Individual pattern representations are context independent, but their collectiverepresentation is context dependent

Abstract

We studied context dependency of the representations underlying perceptual “goodness”. Three experiments used a same–different task with classical Garner 5-dot patterns presented with an interstimulus interval (ISI) of 500 ms. Same patterns were allowed to be rotated or reflected versions of each other. Pattern goodness was varied according to rotation and reflection equivalence, using GarneR&Rsquo;s equivalence set size (ESS) measure. The ESS of both first and second patterns affected reaction time and accuracy. A model based on assumptions that GarneR&Rsquo;s equivalence sets constitute the generic representation of these patterns and that items within these sets are accessed serially was fitted to the data. Excellent fits were obtained, which were robust against frequency-induced bias at the level of the individual pattern, but sensitive to such bias at the level of the equivalence set. It was concluded that individual pattern representations are context independent, whereas their collective representations are context dependent. Simplicity and likelihood principles, therefore, seem to apply to different levels of a representation hierarchy.

Acknowledgments

This work was supported by Grant La 1281/2-1 from the Deutsche Forschungsgemeinschaft (DFG) to Thomas Lachmann. Thanks are due to Robert Proctor, Lester Krueger, Beverly Roskos-Ewoldson, Peter van der Helm, and John Flowers for their critical and very helpful remarks on earlier drafts.

Notes

It could, for instance, be argued that the frequency of individual stimuli affects their encoding (Blackman, 1980; Miller & Pachella, 1973; Smothergill & Kraut, 1981; but see also Pachella & Miller, 1976, who found effects of stimulus probability in a same–different task only for name matches but not for physical matches, and De Jong & Sanders, 1986, who failed to find effect of probability on eye-fixations in a same–different task).

Note: Same combinations consist of patterns from one set; IM (identity match) are pairs of identical patterns, CM (categorical match) are the remaining combinations. Different pairs (NM = nonmatch) consist of patterns from two sets of either the same or different ESS (equivalent set size). The total number of pairs is the total number of possible combinations in a given condition. The number of pairs included is the product of the total number of pairs and the frequency of pair inclusion (i.e., the multiplication factor that was applied in order to adjust the pair frequency in accordance with the particular balancing strategy).

Note: RT = reaction time. IM = identity match. CM = categorical match. NM = nonmatch. ESS = equivalent set size.

^aIn ms. ^bIn percentages.

for low degree of freedom = R² − [(1 − R²) a] / (b − a*), with a = number of independent variables; b = sum of case weights; a* = number of coefficients (including intercept).

Note: IM = identity match. CM = categorical match. NM = nonmatch. ESS = equivalent set size.

The two NM pairs involving patterns of ESS = 1 were not included in the experiment; thus the total number of possible combinations of the 90 patterns is 8,098.

Note: RT = reaction time. IM = identity match. CM = categorical match. NM = nonmatch. ESS = equivalent set size.

^aIn ms. ^bIn percentages.

Note: RT = reaction time. IM = identity match. CM = categorical match. NM = nonmatch. ESS = equivalent set size.

^aIn ms. ^bIn percentages.

Note: RT = reaction time. IM = identity match. CM = categoricalmatch. NM = nonmatch. ESS = equivalent set size.

^aIn ms. ^bIn percentages.

Note: RT = reaction time. IM = identity match. CM = categorical match. NM = nonmatch. ESS = equivalent set size.

Unbiased: includes all pairs except those of which at least one pattern was frequency biased or belonged to the same equivalence set as a frequency-biased pattern. Rest of the biased set (biased set): includes all pairs that contain at least one pattern that belongs to the equivalence set of a frequency-biased pattern, except that pattern itself.

Biased pattern: includes all pairs that contain at least one pattern that was frequency-biased.

^aIn ms. ^bIn percentages.