Abstract
Background: Researchers have devoted much effort in trying to understand how and why our subjective experience of time changes across the adult life-span. The cognitive apparatus that supports timing is integrally entwined with those supporting other cognitive processes including working memory, inhibition and speed of processing. Methods: One-hundred-eighty adults ranged from 19 to 87 years old participated in the study. A time discrimination task, with two standard intervals (short standard = 500 ms; long standard = 1500 ms) was used. Moreover, N-back and Stroop tasks were used to assess working memory, inhibition and speed of processing. Results: Data were analysed with a multilevel mixed model approach. Accounting for between-subject variability, we compared models in order to assess the better fit using chi-square likelihood-ratio test, Akaike information criterion and the Bayesian information criterion. Results showed a significant interaction between age, standard interval, comparison interval and speed of processing. Conclusion: Our study confirmed that younger participants were generally more accurate across conditions than older ones; we also showed that performance depended indeed on intervals, but also on speed of processing abilities across age.
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References
Allan, L. G. (1977). The time-order error in judgments of duration. Canadian Journal of Psychology, 31, 24–31. https://doi.org/10.3758/BF03204158.
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. https://doi.org/10.1016/j.jml.2007.12.005.
Balci, F., Meck, W. H., Moore, H., & Brunner, D. (2009). Timing deficits in aging and neuropathology. In J. L. Bizon & A. G. Woods (Eds.), Animal models of human cognitive aging (pp. 1–41). New York: Humana Press.
Bates, D., Mächler, M., Bolker, B. M., & Walker, S. C. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01.
Baudouin, A., Vanneste, S., Isingrini, M., & Pouthas, V. (2006). Differential involvement of internal clock and working memory in the production and reproduction of duration: A study on older adults. Acta Psychologica, 121, 285–296. https://doi.org/10.1016/j.actpsy.2005.07.004.
Baudouin, A., Clarys, D., Vanneste, S., & Isingrini, M. (2009). Executive functioning and processing speed in age-related differences in memory: Contribution of a coding task. Brain & Cognition, 71(3), 240–245. https://doi.org/10.1016/j.bandc.2009.08.007.
Baudouin, A., Isingrini, M., & Vanneste, S. (2018). Executive functioning and processing speed in age-related differences in time estimation: A comparison of young, old, and very old adults. Aging, Neuropsychology, & Cognition, 26, 264–281. https://doi.org/10.1080/13825585.2018.1426715.
Block, R. A., Zakay, D., & Hancock, P. A. (1998). Human aging and duration judgments: A meta-analytic review. Psychology & Aging, 13(4), 584–596. https://doi.org/10.1037/0882-7974.13.4.584.
Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference understanding AIC and BIC in model selection. Sociological Methods & Research, 33(2), 261–304. https://doi.org/10.1177/0049124104268644.
Dragulescu, A. A. (2014). xlsx: Read, write, format Excel 2007 and Excel 97. 2000/XP/2003 files.
Eckert, M. A., Keren, N. I., Roberts, D. R., Calhoun, V. D., & Harris, K. C. (2010). Age-related changes in processing speed: Unique contributions of cerebellar and prefrontal cortex. Frontiers in Human Neuroscience, 4, Art. 10. https://doi.org/10.3389/neuro.09.010.2010.
Eisler, H., Eisler, A. D., & Hellström, Å. (2008). Psychophysical issues in the study of time perception. In S. Grondin (Ed.), Psychology of time (pp. 75–110). Bingley: Emerald Group.
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. https://doi.org/10.1016/0022-3956(75)90026-6.
Fox, J. (2003). Effect displays in R for generalised linear models. Journal of Statistical Software, 8(15), 1–27. https://doi.org/10.18637/jss.v008.i15.
Gibbon, J., Church, R. M., & Meck, W. H. (1984). Scalar timing in memory. In J. Gibbon & L. G. Allan (Eds.), Timing and time perception (pp. 52–77). New York: The New York Academy of Science.
Gontier, E., Le Dantec, C., Leleu, A., Paul, I., Charvin, H., Bernard, C., et al. (2007). Frontal and parietal ERPs associated with duration discriminations with or without task interference. Brain Research, 1170, 79–89. https://doi.org/10.1016/j.brainres.2007.07.022.
Gontier, E., Paul, I., Le Dantec, C., Pouthas, V., Jean- Marie, G., Bernard, C., et al. (2009). ERPs in anterior and posterior regions associated with duration and size discriminations. Neuropsychology, 23, 668–678. https://doi.org/10.1037/a0015757.
Gontier, E., Hasuo, E., Mitsudo, T., & Grondin, S. (2013). EEG investigations of duration discrimination: The intermodal effect is induced by an attentional bias. PLoS One, 8(8), e74073. https://doi.org/10.1371/journal.pone.0074073.
Gooch, C. M., Stern, Y., & Rakitin, B. C. (2009). Evidence for age-related changes to temporal attention and memory from the choice time production task. Neuropsychology, Development, and Cognition Section B, Aging, Neuropsychology and Cognition, 16, 285–310. https://doi.org/10.1080/13825580802592771.
Grondin, S. (2010). Timing and time perception: Are view of recent behavioural and neuroscience findings and theoretical directions. Attention Perception & Psychophysics, 72, 561–582. https://doi.org/10.3758/APP.72.3.561.
Hellström, Å. (1985). The time-order error and its relatives: Mirrors of cognitive processes in comparing. Psychological Bulletin, 97, 35–61. https://doi.org/10.1037/0033-2909.97.1.35.
Hellström, Å., & Rammsayer, T. H. (2004). Effects of time order error, inter-stimulus intervals, and feedback in duration discrimination of noise bursts in the 50- and 1000-ms ranges. Acta Psychologica, 116, 1–20. https://doi.org/10.1016/j.actpsy.2003.11.003.
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2015). Package “lmerTest.” R Package Version, 0–2.
Lamotte, M., & Droit-Volet, S. (2017). Aging and time perception for short and long durations: A question of attention? Timing & Time Perception, 5, 149–167. https://doi.org/10.1163/22134468-00002086.
Lenth, R. V. (2016). Least-squares means: The R package lsmeans. Journal of Statistical Software, 69(1), 1–33. https://doi.org/10.18637/jss.v069.i01.
Lewis, P. A., & Miall, R. C. (2003a). Distinct systems for automatic and cognitively controlled time measurement: Evidence from neuroimaging. Current Opinion in Neurobiology, 13, 250–255. https://doi.org/10.1016/S0959-4388(03)00036-9.
Lewis, P. A., & Miall, R. C. (2003b). Brain activation patterns during measurement of sub- and supra-second intervals. Neuropsychologia, 41, 1583–1592. https://doi.org/10.1016/S0028-3932(03)00118-0.
Li, S. C., Lindenberger, U., & Bäckman, L. (2010). Dopaminergic modulation of cognition across the life span. Neuroscience & Biobehavioral Reviews, 34, 625–630. https://doi.org/10.1016/j.neubiorev.2010.02.003.
Lustig, C. (2003). Grandfather’s clock: Attention and interval timing in older adults. In W. H. Meck (Ed.), Functional and neural mechanisms of interval timing (pp. 261–293). Boca Raton: CRC Press.
Luszcz, M. A., & Lane, A. P. (2008). Executive function in cognitive, neuropsychological, and clinical aging. In S. M. Hofer & D. F. Alwin (Eds.), Handbook of cognitive aging: Interdisciplinary perspectives (pp. 193–206). Thousand Oaks: Sage Publications, Inc.. https://doi.org/10.4135/9781412976589.n12.
Macar, F., & Vitton, N. (1982). An early resolution of contingent negative variation (CNV) in time discrimination. Electroencephalography and Clinical Neurophysiology, 54(4), 426–435. https://doi.org/10.1016/0013-4694(82)90206-1.
McCormack, T., Brown, G. D., Maylor, E. A., Darby, R. J., & Green, D. (1999). Developmental changes in time estimation: Comparing childhood and old age. Developmental Psychology, 35, 1143–1155. https://doi.org/10.1037/0012-1649.35.4.1143.
McCormack, T., Brown, G. D., Maylor, E. A., Richardson, L. B. N., & Darby, R. J. (2002). Effects of aging on absolute identification of duration. Psychology & Aging, 17, 363–378. https://doi.org/10.1037/0882-7974.17.3.363.
Meck, W. H., Penney, T. B., & Pouthas, V. (2008). Cortico-striatal representation of time in animals and humans. Current Opinion in Neurobiology, 18(2), 145–152. https://doi.org/10.1016/j.conb.2008.08.002.
Mioni, G., Mattalia, G., & Stablum, F. (2013a). Time perception in severe traumatic brain injury patients: A study comparing different methodologies. Brain and Cognition, 81(3), 305–312. https://doi.org/10.1016/j.bandc.2012.12.005.
Mioni, G., Stablum, F., & Cantagallo, A. (2013b). Time discrimination in traumatic brain injury patients. Journal of Clinical and Experimental Neuropsychology, 35(1), 90–102. https://doi.org/10.1080/13803395.2012.755151.
Mioni, G., Stablum, F., & Grondin, S. (2014). Interval discrimination across different duration ranges with a look at spatial compatibility and context effects. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00717.
Mioni, G., Grassi, M., Tarantino, V., Stablum, F., & Bisiacchi, P. S. (2016). The impact of a concurrent motor task on auditory and visual temporal discrimination tasks. Attention Perception & Psychophysics, 78, 742–748. https://doi.org/10.3758/s13414-016-1082-y.
Niemi, P., & Näätänen, R. (1981). Foreperiod and simple reaction time. Psychological Bulletin, 89(1), 133–162. https://doi.org/10.1037/0033-2909.89.1.133.
Paul, I., Le Dantec, C., Bernard, C., Lalonde, R., & Rebaï, M. (2003). Event-related potentials in the frontal lobe during performance of a visual duration discrimination task. Journal of Clinical Neurophysiology, 20, 351–360. https://doi.org/10.1097/00004691-200309000-00007.
Perbal, S., Droit-Volet, S., Isingrini, M., & Pouthas, V. (2002). Relationships between age-related changes in time estimation and age-related changes in processing speed, attention, and memory. Aging, Neuropsychology, & Cognition, 9(3), 201–216. https://doi.org/10.1076/anec.9.3.201.9609.
Pfeuty, M., Ragot, R., & Pouthas, V. (2003). When time is up: CNV time course differentiates the roles of the hemispheres in the discrimination of short tone durations. Experimental Brain Research, 151(3), 372–379. https://doi.org/10.1007/s00221-003-1505-6.
Radua, J., Del Pozo, N. O., Gómez, J., Guillen-Grima, F., & Ortuño, F. (2014). Meta-analysis of functional neuroimaging studies indicates that an increase of cognitive difficulty during executive tasks engages brain regions associated with time perception. Neuropsychologia, 58, 14–22. https://doi.org/10.1016/j.neuropsychologia.2014.03.016.
Rammsayer, T. H. (2001). Ageing and temporal processing of durations within the psychological present. European Journal of Cognitive Psychology, 13, 549–565. https://doi.org/10.1080/09541440042000322.
RCore Team (2016). R: A language and environment for statistical computing. R Foundation for statistical computing, Vienna, Austria. URL: https://www.R-project.org/
RStudio Team (2016). RStudio: Integrated development for R. RStudio, Inc., Boston, MA URL: http://www.rstudio.com/
Rubia, K. (2006). The neural correlates of timing functions. In J. Glickson & M. Myslobodsky (Eds.), Timing the future: The case of time-based prospective memory (pp. 213–238). New York: World Scientific Publishing.
Rubia, K., & Smith, A. (2004). The neural correlates of cognitive time management: A review. Acta Neurobiologiae Experimentalis, 64, 329–340.
Salthouse, T. A. (1993). Speed mediation of adult age differences in cognition. Developmental Psychology, 29(4), 722–738. https://doi.org/10.1037/0012-1649.29.4.722.
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103(3), 403–428. https://doi.org/10.1037/0033-295X.103.3.403.
Salthouse, T. A., & Ferrer-Caja, E. (2003). What needs to be explained to account for age-related effects on multiple cognitive variables? Psychology & Aging, 18, 91–110. https://doi.org/10.1037/0882-7974.18.1.91.
Schaie, K. W., & Willis, S. (2015). Handbook of the psychology of aging (8th ed.). New York: Academic Press.
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. https://doi.org/10.3389/fnagi.2016.00102.
Vallesi, A., Mussoni, A., Mondani, M., Budai, R., Skrap, M., & Shallice, T. (2007a). The neural basis of temporal preparation: Insights from brain tumor patients. Neuropsychologia, 45, 2755–2763. https://doi.org/10.1016/j.neuropsychologia.2007.04.017.
Vallesi, A., Shallice, T., & Walsh, V. (2007b). Role of the prefrontal cortex in the foreperiod effect: TMS evidence for dual mechanisms in temporal preparation. Cerebral Cortex, 17, 466–474. https://doi.org/10.1093/cercor/bhj163.
Vallesi, A., McIntosh, A. R., & Stuss, D. T. (2009). Temporal preparation in aging: A functional MRI study. Neuropsychologia, 47, 2876–2881. https://doi.org/10.1016/j.neuropsychologia.2009.06.013.
Wagenmakers, E. J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin & Review, 11(1), 192–196.
Winter, B. (2013). Linear models and linear mixed effects models in R with linguistic applications. arXiv:1308.5499.
Xu, R., & Church, R. M. (2017). Age-related changes in human and nonhuman timing. Timing & Time Perception, 5, 261–279. https://doi.org/10.1163/22134468-00002092.
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Mioni, G., Cardullo, S., Ciavarelli, A. et al. Age-related changes in time discrimination: The involvement of inhibition, working memory and speed of processing. Curr Psychol 40, 2462–2471 (2021). https://doi.org/10.1007/s12144-019-00170-8
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DOI: https://doi.org/10.1007/s12144-019-00170-8