Fig 1.
The Diffusion Model [17].
Illustration of the diffusion process for the classification of an “old” item as either “old” or “new”. The decision process starts at point z and moves toward the upper boundary or lower boundary by a drift rate ν. In this example, “old” response corresponds to the upper (and correct) boundary a, and is driven by a positive drift rate. Three sample paths are illustrated with responses 1 and 2 ending in a correct response at the upper boundary (“old”) but path 3 drifts toward the lower boundary 0, ending in an incorrect response “new”. RT = reaction time; t0 = perceptual motor RT.
Table 1.
Mean Arousal and Valence Ratings of the Experimental Stimuli.
Table 2.
Means of Diffusion Model Parameters for Participants with Good Model Fit.
Table 3.
Arousal and Valence Effects: Means of Signal Detection Parameters and Median Reaction Times for Participants with Good Model Fit.
Table 4.
Means of Signal Detection Parameters, Median Reaction Times and Mean Diffusion Model Parameters of Low-Arousal Valence Analyses for Participants with Good Model Fit.
Fig 2.
Box plots of the distribution of response bias values for high and low-arousal items and negative and positive items at each lag. The line in each box represents the median. Response bias values above .5 (to the right of the dotted line) indicate a bias to classify items as “old”, whereas values below .5 indicate a bias to classify items as “new”. Error bars represent standard error. Hi = high-arousal items; Lo = low-arousal items; Neg = negative items; Pos = positive items; 1-day = 1-day study-test lag; 7-day = 7-day study-test lag.
Fig 3.
Mean memory bias values for high and low-arousal items, and negative and positive items at each lag. Positive memory bias values indicate familiarity bias, whereas negative values indicate novelty bias. Error bars represented the standard errors. Hi = high-arousal items; Lo = low-arousal items; Neg = negative items; Pos = positive items; 1-day = 1-day study-test lag; 7-day = 7-day study-test lag.