Experiment 1 aimed to explore in adults how the recognition of images evolves over time, depending on whether they were meaningful or meaningless.
Results And Discussion
The hits (i.e., when the image is old and the participant's response is old) and the false alarms (FA, i.e., when the image is new and the participant's response is old) observed in the recognition task depending of the type of images, the exposure duration, the number of exposures and the delay are shown in Supplementary materials, Table 1. The ROC curves in each condition derived from the confidence ratings are shown in Supplementary materials, Fig. 1. Examination of the zROC (which corresponds to z scores of hits and FA plotted as coordinates) revealed a slope almost always different than 1, suggesting Gaussian distributions of unequal variance in responses. Therefore, recognition accuracy was calculated using the discriminability measure of da 38. Each da was computed separately from the false-alarm and hit rates for each subject and for each type of image (meaningless vs. meaningful) and exposure condition (120 vs. 1920ms and 1 vs. 2 exposures) and was corrected by the slope of the zROC in each condition. The da is calculated as follows:
where s corresponds to the zROC slope, zH to the z scores of the hits and zF to the z-scores on the FA. The da values are illustrated Fig. 3.
To minimize both Type I and Type II errors, we conducted several analyses instead of only one that would include the all factors. In a first analysis, we explored the impact of the number of exposures and of the exposure duration on memory. A repeated-measures ANOVA was conducted on the da with Delay (immediate, 3-weeks, and 6-weeks) as between-subject factors, with Exposure duration (1920ms vs. 120ms) and Number of exposures (1 vs. 2) as within-subject factors. The analysis revealed a main effect of each factor: Delay, F(2,33) = 26.535, p < .001, η²G = 0.55, Exposure duration, F(1,33) = 329.608, p < .001, η²G = 0.49; Number of exposures, F(1,33) = 137.536, p < .001, η²G = 0.29. The interactions [Number of exposures x Exposure duration, F(1,33) = 64.069, p < .001, η²G = 0.084], [Delay x Exposure duration, F(2,33) = 8.183, p < .001, η²G = 0.046] and [Delay x Number of exposure x Exposure duration, F(2,33) = 4.020, p < .05, η²G = 0.01] were all reliable. The interaction [Delay x Number of exposures, F(2,66) < 1, η²G = 0.002] was not reliable.
Those results show that 1) memory for images decayed strongly over weeks; 2) memory benefited from multiple and extended exposures; 3) multiple and extended exposures had a potentiating effect on memory; 4) the benefit of an extended exposure was even more pronounced across weeks.
In a second series of analyses, we compared how memory for meaningless vs. meaningful images evolved across the weeks separately within each exposure condition, i.e. 120ms-1exposure, 120ms-2exposures, 1920ms-1exposure, 1920ms-2exposures. We carried out four repeated-measure ANOVA on the da with Delay (immediate, 3-weeks, and 6-weeks) as between-subject factor, and Type of images (meaningful vs. meaningless) as within-subject factor.
The analysis of the condition “120ms − 1exposure” showed a main effect of Delay, F(1,33) = 13.776, p < .001, η²p = 0.455, Type, F(1,33) = 29.349, p < .001, η²p = 0.471, and a reliable interaction between both factors, F(2,33) = 10.863, p < .001, η²p = 0.397. Consistently with our prediction, the results revealed a strong impact of semantic information when memory was tested immediately after learning. Nevertheless, they also suggest that almost nothing remains in memory after three weeks, whether the images were meaningless or meaningful. Note that the reliable interaction was probably due to the fact that memory performance for the meaningless images had dropped to chance level across weeks.
The ANOVA conducted on the da observed in the condition “120ms − 2 exposures” yielded a main effect of Delay, F(1,33) = 19.307, p < .001, η²p = 0.539 and Type, F(1,33) = 58.296, p < .001, η²p = 0.639. The interaction between both factors was marginally significant, F(2,33) = 3.118, p = .058, η²p = 0.159. Again, the results show a strong impact of semantic information on memory and a strong impact of the delay in both conditions. For the meaningful images only, a second exposure had allowed to maintain some memories for at least 6 weeks.
For the condition “1920ms − 1exposure”, the analysis revealed a main effect of Delay, F(1,33) = 35.365, p < .001, η²p = .682 and Type, F(1,33) = 25.910, p < .001, η²p = .440, but no reliable interaction between both factors, F(2,33) = 1.895, p = .166, η²p = .103. The analysis conducted in the condition “1920ms − 2exposures” yielded a main effect of Delay, F(1,33) = 17.719, p < .001, η²p = .519 and Type, F(1,33) = 8.119, p < .01, η²p = .197, as well as a reliable interaction between factors, F(2,33) = 6.503, p < .005, η²p = .283. Overall, the results observed for longer exposures suggest a strong effect of semantic information when memory was accessed immediately after learning, but this benefit tended to disappear across weeks. Contrary to the 120ms-exposure conditions, the reliable interaction was not due to the fact that memory performance approached a floor effect over weeks. After 6-weeks, there was no evidence of benefit for the meaningful images as compared to the meaningless ones when there were presented twice. This result goes against our initial prediction
The false alarms are illustrated in Table 1. The FA observed in the novel-gist meaningful and meaningless conditions were compared using a repeated-measures ANOVA. This analysis showed a marginal effect of Type, F(1,33) = 4.105, p = .051, ηp2 = 0.11, a reliable effect of Delay, F(1,33) = 6.659, p < .005, ηp2 = 0.288 and a reliable interaction [Type x Delay, F(2,66) = 4.201, p < .05, ηp2 = 0.20]. Those results indicated that the false alarms increased more across weeks for meaningful images than for meaningless images.
To examine memory distortion regarding the new images that depicted a category used in the learning phase, a series of paired samples t-Test was conducted between the novel-gist images and the old-gist lures (see Table 1). Those analyses showed that the false alarms were higher for the old-gist lures than for the novel-gist images in the conditions [Immediate, 120ms-1exposure, t = 2.65, p < .05] and [Immediate, 120ms-2exposures, t = 2.46, p < .05] and that the false alarms were marginally higher for the novel-gist images in the conditions [6-weeks, 120ms-2exposures, t = 2.081, p = .062] and [6-weeks, 1920ms-2exposures, t = 2.196, p = .051]. We also conducted Bayes Factor analyses for any null statistical outcomes to evaluate the degree of evidence for the null versus alternative hypothesis. Specifically, we computed Bayes Factor10, which indicates the likelihood ratio of evidence given both the null and alternative hypotheses (e.g., BF10 = (likelihood of data given H1 / likelihood of data given H0)). Thus, the outcome value for BF10 indicates the likelihood of the data to occur in the alternative compared to the null hypothesis. Importantly, the outcomes of Bayes Factor analyses are considered on a continuous scale reflecting the degree of evidence for the null versus alternative hypothesis. Those Bayes factors analyses (see Table 1) confirmed the conclusions of paired samples t-Test, except for the conditions [6-weeks, 120ms-2exposures, t = 2.081, p = .062] and [6-weeks, 1920ms-2exposures, t = 2.196, p = .051], for which a difference between the novel-gist images and the old-gist lures was privileged compared to the null hypothesis. Therefore, in regard to the Bayesian statistics, the old-gist lures triggered more false alarms in the immediate conditions (when the images depicting a related gist were presented briefly in the learning phase). However, this effect disappeared across weeks. Surprisingly, the opposite patterns tended to emerge at 6-weeks: the old-gist lures for images that were presented twice generated less false alarms than the new images that depicted a novel gist. Though the last statistics remain weak to firmly accept this hypothesis, they nevertheless allow us to reject the hypothesis that the false alarms increase more for the old-gist lures than for the novel-gist images. Thus, contrary to our prediction, the false alarms for the old-gist lures did not increase more across weeks than the false alarms on new images depicting an original gist.