Main article
Categorization task
Categorization responses
Proportion of ‘category B’ responses for each morph level and morph series separately, averaged across participants. Colored dots indicate the empirical proportions for responding ‘category B’. Colored lines indicate} the mean posterior predictions from the model and shaded regions indicate 95% highest density continuous intervals of the posterior predictive distributions. The black dashed vertical line indicates the category boundary as defined based on the empirical proportions. In this figure, the proportion ‘category B’ responses increases more steeply across morph levels for the recognizable than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the data points to see the related stimuli as well as the exact percentage category B responses and the number of trials related to each data point.
Estimated pairwise differences between the posterior distributions for the effect of morph level on the categorization responses for each of the different recognizable and non-recognizable morph series combinations, in logodds units. Black dots and intervals represent the mean, 66%, and 95% highest density continuous interval (HDCI) for each slope or difference value. The black vertical line indicates a slope or difference in slope of zero. This figure confirms that all morph series show a positive slope across morph levels, and that the effect of morph level is larger for each of the recognizable morph series than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the intervals to see the related mean and 95% HDCI for each distribution.
Categorization reponse times
Categorization response times for each morph level and morph series separately, averaged across participants. Colored dots indicate the empirical mean response times in the categorization task.Colored lines indicate the mean posterior predictions from the model and shaded regions indicate 95% highest density continuous intervals of the posterior predictive distributions. The black dashed vertical line indicates the category boundary as defined based on the empirical categorization proportions. In this figure, the recognizable series show stronger differences in mean response time across morph levels than the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the data points to see the related stimuli as well as the exact mean response time and the number of trials related to each data point.
Estimated pairwise differences between the posterior distributions for the quadratic effect of morph level on categorization response times for each of the different recognizable and non-recognizable morph series combinations. Black dots and intervals represent the mean, 66%, and 95% highest density continuous interval (HDCI) for each slope or difference value. The black vertical line indicates a slope or difference in slope of zero. This figure confirms that all recognizable morph series show a quadratic effect of morph level different from zero, and that the quadratic effect of morph level is larger (i.e., more negative, indicating higher response times for the middle morph levels than for the extremes) for each of the recognizable morph series than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the intervals to see the related mean and 95% HDCI for each distribution.
Discrimination task
Proportion of ‘different’ responses in the successive discrimination task for each stepsize, trial type (i.e., between-category vs. within-category), and morph series separately, averaged across participants. Bars indicate the empirical proportions for responding ‘different’. The black dots indicate the mean posterior predictions from the model and the error bars indicate the 95% highest density continuous intervals (HDCI) of the posterior predictive distributions. In this figure, the difference between the darker and the lighter bars (i.e., the category boundary effect: more ‘different’ responses for between-category compared to within-category pairs, keeping stepsize equal) is on average higher for the recognizable than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the colored bars to see the exact percentage different responses, the mean and 95% HDCI of the posterior predictive distributions, and the number of trials related to each bar.
Difference in proportion of ‘different’ responses in the successive discrimination task when comparing between-category and within-category pairs, per stepsize and morph series, averaged across participants. Colored dots are the empirical differences in the proportion of ‘different’ responses. The black dots and intervals indicate the mean and the 95% highest density continuous intervals (HDCI) of the expected values for the posterior predictive distributions. In this figure, the category boundary effect (i.e., more ‘different’ responses for between-category compared to within-category pairs, keeping stepsize equal) is on average higher for the recognizable than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the data points to see the exact difference in percentage as well as the mean and 95% HDCI of the expected values for the posterior predictive distributions related to each data point.
Estimated pairwise differences between the posterior distributions for the intercept (A), effect of stepsize (B), effect of trial type (within-category = 0, between-category = 1; C), and interaction between stepsize and trial type (D) on the probability of responding ‘different’ in the successive discrimination task, for each of the different recognizable and non-recognizable morph series combinations, in logodds units. Black dots and intervals indicate the mean, 66%, and 95% highest density continuous interval (HDCI) for each slope or difference value. The black vertical line indicates a difference in slope of zero. In this figure, the estimated effect of stepsize is larger for the recognizable than for the non-recognizable morph series (B). The main effect of trial type is larger for the recognizable series car-tortoise and penguin-child than for all non-recognizable morph series (C). The interaction effect between stepsize and trial type is more negative for the recognizable series penguin-child than for all non-recognizable series (D). Note. In the interactive version of this figure, you can hover over the intervals to see the related mean and 95% HDCI for each distribution.
Proportion of ‘different’ responses in the successive discrimination task for each stepsize, stimulus pair, and morph series separately, averaged across participants and stimulus order within the pair. Stimulus pairs are ordered per stepsize and from left to right in the morph series as presented in Figure 3. Bars indicate the empirical proportions for responding ‘different’.} The black dots indicate the mean posterior predictions from the model and the grey error bars indicate the 95% highest density continuous intervals (HDCI) of the posterior predictive distributions. In this figure, a clear, gradual, ‘peaked’ pattern can be observed for the recognizable morph series, where pairs that include stimuli close to the reference points lead to a lower probability of responding ‘different’ than pairs that include stimuli further away from the reference points, while keeping the physical distance between the stimuli in the pair (i.e., stepsize) equal. This peaked pattern is much less pronounced for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the colored bars to see the stimuli involved in the pair, the exact percentage different responses, the mean and 95% HDCI of the posterior predictive distributions, and the number of trials related to each bar.
Prediction of probability of responding ‘different’ in the successive discrimination task based on categorization probabilities of individual stimuli in a pair in the categorization task. Bars are the empirical proportions for responding ‘different’ per stepsize, stimulus pair, and morph series, averaged across participants and stimulus order within the pair. The black dots and lines indicate the predictions based on the estimated mean categorization probabilities for the stimuli in a pair. Note. In the interactive version of this figure, you can hover over the colored bars to see the stimuli involved in the pair, the exact percentage different responses, the mean and 95% HDCI of the posterior predictive distributions, and the number of trials related to each bar.
Similarity judgment task
Standardized similarity scores for each stepsize, trial type (i.e., between-category vs. within-category), and morph series separately, averaged across participants. Grey dots indicate the raw standardized similarity scores. For the conditions that contain less trials, these grey dots are not always clearly visible. The colored dots and error bars indicate the mean posterior predictions from the model and the 95% highest density continuous interval (HDCI) of the posterior predictive distributions. In this figure, the difference between the darker and the lighter intervals (i.e., the category boundary effect: between-category pairs rated as less similar than within-category pairs, keeping stepsize equal) is on average larger for the recognizable than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the intervals to see the exact similarity score, the mean and 95% HDCI of the posterior predictive distributions, and the number of trials related to each interval.
Difference in standardized similarity score when comparing between-category and within-category pairs, per stepsize and morph series, averaged across participants. Colored dots are the empirical differences in the standardized similarity scores. The black dots and intervals indicate the mean and the 95% highest density continuous intervals (HDCI) of the expected values for the posterior predictive distributions. In this figure, the category boundary effect (i.e., lower similarity scores for between-category compared to within-category pairs, keeping stepsize equal) is on average higher for the recognizable than for the non-recognizable morph series. Note. In the interactive version of this figure, you can hover over the data points to see the exact difference in similarity as well as the mean and 95% HDCI of the expected values for the posterior predictive distributions related to each data point.