Visual experience forms a multidimensional pattern that is not reducible to a single measure: Evidence from metacontrast masking

Abstract

A metacontrast masking paradigm was employed to provide evidence for the richness and diversity of our visual experience. Square- and diamond-shaped targets were followed by square- and diamond-shaped masks at varying stimulus onset asynchronies (SOAs), resulting in shape-congruent and shape-incongruent trials. In Experiment 1, participants reported in each trial how they perceived target and mask. After extended training, seven different aspects of the target could be distinguished as specific percepts in this metacontrast masking paradigm. These percepts encompass aspects including the temporal distance between both stimuli, the perceived contrast of the target, and motion percepts resulting from the interplay between the target and mask. Participants spontaneously reported each of these percepts, and the frequency of reports varied systematically with SOA and the congruency between target and mask. In Experiment 2, we trained a new group of participants to distinguish each of these target percepts. Again, the frequency of reports of the specific percepts varied with SOA and congruency, just as in Experiment 1. In a last session, we measured objective discrimination performance yielding the typical individually different masking functions across SOAs. An examination of the relation between the frequencies of reports of subjective percepts and objective discrimination performance revealed multiple dissociations between these measures. Results suggest a multidimensional pattern of subjective experiences under metacontrast, which is reflected in dissociated subjective and objective measures of visual awareness. As a consequence, awareness cannot be assessed exhaustively by a single measure, thus challenging the use of simple one-dimensional subjective or objective measures in visual masking.

Figure 1.

Trial sequence (A) and stimuli (B) that were used in all experiments.

Figure 2.

Classification of spontaneous descriptions in Experiment 1 based on rater 1. (A) Percentage of participants, whose spontaneous descriptions in the training phase were classified into the respective percept categories in Experiment 1a (top) and Experiment 1b (bottom). (B) Percentages of participants whose spontaneous descriptions in the training phase were classified into the respective number of seven percept categories (without the residual category Other) for Experiment 1a (gray bars) and Experiment 1b (black bars).

Figure 3.

Mean absolute frequencies of classified reports in the test phase of Experiment 1 for each of the seven percept categories as a function of SOA and congruency. Error bars depict within-subject standard error (Loftus & Masson, 1994). Numbers in brackets indicate the number of participants on which each perceptual category is based (rater 1/rater 2). Maximum number of trials was N = 56. The absolute number of participants was 33.

Figure 4.

Percentages of trials in which participants reported to perceive a specific percept category in Experiment 2 (“yes” responses); 100% refers to the total number of trials in each percept category (N = 576), and points represent the data of single participants. Lines and boxes represent the mean percentage averaged across participants and its 95% confidence interval, respectively. Shaded areas represent the density distribution of reports within each category. On each trial, participants were asked for only one of the seven percepts. The percept that we asked for varied blockwise.

Figure 5.

Mean percentages of “seen”-reports as a function of SOA, congruency, and percept category in Experiment 2. Error bars depict within-subject standard error (Loftus & Masson, 1994).

Figure 6.

Relation of the time courses of reports across SOA in Experiment 1 (x-axis) and Experiment 2 (y-axis) shows close correspondence for all percepts. Relative frequency of reports are normalized to M = 0 for each percept category and congruency condition so that effects of congruency and differences between percepts are diminished. Data from Experiment 1 are based on rater 1. For data based on Rater 2, see Supplementary Figure S2.

Figure 7.

Performance in the objective discrimination task in Experiment 2. Averaged across all participants, performance decreases with increasing SOA (A). Individual masking functions show decreasing courses (B–D), U-shaped courses (E), and flat-line or increasing courses (F).