systems beyond V1, Skottun and Skoyles cite studies that have shown mixing of parvoand magnocellular signals within some layers and in some neurons of V1. But such mixing within the primary visual cortex is not inconsistent with the well-demonstrated fact that distinct groups of extrastriate neurons show largely independent influences of parvoand magnocellular subdivisions. For example, Maunsell et al. (1990) studied the effect of selectively blocking parvoand magnocellular layers of the LGN on MT neural responses in macaque monkeys. They found that blocking magnocellular layers consistently reduced MT responses and that the reduction was pronounced and often complete. In contrast, blocking parvocellular layers of the LGN rarely affected MT responses. Thus, it appears that a majority of MT neurons are influenced far more by magnocellular input than by parvocellular input. Visual Neuroscience (2008), 25, 611–616. Printed in the USA. Copyright 2008 Cambridge University Press 0952-5238/08 $25.00 doi:10.1017/S0952523807080649