Mariagrazia Capizzi (1), Giovanna Mioni (2) y Antonino Visalli (2)
(1) Dept. Psicología Experimental y Centro de Investigación Mente Cerebro y Comportamiento (CIMCYC), Universidad de Granada, España
(2) Dept. General Psychology, University of Padua, Italia
(cc) Mariagrazia Capizzi.
Time processing in the millisecond-to-seconds range is essential to many daily activities, including dancing, playing sports, and music. A key question in the field is how older adults process time within this range, as previous studies have yielded inconclusive results. In a recent lifespan study, we addressed this question by examining a large sample of participants ranging from 20 to 85 years, who completed two timing tasks in a single session, one requiring implicit (incidental use of time) and the other explicit (deliberate use of time) processing. Our findings corroborate previous research by showing age-related differences only in explicit, but not in implicit timing, offering valuable insight into how timing abilities change across the lifespan.
Remember “Uncle Joseph” and his breakfast routine of making toast? (Capizzi, et al., 2022). In our previous outreach article, we coined this nickname to illustrate an older adult in a seniors’ home who was assisted in preparing breakfast. This scenario served as an opening example to explain the difference between implicit and explicit timing tasks. “Implicit timing” is used incidentally to complete a task where time itself is not the primary focus, whereas “explicit timing” occurs when you are asked to process time, such as when judging the duration of an interval (Coull & Nobre, 2008). Accordingly, implicit timing comes into play when Uncle Joseph anticipates that the chance of his toast popping up from the toaster is higher as time passes, allowing him to be prepared. In contrast, explicit timing would be involved if he were asked to estimate how much time had passed between pressing the toaster lever and the toast popping up.
Experimentally, implicit and explicit timing can be studied using tasks that resemble this breakfast scenario. For example, in an implicit timing task, a target (such as the toast popping up) is preceded by a warning signal (like the toaster lever) with varying time intervals or “foreperiods” (known as a foreperiod task). If the target does not appear after a shorter interval, the probability of its appearance increases over time, leading to faster response times at longer intervals. Since participants are instructed only to respond to the target rather than explicitly track time, this task is considered implicit. In the explicit timing task, participants are asked to memorize both a short and a long standard duration and then classify intermediate durations as closer to either the short or the long standard (known as a time bisection task).
In a previous study (Capizzi et al., 2022), we found that age and cognitive decline in older adults affected implicit and explicit timing differently, with only implicit timing abilities being preserved during aging. In other words, Uncle Joseph would have no difficulty implicitly predicting when his toast would be ready, but he would show greater variability in estimating how much time had elapsed for the toast to pop up. Because our conclusions about age-related effects on implicit and explicit timing were based on a relatively narrow age range, we sought to replicate and expand them by adopting a more comprehensive lifespan approach. In a follow-up study (Visalli et al., 2024), we tested 307 healthy adults ranging in age from 20 to 85 years, who completed the same implicit (foreperiod task) and explicit (time bisection) tasks used in our earlier research, as described above. Our study had two main strengths compared to previous research: a broader age range and a large sample size. As expected, the older the participants, the greater the variability (smaller precision) in discriminating durations across trials. In contrast, implicit timing processing remained largely unaffected by age, as evidenced by faster response times to targets occurring at longer intervals.
Having replicated the difference between implicit and explicit time processing in our lifespan study, a natural question arises: What explains the age-related differences between these two tasks? The simplest explanation is that explicit timing tasks demand more cognitive resources than implicit ones. But there’s likely more to the story.
Neurobiological models of timing suggest that distinct brain circuits might govern time processing depending on task demands (Turgeon et al., 2016). Thus, it is possible that the neural networks needed for explicit timing are more susceptible to age-related changes than those used for implicit timing. We also know that aging affects fronto-striatal circuits, which are key to temporal processing (Wild-Wall et al., 2008). Some compensatory mechanisms might mitigate declines in these networks, helping older adults to perform adequately in tasks with minimal cognitive demands (like implicit timing) but not in more demanding tasks (like explicit timing). Finally, it has been proposed that older adults rely on resilient predictive mechanisms to compensate for decline (Turgeon & Wing, 2012). This would give them an advantage in tasks involving temporal predictions, such as the implicit timing task.
These possibilities are not mutually exclusive. Together, they make the age-related differences in explicit and implicit timing an exciting area for future research, offering valuable insights into how we deal with timing demands throughout the aging process.
References
Capizzi, M., Visalli, A., Faralli, A., & Mioni, G. (2022). Explicit and implicit timing in older adults: Dissociable associations with age and cognitive decline. PLoS ONE, 17(3): e0264999.
Coull, J. T., & Nobre, A. C. (2008). Dissociating explicit timing from temporal expectation with fMRI. Current Opinion in Neurobiology, 18, 137-144.
Turgeon, M., Lustig, C., & Meck, W. H. (2016). Cognitive aging and time perception: Roles of Bayesian optimization and degeneracy. Frontiers in Aging Neuroscience, 8,102.
Turgeon, M., & Wing, A. M. (2012). Late onset of age-related difference in unpaced tapping with no age-related difference in phase-shift error detection and correction. Psychology and Aging, 27, 1152–1163.
Visalli, A., Capizzi, M., & Mioni, G. (2024). Explicit and implicit timing across the adult lifespan. Psychology and Aging. Advance online publication. https://doi.org/10.1037/pag0000866
Wild-Wall, N., Willemssen, R., Falkenstein, M., & Beste, C. (2008). Time estimation in healthy ageing and neurodegenerative basal ganglia disorders. Neuroscience Letters, 442, 34–38.
Manuscript received on October 26th, 2024.
Accepted on January 29th, 2025.
This is the English version of
Capizzi, M., Mioni, G., y Visalli, A. (2025). ¡Prepárate para tu tostada! Procesamiento temporal implícito y explícito a lo largo del ciclo de vida. Ciencia Cognitiva, 19:2, 38-40.
