Mental association of time and valence

Abstract

Five experiments investigated the association between time and valence. In the first experiment, participants classified temporal expressions (e.g., past, future) and positively or negatively connotated words (e.g., glorious, nasty) based on temporal reference or valence. They responded slower and made more errors in the mismatched condition (positive/past mapped to one hand, negative/future to the other) compared with the matched condition (positive/future to one hand, negative/past to the other hand). Experiment 2 confirmed the generalization of the match effect to nonspatial responses, while Experiment 3 found no reversal of this effect for left-handers. Overall, the results of the three experiments indicate a robust match effect, associating the past with negative valence and the future with positive valence. Experiment 4 involved rating the valence of time-related words, showing higher ratings for future-related words. Additionally, Experiment 5 employed latent semantic analysis and revealed that linguistic experiences are unlikely to be the source of this time-valence association. An interactive activation model offers a quantitative explanation of the match effect, potentially arising from a favorable perception of the future over the past.

Keywords: Concepts; Time perception; Valence.

Fig. 1

Mean reaction time (RT) and mean percentage correct (PC) in Experiment 1 as a function of Match (match vs. mismatch), Domain (valence vs. time), and Congruency (congruent condition vs. incongruent condition). The panels on the left depict the result for RT, whereas the panels on the right depict the PC result. The two top panels show the results of the congruent condition and the two bottom panels for incongruent condition. The error bars represent ±1 SE, where SE denotes the standard error of the mean. SE was computed with the R routine summarySE (Hope, 2022)

Fig. 2

Mean response time (RT) and mean percentage of correct (PC) in Experiment 2 as a function of stimulus domain (time vs. valence) and time–valence match. The error bars reflect ±1 SE, where SE denotes the within-subject error of mean computed according to Cousineau (2007) with the correction suggested by Morey (2008). SE was computed with the R routine summarySE (Hope, 2022)

Fig. 3

Mean response time (RT) and mean percentage of correct (PC) in Experiment 3 as a function of stimulus domain (time vs. valence) and time–valence match. The error bars reflect ±1 SE, where SE denotes the within-subject error of mean computed according to Cousineau (2007) with the correction suggested by Morey (2008). SE was computed with the R routine summarySEwithin (Hope, 2022)

Fig. 4

Mean rating as a function of time (past vs. future) for younger and older adults. The error bars present the 95% confidence interval. CI was computed with the R routine summarySEwithin (Hope, 2022)

Fig. 5

Cosine similarity scores for the four categories of words used in Experiments 1–3. The error bars reflect ±1 SE

Fig. 6

An interactive activation model to account for the match effect observed in Experiments 1–3. A Architecture of this model. Four nodes represent past time (1), future time (2), negative valence (3), and positive valence (4). Mutual inhibition acts between Nodes 1 and 2 and between Nodes 3 and 4. By contrast, mutual excitation acts between Nodes 1 and 3 and between Nodes 2 and 4. Stimulus input activates the corresponding node. For example, past-related information activates Node 1 via input I₁. The concerted outputs O_i (i=1,...,4) of all four nodes determine the dynamic of response activation. B How these outputs drive the activation of the response Nodes A and B under the Match condition and the Mismatch condition.

Fig. 7

Predicted response activation as a function of time and Match condition for Model 1 (upper two panels) and Model 2 (lower two panels). The two left panels depict these functions for responses to past or negative words, whereas the panels on the right for responses to future or positive words. Appendix 2 contains the computational details