University of Groningen
Time & Other Dimensions
Schlichting, Nadine
DOI:
10.33612/diss.97434922
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Schlichting, N. (2019). Time & Other Dimensions. University of Groningen. https://doi.org/10.33612/diss.97434922
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References
Acerbi, L., Wolpert, D. M., & Vijayakumar, S. (2012). Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing. PLoS
Computational Biology, 8(11), e1002771. doi:10.1371/journal.pcbi.1002771
Addyman, C., French, R. M., & Thomas, E. (2016). Computational models of in-terval timing. Current Opinion in Behavioral Sciences, 8, 140–146. doi:10.1016/J. COBEHA.2016.01.004
Aksoy, E. E., Aein, M. J., Tamosiunaite, M., & Worgotter, F. (2015). Semantic parsing of human manipulation activities using on-line learned models for robot imitation. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 2875–2882). IEEE. doi:10.1109/IROS.2015.7353773 Allman, M. J., Teki, S., Griffiths, T. D., & Meck, W. H. (2014). Properties of the in-ternal clock: first- and second-order principles of subjective time. Annual Review
of Psychology, 65, 743–71. doi:10.1146/annurev-psych-010213-115117
Arnal, L. H., Doelling, K. B., & Poeppel, D. (2015). Delta-beta coupled oscilla-tions underlie temporal prediction accuracy. Cerebral Cortex, 25(9), 3077–3085. doi:10.1093/cercor/bhu103
Bates, D. M., Kliegl, R., Vasishth, S., & Baayen, H. (2015). Parsimonious mixed models. ArXiv Preprint. doi:arXiv:1506.04967
Bates, D. M., Mächler, M., Bolker, B., & Walker, S. (2014). Fitting Linear Mixed-Ef-fects Models using lme4. Journal of Statistical Software, 67(1), 51. doi:10.18637/ jss.v067.i01
Bausenhart, K. M., Dyjas, O., & Ulrich, R. (2014). Temporal reproductions are influenced by an internal reference: Explaining the Vierordt effect. Acta
Psycholo-gica, 147, 60–67. doi:10.1016/j.actpsy.2013.06.011
Bausenhart, K. M., Dyjas, O., & Ulrich, R. (2015). Effects of stimulus order on discrimination sensitivity for short and long durations. Attention, Perception, &
Psychophysics, 77, 1033–1043. doi:10.3758/s13414-015-0875-8
Bender, A., & Beller, S. (2014). Mapping spatial frames of reference onto time: a re-view of theoretical accounts and empirical findings. Cognition, 132(3), 342–382. doi:10.1016/j.cognition.2014.03.016
Bendixen, A., Grimm, S., & Schröger, E. (2005). Human auditory event-related potentials predict duration judgments. Neuroscience Letters, 383(3), 284–288. doi:10.1016/j.neulet.2005.04.034
Block, Richard A., Grondin, S., & Zakay, D. (2018). Prospective and retrospec-tive timing processes: Theories, methods, and findings. In A. Vatakis, F. Bal-cı, M. Di Luca, & Á. Correa (Eds.), Timing and Time Perception: Procedu-res, MeasuProcedu-res, and Applications (pp. 32–51). Leiden, The Netherlands: Brill. doi:10.1163/9789004280205_003
Boehm, U., Van Maanen, L., Forstmann, B., & Van Rijn, H. (2014). Trial-by-trial fluctuations in CNV amplitude reflect anticipatory adjustment of response cauti-on. NeuroImage, 96, 95–105. doi:10.1016/j.neuroimage.2014.03.063
Bonato, M., Zorzi, M., & Umiltà, C. (2012). When time is space: Evidence for a mental time line. Neuroscience and Biobehavioral Reviews, 36(10), 2257–2273. doi:10.1016/j.neubiorev.2012.08.007
Boroditsky, L. (2001). Does language shape thought?: Mandarin and English speakers’ conceptions of time. Cognitive Psychology, 43(1), 1–22. doi:10.1006/ cogp.2001.0748
Boroditsky, L., Fuhrman, O., & McCormick, K. (2011). Do English and Mandarin speakers think about time differently? Cognition, 118(1), 123–129. doi:10.1016/J. COGNITION.2010.09.010
Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436. Brown, S. W., Stubbs, D. A., & West, A. N. (1992). Attention, multiple timing, and
psychophysical scaling of temporal judgments. In Time, Action and Cogniti-on (pp. 129–140). Dordrecht: Springer Netherlands. doi:10.1007/978-94-017-3536-0_15
Brown, S. W. (1997). Attentional resources in timing: Interference effects in concur-rent temporal and nontemporal working memory tasks. Perception &
Psychophy-sics, 59(7), 1118–1140. doi:10.3758/BF03205526
Brown, S. W. (2006). Timing and executive function: Bidirectional interference between concurrent temporal production and randomization tasks. Memory &
Cognition, 34(7), 1464–1471. doi:10.3758/BF03195911
Brown, S. W., & West, A. N. (1990). Multiple timing and the allocation of attention.
Acta Psychologica, 75(2), 103–121. doi:10.1016/0001-6918(90)90081-P
Bueno, F. D., Morita, V. C., de Camargo, R. Y., Reyes, M. B., Caetano, M. S., & Cravo, A. M. (2017). Dynamic representation of time in brain states. Scientific
Reports, 7(1), 46053. doi:10.1038/srep46053
Bueti, D., & Macaluso, E. (2011). Physiological correlates of subjective time: Evi-dence for the temporal accumulator hypothesis. NeuroImage, 57(3), 1251–1263. doi:10.1016/j.neuroimage.2011.05.014
Bueti, D., & Walsh, V. (2009). The parietal cortex and the representation of time, space, number and other magnitudes. Philosophical Transactions of the Royal
So-ciety of London. Series B, Biological Sciences, 364(1525), 1831–1840. doi:10.1098/
rstb.2009.0028
Buhusi, C. V, & Meck, W. H. (2005). What makes us tick? Functional and neu-ral mechanisms of interval timing. Nature Reviews Neuroscience, 6(10), 755–65. doi:10.1038/nrn1764
Buneo, C. A. (2011). Analyzing neural responses with vector fields. Journal of
Neu-roscience Methods, 197(1), 109–117. doi:10.1016/J.JNEUMETH.2011.02.008
Buneo, C. A., & Andersen, R. A. (2012). Integration of target and hand position sig-nals in the posterior parietal cortex: effects of workspace and hand vision. Journal
of Neurophysiology, 108(1), 187–199. doi:10.1152/jn.00137.2011
Buonomano, D. V. (2000). Decoding temporal information: A model based on short-term synaptic plasticity. Journal of Neuroscience, 20(3), 1129–41. doi:10.1523/JN-EUROSCI.20-03-01129.2000
Buonomano, D. V. (2007). The biology of time across different scales. Nature
Chemi-cal Biology, 3(10), 594–597. doi:10.1038/nchembio1007-594
Buonomano, D. V. (2017). Your brain is a time machine: The neuroscience and phy-sics of time. New York, NY: W. W. Norton & Company.
Buonomano, D. V. (2014). Neural dynamics based timing in the subsecond to se-conds range. In H. Merchant & V. de Lafuente (Eds.), Neurobiology of Interval Timing. Advances in Experimental Medicine and Biology, vol 829 (pp. 49–71). New York, NY: Springer. doi:10.1007/978-1-4939-1782-2_6
Buszáki, G., & Llinás, R. (2017). Space and time in the brain. Science, 358(6362), 482–485. doi:10.1126/science.aan8869
Buzsáki, G. (2019). The brain from inside out. New York, NY: Oxford University Press.
Cai, Z. G., & Connell, L. (2016). On magnitudes in memory: An internal clock account of space-time interaction. Acta Psychologica, 168, 1–11. doi:10.1016/j.ac-tpsy.2016.04.003
Cai, Z. G., & Wang, R. (2014). Numerical magnitude affects temporal memories but not time encoding. PLoS ONE, 9(1). doi:10.1371/journal.pone.0083159
Cai, Z. G., Wang, R., Shen, M., & Speekenbrink, M. (2018). Cross-dimensional magnitude interactions arise from memory interference. Cognitive Psychology,
106, 21–42. doi:10.1016/J.COGPSYCH.2018.08.001
Campbell, S. L., Hutson, R. B., Marti, G. E., Goban, A., Darkwah Oppong, N., McNally, R. L., … Ye, J. (2017). A Fermi-degenerate three-dimensional optical lattice clock. Science, 358(6359), 90–94. doi:10.1126/science.aam5538
Carrozzo, M., & Lacquaniti, F. (2013). Effects of speeding up or slowing down animate or inanimate motions on timing. Experimental Brain Research, 224(4), 581–590. doi:10.1007/s00221-012-3338-7
Carrozzo, M., Moscatelli, A., & Lacquaniti, F. (2010). Tempo rubato: Animacy speeds up time in the brain, PLoS ONE, 5(12). doi:10.1371/journal.pone.0015638 Casasanto, D., & Boroditsky, L. (2008). Time in the mind: Using space to think
about time. Cognition, 106(2), 579–593. doi:10.1016/j.cognition.2007.03.004 Chang, A. Y.-C., Tzeng, O. J. L., Hung, D. L., & Wu, D. H. (2011). Big time is
not always long: numerical magnitude automatically affects time reproduction.
Psychological Science, 22(12), 1567–1573. doi:10.1177/0956797611418837
Charles, E. P. (2005). The correction for attenuation due to measurement error: Clarifying concepts and creating confidence sets. Psychological Methods, 10(2), 206–226. doi:10.1037/1082-989X.10.2.206
Chen, Y. G., Chen, X., Kuang, C. W., & Huang, X. T. (2015). Neural oscillatory correlates of duration maintenance in working memory. Neuroscience, 290, 389– 397. doi:10.1016/j.neuroscience.2015.01.036
Church, R. (2003). A concise introduction to scalar timing theory. In W.H. Meck (Ed.), Functional and neural mechanisms of interval timing (pp. 3–22). Boca Raton, FL, US: CRC Press. doi:10.1201/9780203009574.sec1
Church, R. M., Meck, W. H., & Gibbon, J. (1994). Application of scalar timing theory to individual trials. Journal of Experimental Psychology: Animal Behavior
Processes, 20(2), 135–155. doi:10.1037/0097-7403.20.2.135
Citri, A., & Malenka, R. C. (2008). Synaptic plasticity: Multiple forms, func-tions, and mechanisms. Neuropsychopharmacology, 33(1), 18–41. doi:10.1038/ sj.npp.1301559
Conson, M., Cinque, F., Barbarulo, A. M., & Trojano, L. (2008). A common pro-cessing system for duration, order and spatial information: Evidence from a time estimation task. Experimental Brain Research, 187(2), 267–274. doi:10.1007/ s00221-008-1300-5
Coull, J. T., Charras, P., Donadieu, M., Droit-Volet, S., & Vidal, F. (2015). SMA selectively codes the active accumulation of temporal, not spatial, magnitude.
Journal of Cognitive Neuroscience, 27(11), 2281–2298. doi:10.1162/jocn_a_00854
Coull, J. T., Cheng, R.-K., & Meck, W. H. (2011). Neuroanatomical and neuroche-mical substrates of timing. Neuropsychopharmacology, 36(1), 3–25. doi:10.1038/ npp.2010.113
Coull, J. T., & Droit-Volet, S. (2018). Explicit understanding of duration de-velops implicitly through action. Trends in Cognitive Sciences, 22(10), 923–937. doi:10.1016/J.TICS.2018.07.011
Coull, J. T., Johnson, K. A., & Droit-Volet, S. (2018). A mental timeline for dura-tion from the age of 5 years old. Frontiers in Psychology, 9, 1155. doi:10.3389/ fpsyg.2018.01155
Coull, J. T., Vidal, F., & Burle, B. (2016). When to act, or not to act: That’s the SMA’s question. Current Opinion in Behavioral Sciences. doi:10.1016/j.co-beha.2016.01.003
Coull, J. T., Vidal, F., Nazarian, B., & Macar, F. (2004). Functional anatomy of the attentional modulation of time estimation. Science, 303(5663), 1506–1508. doi:10.1126/science.1091573
Crystal, J. D. (2007). The psychology of time: A tribute to the contributions of Rusell M. Church [Special Issue]. Behavioural Processes, 74(2).
Damsma, A., Van der Mijn, R., & Van Rijn, H. (2018). Neural markers of memory consolidation do not predict temporal estimates of encoded items.
Neuropsycholo-gia, 117, 36–45. doi:10.1016/J.NEUROPSYCHOLOGIA.2018.04.039
Damsma, A., Schlichting, N., Eike, R., & Van Rijn, H. (in preparation). Decoding the influence of temporal context on time perception. Program No. 169.12. 2018 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2018. Online.
Darlow, H. M., Dylman, A. S., Gheorghiu, A. I., & Matthews, W. J. (2013). Do changes in the pace of events affect one-off judgments of duration? PLoS ONE,
8(3), e59847. doi:10.1371/journal.pone.0059847
Dehaene, S., Dehaene-Lambertz, G., & Cohen, L. (1998). Abstract representations of numbers in the animal and human brain. Trends in Neurosciences, 21(8), 355– 361. doi:10.1016/S0166-2236(98)01263-6
Dennett, D. C., & Kinsbourne, M. (1992). Time and the observer: The where and when of consciousness in the brain. Behavioral and Brain Sciences, 15(02), 183– 201. doi:10.1017/S0140525X00068229
Dormal, V., Dormal, G., Joassin, F., & Pesenti, M. (2012). A common right fron-to-parietal network for numerosity and duration processing: An fMRI study.
Human Brain Mapping, 33(6), 1490–1501. doi:10.1002/hbm.21300
three-dimensional Stroop-like task: Towards a gradient of processing automati-city? Psychological Research, 77(2), 116–127. doi:10.1007/s00426-012-0414-3 Dormal, V., Seron, X., & Pesenti, M. (2006). Numerosity-duration
interferen-ce: A Stroop experiment. Acta Psychologica, 121, 109–124. doi:10.1016/j.act-psy.2005.06.003
Droit-Volet, S. (2010). Stop using time reproduction tasks in a comparative per-spective without further analyses of the role of the motor response: The ex-ample of children. European Journal of Cognitive Psychology, 22(1), 130–148. doi:10.1080/09541440902738900
Droit-Volet, Sylvie, Clément, A., & Fayol, M. (2008). Time, number and length: Similarities and differences in discrimination in adults and chil-dren. The Quarterly Journal of Experimental Psychology, 61(12), 1827–1846. doi:10.1080/17470210701743643
Durstewitz, D. (2004). Neural representation of interval time. Neuroreport, 15(5), 745–9. doi:10.1097/00001756-200404090-00001
Dyjas, O., Bausenhart, K. M., & Ulrich, R. (2012). Trial-by-trial updating of an internal reference in discrimination tasks: Evidence from effects of stimu-lus order and trial sequence. Attention, Perception, & Psychophysics, 1819–1841. doi:10.3758/s13414-012-0362-4
Dyjas, O., Bausenhart, K. M., & Ulrich, R. (2014). Effects of stimulus order on duration discrimination sensitivity are under attentional control. Journal of
Expe-rimental Psychology: Human Perception and Performance, 40, 292–307. doi:10.1037/
a0033611
Eagleman, D. M. (2008). Human time perception and its illusions. Current Opinion
in Neurobiology, 18(2), 131–136. doi:10.1016/j.conb.2008.06.002
Eagleman, D. M., & Pariyadath, V. (2009). Is subjective duration a signature of co-ding efficiency? Philosophical Transactions of the Royal Society B: Biological Sciences,
364(1525), 1841–1851. doi:10.1098/rstb.2009.0026
Ebert, J. P., & Wegner, D. M. (2010). Time warp: Authorship shapes the percei-ved timing of actions and events. Consciousness and Cognition, 19(1), 481–489. doi:10.1016/j.concog.2009.10.002
Efron, B., & Tibshirani, R. (1986). Bootstrap methods for standard errors, confi-dence intervals, and other measures of statistical accuracy. Statistical Science, 1(1), 54–77.
Eichenbaum, H. (2014). Time cells in the hippocampus: A new dimension for mapping memories. Nature Reviews Neuroscience, 15(11), 732–744. doi:10.1038/ nrn3827
Engel, A. K., & Fries, P. (2010). Beta-band oscillations-signalling the status quo?
Current Opinion in Neurobiology, 20(2), 156–165. doi:10.1016/j.conb.2010.02.015
Fabbri, M., Cancellieri, J., & Natale, V. (2012). The A Theory Of Magnitude (ATOM) model in temporal perception and reproduction tasks. Acta
Psychologi-ca, 139(1), 111–123. doi:10.1016/J.ACTPSY.2011.09.006
Fabbri, M., Cellini, N., Martoni, M., Tonetti, L., & Natale, V. (2013). The me-chanisms of space-time association: Comparing motor and perceptual
contri-butions in time reproduction. Cognitive Science, 37(7), 1228–1250. doi:10.1111/ cogs.12038
Fayolle, S. L., & Droit-Volet, S. (2014). Time perception and dynamics of facial ex-pressions of emotions. PLoS ONE, 9(5). doi:10.1371/journal.pone.0097944 Friston, K. J., Price, C. J., Fletcher, P., Moore, C., Frackowiak, R. S., & Dolan,
R. J. (1996). The trouble with cognitive subtraction. NeuroImage, 4(2), 97–104. doi:10.1006/nimg.1996.0033
Fründ, I., Haenel, N. V., & Wichmann, F. A. (2011). Inference for psychometric functions in the presence of nonstationary behavior. Journal of Vision, 11(6), 1–19. doi:10.1167/11.6.16.Introduction
Fuhrman, O., & Boroditsky, L. (2010). Cross-cultural differences in mental repre-sentations of time: Evidence from an implicit nonlinguistic task. Cognitive
Scien-ce, 34(8), 1430–1451. doi:10.1111/j.1551-6709.2010.01105.x
Garsoffky, B., Huff, M., & Schwan, S. (2017). Mind the gap: Temporal discontinu-ities in observed activity streams influence perceived duration of actions.
Psycho-nomic Bulletin & Review. doi:10.3758/s13423-017-1239-2
Gibbon, J., Church, R. M., & Meck, W. H. (1984). Scalar timing in memory. Annals
of the New York Academy of Sciences, 423(1), 52–77. doi:10.1111/j.1749-6632.1984.
tb23417.x
Gibbon, J., Malapani, C., Dale, C. L., & Gallistel, C. R. (1997). Toward a neu-robiology of temporal cognition: Advances and challenges. Current Opinion in
Neurobiology, 7(2), 170–184. doi:10.1016/S0959-4388(97)80005-0
Gibson, J. J. (1975). Events are perceivable but time is not. In J.T. Fraser & N. La-wrence (Eds.), The Study of Time II (pp. 295–301). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-50121-0_22
Goel, A., & Buonomano, D. V. (2014). Timing as an intrinsic property of neural networks: Evidence from in vivo and in vitro experiments. Philosophical
Transac-tions of the Royal Society B: Biological Sciences, 369(1637), 20120460–20120460.
doi:10.1098/rstb.2012.0460
Gorea, A., & Hau, J. (2013). Time in perspective. Psychological Science, 24(8), 1477– 86. doi:10.1177/0956797612473486
Grabot, L., & Van Wassenhove, V. (2017). Time order as psychological bias.
Psycho-logical Science, 28(5), 670–678. doi:10.1177/0956797616689369
Green, S. B., Yang, Y., Alt, M., Brinkley, S., Gray, S., Hogan, T., & Cowan, N. (2016). Use of internal consistency coefficients for estimating reliability of experi-mental task scores. Psychonomic Bulletin & Review, 23(3), 750–763. doi:10.3758/ s13423-015-0968-3
Grondin, S. (1993). Duration discrimination of empty and filled intervals mar-ked by auditory and visual signals. Perception & Psychophysics, 54(3), 383–394. doi:10.3758/BF03205274
Grondin, S. (2010). Timing and time perception: A review of recent behavioral and neuroscience findings and theoretical directions. Attention, Perception, &
Psycho-physics, 72(3), 561–582. doi:10.3758/APP.72.3.561
in Experimental Medicine and Biology, 829, 17–32.
doi:10.1007/978-1-4939-1782-2_2
Gu, B., Van Rijn, H., & Meck, W. H. (2015). Oscillatory multiplexing of neural population codes for interval timing and working memory. Neuroscience and
Bio-behavioral Reviews, 48, 160–185. doi:10.1016/j.neubiorev.2014.10.008
Haggard, P., Clark, S., & Kalogeras, J. (2002). Voluntary action and conscious awa-reness. Nature Neuroscience, 5(4), 382–385. doi:10.1038/nn827
Hallez, Q., Damsma, A., Rhodes, D., Van Rijn, H., & Droit-Volet, S. (2019). The dynamic effect of context on interval timing in children and adults. Acta
Psycho-logica, 192, 87–93. doi:10.1016/J.ACTPSY.2018.10.004
Hancock, & Block. (2012). The Psychology of time: A view backward and forward.
The American Journal of Psychology, 125(3), 267. doi:10.5406/amerjpsyc.125.3.0267
Hanson, B., Klink, K., Matsuura, K., Robeson, S. M., & Willmott, C. J. (1992). Vec-tor correlation: Review, exposition, and geographic application. Annals of the
As-sociation of American Geographers, 82(1), 103–116. doi:10.1111/j.1467-8306.1992.
tb01900.x
Harvey, B. M., Dumoulin, S. O., Fracasso, A., & Paul, J. M. (2018). A network of topographic maps for visual event timing in human association cortex. Program No. 719.01. 2018 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2018. Online.
Hass, J., & Durstewitz, D. (2014). Neurocomputational models of time perception. In H. Merchant & V. de Lafuente (Eds.), Neurobiology of Interval Timing. Ad-vances in Experimental Medicine and Biology, vol 829 (pp. 49–71). New York, NY: Springer. doi:10.1007/978-1-4939-1782-2_4
Hass, J., & Durstewitz, D. (2016). Time at the center, or time at the side? Asses-sing current models of time perception. Current Opinion in Behavioral Sciences, 8, 238–244. doi:10.1016/J.COBEHA.2016.02.030
Hayashi, M. J., Kanai, R., Tanabe, H. C., Yoshida, Y., Carlson, S., Walsh, V., & Sadato, N. (2013). Interaction of numerosity and time in prefrontal and pa-rietal cortex. Journal of Neuroscience, 33(3), 883–93. doi:10.1523/JNEUROS-CI.6257-11.2013
Hayashi, M. J., Valli, A., & Carlson, S. (2013). Numerical quantity affects time esti-mation in the suprasecond range. Neuroscience Letters, 543, 7–11. doi:10.1016/J. NEULET.2013.02.054
Hayashi, M. J., van der Zwaag, W., Bueti, D., & Kanai, R. (2018). Representa-tions of time in human frontoparietal cortex. CommunicaRepresenta-tions Biology, 1(1), 233. doi:10.1038/s42003-018-0243-z
Hedge, C., Powell, G., & Sumner, P. (2017). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research
Methods, 1–21. doi:10.3758/s13428-017-0935-1
Hothorn, T., Bretz, F., Westfall, P., Heiberger, R. M., Schuetzenmeister, A., Schei-be, S., & Hothorn, M. T. (2017). Package “multcomp.” See Https://Cran. r-Pro-ject. Org/Web/Packages/Multcomp/Index. Html.
with item and temporal order maintenance in working memory. Journal of
Neu-roscience, 31(30), 10803–10810. doi:10.1523/JNEUROSCI.0828-11.2011
Ishihara, M., Keller, P. E., Rossetti, Y., & Prinz, W. (2008). Horizontal spatial re-presentations of time: Evidence for the STEARC effect. Cortex, 44(4), 454–461. doi:10.1016/j.cortex.2007.08.010
Javadi, A. H., & Aichelburg, C. (2012). When time and numerosity interfere: The longer the more, and the more the longer. PLoS ONE, 7(7), 1–10. doi:10.1371/ journal.pone.0041496
Jazayeri, M., & Shadlen, M. N. (2010). Temporal context calibrates interval timing.
Nature Neuroscience, 13(8), 1020–1026. doi:10.1038/nn.2590
Jensen, A. R. (1998). The g factor: The science of mental ability. Politics and the Life Sciences (Vol. 17). Westport, Connecticut: Praeger.
Kanai, R., & Rees, G. (2011). The structural basis of inter-individual differences in human behaviour and cognition. Nature Reviews Neuroscience, 12(4), 231–242. doi:10.1038/nrn3000
Karmarkar, U. R., & Buonomano, D. V. (2007). Timing in the absence of clocks: Encoding time in neural network states. Neuron, 53(3), 427–438. doi:10.1016/J. NEURON.2007.01.006
Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: The in-hibition-timing hypothesis. Brain Research Reviews, 53(1), 63–88. doi:10.1016/j. brainresrev.2006.06.003
Kononowicz, T. W., & Penney, T. B. (2016). The contingent negative variation (CNV): Timing isn’t everything. Current Opinion in Behavioral Sciences, 8, 231– 237. doi:10.1016/j.cobeha.2016.02.022
Kononowicz, T. W., Sander, T., & Van Rijn, H. (2015). Neuroelectromagnetic si-gnatures of the reproduction of supra-second durations. Neuropsychologia, 75, 201–213. doi:10.1016/j.neuropsychologia.2015.06.001
Kononowicz, T. W., & Van Rijn, H. (2011). Slow potentials in time estimation: The role of temporal accumulation and habituation. Frontiers in Integrative
Neuros-cience, 5(48), 1–10. doi:10.3389/fnint.2011.00048
Kononowicz, T. W., & Van Rijn, H. (2014a). Decoupling interval timing and clim-bing neural activity: A dissociation between CNV and N1P2 amplitudes. Journal
of Neuroscience, 34(8), 2931–2939. doi:10.1523/JNEUROSCI.2523-13.2014
Kononowicz, T. W., & Van Rijn, H. (2014b). Tonic and phasic dopamine fluctua-tions as reflected in beta-power predict interval timing behavior. Procedia - Social
and Behavioral Sciences, 126(2005), 47. doi:10.1016/j.sbspro.2014.02.313
Kononowicz, T. W., & Van Rijn, H. (2015). Single trial beta oscillations index time estimation. Neuropsychologia, 75, 381–389. doi:10.1016/j.neuropsycholo-gia.2015.06.014
Kononowicz, T. W., & Van Wassenhove, V. (2016). In search of oscillatory traces of the internal clock. Frontiers in Psychology, 7(244). doi:10.3389/fpsyg.2016.00224 Kulashekhar, S., Pekkola, J., Palva, J. M., & Palva, S. (2016). The role of cortical
beta oscillations in time estimation. Human Brain Mapping, 37(9), 3262–3281. doi:10.1002/hbm.23239
Lacquaniti, F., Carrozzo, M., Andrea d’Avella, Scaleia, B. La, Moscatelli, A., & Zago, M. (2014). How long did it last? You would better ask a human. Frontiers
in Neurorobotics, 8(2), 1–12. doi:10.3389/fnbot.2014.00002
Lambrechts, A., Walsh, V., & Van Wassenhove, V. (2013). Evidence accumulation in the magnitude system. PLoS ONE, 8(12). doi:10.1371/journal.pone.0082122 Leibovich, T., Katzin, N., Harel, M., & Henik, A. (2016). From “sense of number”
to “sense of magnitude” – The role of continuous magnitudes in numerical cog-nition. Behavioral and Brain Sciences, 8, 1–62. doi:10.1017/S0140525X16000960 Lejeune, H., & Wearden, J. H. (2009). Vierordt’s the experimental study of the time
sense (1868) and its legacy. European Journal of Cognitive Psychology, 21(6), 941– 960. doi:10.1080/09541440802453006
Loeffler, J., Cañal-Bruland, R., Schroeger, A., Tolentino-Castro, J. W., & Raab, M. (2018). Interrelations between temporal and spatial cognition: The role of modality-specific processing. Frontiers in Psychology, 9, 2609. doi:10.3389/ fpsyg.2018.02609
Los, S. A. (2010). Foreperiod and sequential effects: Theory and data. In A. C. Nobre & J. T. Coull (Eds.), Attention and Time (pp. 289–302). Oxford, UK: Oxford University Press.
Maaß, S. C., Riemer, M., Wolbers, T., & Van Rijn, H. (2019). Timing deficiencies in amnestic mild cognitive impairment: Disentangling clock and memory pro-cesses. Behavioural Brain Research, 373. doi:10.1016/j.bbr.2019.112110
Macar, F., & Vidal, F. (2004). Event-related potentials as indices of time proces-sing: A review. Journal of Psychophysiology, 18(2–3), 89–104. doi:10.1027/0269-8803.18.23.89
Macar, F., & Vidal, F. (2009). Timing processes: An outline of behavioural and neu-ral indices not systematically considered in timing models. Canadian Journal of
Experimental Psychology, 63(3), 227–239. doi:10.1037/a0014457
Macar, F., Vidal, F., & Casini, L. (1999). The supplementary motor area in motor and sensory timing: Evidence from slow brain potential changes. Experimental Brain
Research, 125(3), 271–280. doi:10.1007/s002210050683
MacDonald, C. J., Lepage, K. Q., Eden, U. T., & Eichenbaum, H. (2011). Hip-pocampal “time cells” bridge the gap in memory for discontiguous events.
Neu-ron, 71(4), 737–49. doi:10.1016/j.neuron.2011.07.012
Magnani, B., & Musetti, A. (2017). Innate and cultural spatial time: A develop-mental perspective. Frontiers in Human Neuroscience, 11, 215. doi:10.3389/ fnhum.2017.00215
Mandery, C., Terlemez, Ö., Do, M., Vahrenkamp, N., & Asfour, T. (2015). The KIT whole-body human motion database. Proceedings of the 17th Internatio-nal Conference on Advanced Robotics, ICAR 2015, 611909(611909), 329–336. doi:10.1109/ICAR.2015.7251476
Marr, D. (1982). Vision: A computational investigation into the human representa-tion and processing of visual informarepresenta-tion. San Francisco, CA: W.H. Freeman. Martin, B., Wiener, M., & Van Wassenhove, V. (2017). A Bayesian perspective on
s41598-017-00680-0
Martínez-Loredo, V., Fernández-Hermida, J. R., Carballo, J. L., & Fernández-Ar-tamendi, S. (2017). Long-term reliability and stability of behavioral measures among adolescents: The Delay Discounting and Stroop tasks. Journal of
Adole-scence, 58, 33–39. doi:10.1016/j.adolescence.2017.05.003
Matell, M. S. (2014). Searching for the holy grail: Temporally informative firing patterns in the rat. In H. Merchant & V. Lafuente (Eds.), Neurobiology of In-terval Timing. Advances in Experimental Medicine and Biology, vol. 829 (pp. 209–34). New York, NY: Springer. doi:10.1007/978-1-4939-1782-2_12
Matell, M. S., & Meck, W. H. (2000). Neuropsychological mechanisms of interval timing behavior. BioEssays, 22(1), 94–103. doi:10.1002/(SICI)1521-1878(200001 )22:1<94::AID-BIES14>3.0.CO;2-E
Matell, M. S., & Meck, W. H. (2004). Cortico-striatal circuits and interval timing: Coincidence detection of oscillatory processes. Cognitive Brain Research, 21(2), 139–170. doi:10.1016/j.cogbrainres.2004.06.012
Matell, M. S., Shea-Brown, E., Gooch, C., Wilson, G., & Rinzel, J. (2011). A he-terogeneous population code for elapsed time in rat medial agranular cortex.
Behavioral Neuroscience, 125(1), 54–73. doi:10.1037/a0021954
Mathôt, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, gra-phical experiment builder for the social sciences. Behavior Research Methods,
44(2), 314–24. doi:10.3758/s13428-011-0168-7
Matthews, W. J. (2011). How do changes in speed affect the perception of durati-on? Journal of Experimental Psychology: Human Perception and Performance, 37(5), 1617–1627. doi:10.1037/a0022193
Matthews, W. J., & Meck, W. H. (2014). Time perception: The bad news and the good. Wiley Interdisciplinary Reviews: Cognitive Science, 5(4), 429–446. doi:10.1002/wcs.1298
Matthews, W. J., & Meck, W. H. (2016). Temporal cognition: Connecting sub-jective time to perception, attention, and memory. Psychological Bulletin, 142(8), 865–907. doi:10.1037/bul0000045
Mau, W., Sullivan, D. W., Kinsky, N. R., Hasselmo, M. E., Howard, M. W., & Eichenbaum, H. (2018). The same hippocampal CA1 population simultaneously codes temporal information over multiple timescales. Current Biology, 28(10), 1499-1508.e4. doi:10.1016/J.CUB.2018.03.051
McTaggart, J. E. (1908). The unreality of time. Mind, 17(68), 457–474. doi:10.2307/2248314
Meck, W. H. (1983). Selective adjustment of the speed of internal clock and memo-ry processes. Journal of Experimental Psychology: Animal Behavior Processes, 9(2), 171–201. doi:10.1037/0097-7403.9.2.171
Meeter, M., Jehee, J., & Murre, J. (2007). Neural models that convince: Model hie-rarchies and other strategies to bridge the gap between behavior and the brain.
Philosophical Psychology, 20(6), 749–772. doi:10.1080/09515080701694128
Mello, G. B. M., Soares, S., & Paton, J. J. (2015). A scalable population code for time in the striatum. Current Biology, 25(9), 1113–1122. doi:10.1016/J.
CUB.2015.02.036
Mento, G. (2013). The passive CNV: Carving out the contribution of task-related processes to expectancy. Frontiers in Human Neuroscience, 7, 827. doi:10.3389/ fnhum.2013.00827
Michon, J. A. (1990). Implicit and explicit representations of time. In R.A. Block (Ed.), Cognitive models of psychological time (pp. 37–58). Hillsdale, NJ: La-wrence Erlbaum Associates, Inc.
Miletić, S., & Van Maanen, L. (2019). Caution in decision-making under time pres-sure is mediated by timing ability. Cognitive Psychology, 110, 16–29. doi:10.1016/J. COGPSYCH.2019.01.002
Miller, J., & Ulrich, R. (2013). Mental chronometry and individual differences: Mo-deling reliabilities and correlations of reaction time means and effect sizes.
Psy-chonomic Bulletin & Review, 20(5), 819–858. doi:10.3758/s13423-013-0404-5
Mioni, G. (2018). Methodological issues in the study of prospective timing. In A. Vatakis, F. Balcı, M. Di Luca, & Á. Correa (Eds.), Timing and Time Percepti-on: Procedures, Measures, and Applications (pp. 79–97). Leiden, The Nether-lands: Brill. doi:10.1163/9789004280205_005
Mita, A., Mushiake, H., Shima, K., Matsuzaka, Y., & Tanji, J. (2009). Interval time coding by neurons in the presupplementary and supplementary motor areas.
Na-ture Neuroscience, 12(4), 502–507. doi:10.1038/nn.2272
Morey, R. D., Rouder, J. N., & Jamil, T. (2014). BayesFactor: Computation of Bayes Factors for common designs. R Package Version, 0.9(8).
Ng, K. K., & Penney, T. B. (2014). Probing interval timing with scalp-recorded elec-troencephalography (EEG). In Neurobiology of Interval Timing (pp. 187–207). Springer New York. doi:10.1007/978-1-4939-1782-2_11
Nobre, Anna C., & Van Ede, F. (2018). Anticipated moments: Temporal structure in attention. Nature Reviews Neuroscience, 19(1), 34–48. doi:10.1038/nrn.2017.141 Núñez, R., & Cooperrider, K. (2013). The tangle of space and time in human
cogni-tion. Trends in Cognitive Sciences, 17(5), 220–229. doi:10.1016/j.tics.2013.03.008 Oliver, J. (2019, July 5). A basic risotto recipe. Retrieved from
https://www.jamieoli-ver.com/recipes/rice-recipes/a-basic-risotto-recipe/
Oliveri, M., Vicario, C. M., Salerno, S., Koch, G., Turriziani, P., Mangano, R., … Caltagirone, C. (2008). Perceiving numbers alters time perception. Neuroscience
Letters, 438(3), 308–311. doi:10.1016/j.neulet.2008.04.051
Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J. (2011). FieldTrip : Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. doi:10.1155/2011/156869
Oprisan, S. A., & Buhusi, C. V. (2011). Modeling pharmacological clock and me-mory patterns of interval timing in a striatal beat-frequency model with reali-stic, noisy neurons. Frontiers in Integrative Neuroscience, 5, 52. doi:10.3389/fn-int.2011.00052
Orgs, G., Bestmann, S., Schuur, F., & Haggard, P. (2011). From body form to biolo-gical motion: The apparent velocity of human movement biases subjective time.
Paap, K. R., & Sawi, O. (2016). The role of test-retest reliability in measuring in-dividual and group differences in executive functioning. Journal of Neuroscience
Methods, 274, 81–93. doi:10.1016/J.JNEUMETH.2016.10.002
Petter, E. A., Gershman, S. J., & Meck, W. H. (2018). Integrating models of interval timing and reinforcement learning. Trends in Cognitive Sciences, 22(10), 911–922. doi:10.1016/J.TICS.2018.08.004
Petzschner, F. H., Glasauer, S., & Stephan, K. E. (2015). A Bayesian perspective on magnitude estimation. Trends in Cognitive Sciences, 19(5), 285–293. doi:10.1016/j. tics.2015.03.002
Pfeuty, M., Ragot, R., & Pouthas, V. (2005). Relationship between CNV and timing of an upcoming event. Neuroscience Letters, 382(1–2), 106–111. doi:10.1016/j.neu-let.2005.02.067
Protopapa, F., Hayashi, M. J., Kulashekhar, S., van der Zwaag, W., Battistella, G., Murray, M. M., … Bueti, D. (2019). Chronotopic maps in human supplementary motor area. PLoS Biology, 17(3), e3000026. doi:10.1371/journal.pbio.3000026 R Core Team (2016). R: A language and environment for statistical computing.
Vi-enna, Austria: R Foundation for Statistical Computing. Retrieved from https:// www.r-project.org/
R Development Core Team (2008). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. doi:ISBN 3-900051-07-0
Rammsayer, T. H., & Verner, M. (2014). The effect of nontemporal stimulus size on perceived duration as assessed by the method of reproduction. Journal of Vision,
14(5), 1–10. doi:10.1167/14.5.17.doi
Rhodes, D. (2018). On the distinction between perceived duration and event timing: Towards a unified model of time perception. Timing & Time Perception, 6(1), 90–123. doi:10.1163/22134468-20181132
Riemer, M., Diersch, N., Bublatzky, F., & Wolbers, T. (2016). Space, time, and numbers in the right posterior parietal cortex: Differences between response code associations and congruency effects. NeuroImage, 129, 72–79. doi:10.1016/J. NEUROIMAGE.2016.01.030
Riemer, M., Trojan, J., Kleinböhl, D., & Hölzl, R. (2012). A “view from nowhen” on time perception experiments. Journal of Experimental Psychology: Human
Percep-tion and Performance, 38(5), 1118–1124. doi:10.1037/a0027073
Roberts, B. M., Hsieh, L., & Ranganath, C. (2013). Oscillatory activity during maintenance of spatial and temporal information in working memory.
Neuropsy-chologia, 51(2), 349–357. doi:10.1016/j.neuropsychologia.2012.10.009
Rohenkohl, G., & Nobre, A. C. (2011). Alpha oscillations related to anticipatory attention follow temporal expectations. Journal of Neuroscience, 31(40), 14076– 14084. doi:10.1523/JNEUROSCI.3387-11.2011
Roseboom, W., Fountas, Z., Nikiforou, K., Bhowmik, D., Shanahan, M., & Seth, A. K. (2019). Activity in perceptual classification networks as a basis for hu-man subjective time perception. Nature Communications, 10(1), 267. doi:10.1038/ s41467-018-08194-7
Rovelli, C. (2017). Reality is not what it seems: The journey to quantum gravity. London, UK: Penguin.
Rovelli, C. (2018). The order of time. London, UK: Penguin.
Saigusa, T., Tero, A., Nakagaki, T., & Kuramoto, Y. (2008). Amoebae anticipate periodic events. Physical Review Letters, 100(1), 018101. doi:10.1103/PhysRe-vLett.100.018101
Salet, J. M., Kruijne, W., Los, S. A., Van Rijn, H., & Meeter, M. (in preparation). fMTP: A unifying computational framework of temporal preparation across time scales.
Samaha, J., Bauer, P., Cimaroli, S., & Postle, B. R. (2015). Top-down control of the phase of alpha-band oscillations as a mechanism for temporal prediction.
Proceedings of the National Academy of Sciences, 112(27), 8439–8444. doi:10.1073/
pnas.1503686112
Sasaki, K., Yamamoto, K., & Miura, K. (2013). The difference in speed sequence influences perceived duration. Perception, 42(2), 198–207. doi:10.1068/p7241 Schlichting, N., de Jong, R., & Van Rijn, H. (2018). Performance-informed EEG
analysis reveals mixed evidence for EEG signatures unique to the processing of time. Psychological Research, 1–18. doi:10.1007/s00426-018-1039-y
Shankar, K. H., & Howard, M. W. (2010). Timing using temporal context. Brain
Research, 1365, 3–17. doi:10.1016/J.BRAINRES.2010.07.045
Siegrist, M. (1997). Test-retest reliability of different versions of the Stroop test.
Journal of Psychology, 131(3), 299–306. doi:10.1080/00223989709603516
Soares, S., Atallah, B. V, & Paton, J. J. (2016). Midbrain dopamine neurons control judgment of time. Science, 354(6317), 1273–1277. doi:10.1126/science.aah5234 Sohn, H., Narain, D., Meirhaeghe, N., & Jazayeri, M. (2018). Bayesian computation
through cortical latent dynamics. BioRxiv, 465419. doi:10.1101/465419
Staddon, J. E. R. (2005). Interval timing: Memory, not a clock. Trends in Cognitive
Sciences, 9(7), 312–314. doi:10.1016/J.TICS.2005.05.013
Staddon, J. E. R., & Higa, J. J. (1999). Time and memory: Towards a pacemaker-free theory of interval timing. Journal of the Experimental Analysis of Behavior, 71(2), 215–251. doi:10.1901/jeab.1999.71-215
Strauss, G. P., Allen, D. N., Jorgensen, M. L., & Cramer, S. L. (2005). Test-re-test reliability of standard and emotional Stroop tasks: An investigati-on of color-word and picture-word versiinvestigati-ons. Assessment, 12(3), 330–337. doi:10.1177/1073191105276375
Taatgen, N., & Van Rijn, H. (2011). Traces of times past: Representations of tem-poral intervals in memory. Memory & Cognition, 39(8), 1546–1560. doi:10.3758/ s13421-011-0113-0
Terlemez, Ö., Ulbrich, S., Mandery, C., Do, M., Vahrenkamp, N., & Asfour, T. (2014). Master Motor Map (MMM) - Framework and toolkit for capturing, re-presenting, and reproducing human motion on humanoid robots. In IEEE-RAS International Conference on Humanoid Robots (pp. 894–901). Madrid, Spain. doi:10.1109/HUMANOIDS.2014.7041470
subjective time. Consciousness and Cognition, 71, 114–122. doi:10.1016/J.CON-COG.2019.04.004
Tiganj, Z., Cromer, J. A., Roy, J. E., Miller, E. K., & Howard, M. W. (2018). Com-pressed timeline of recent experience in monkey lateral prefrontal cortex. Journal
of Cognitive Neuroscience, 30(7), 935–950. doi:10.1162/jocn_a_01273
Tsao, A., Sugar, J., Lu, L., Wang, C., Knierim, J. J., Moser, M.-B., & Moser, E. I. (2018). Integrating time from experience in the lateral entorhinal cortex. Nature,
561(7721), 57–62. doi:10.1038/s41586-018-0459-6
Vallesi, A., Binns, M. A., & Shallice, T. (2008). An effect of spatial–temporal asso-ciation of response codes: Understanding the cognitive representations of time.
Cognition, 107(2), 501–527. doi:10.1016/J.COGNITION.2007.10.011
Van den Berg, B., Krebs, R. M., Lorist, M. M., & Woldorff, M. G. (2014). Utilizati-on of reward-prospect enhances preparatory attentiUtilizati-on and reduces stimulus cUtilizati-on- con-flict. Cognitive, Affective, & Behavioral Neuroscience, 14(2), 561–577. doi:10.3758/ s13415-014-0281-z
Van Maanen, L., Van der Mijn, R., Van Beurden, M. H. P. H., Roijendijk, L. M. M., Kingma, B. R. M., Miletić, S., & Van Rijn, H. (2019). Core body tempera-ture speeds up temporal processing and choice behavior under deadlines.
Scien-tific Reports, 9, 10053. doi:10.1038/s41598-019-46073-3
Van Maanen, L., Van Rijn, H., & Borst, J. P. (2009). Stroop and picture—word in-terference are two sides of the same coin. Psychonomic Bulletin & Review, 16(6), 987–999. doi:10.3758/PBR.16.6.987
Van Rijn, H. (2014). It’s time to take the psychology of biological time into account: Speed of driving affects a trip’s subjective duration. Frontiers in Psychology, 5, 1028. doi:10.3389/fpsyg.2014.01028
Van Rijn, H. (2016). Accounting for memory mechanisms in interval timing: A review. Current Opinion in Behavioral Sciences, 8, 245–249. doi:10.1016/j.co-beha.2016.02.016
Van Rijn, H. (2018). Towards ecologically valid interval timing. Trends in Cognitive
Sciences, 22(10), 850–852. doi:10.1016/J.TICS.2018.07.008
Van Rijn, H., Borst, J., Taatgen, N., & Van Maanen, L. (2016). On the necessity of integrating multiple levels of abstraction in a single computational frame-work. Current Opinion in Behavioral Sciences, 11, 116–120. doi:10.1016/j.co-beha.2016.07.007
Van Rijn, H., Gu, B.-M., & Meck, W. H. (2014). Dedicated clock/timing-cir-cuit theories of time perception and timed performance. In H. Merchant & V. de Lafuente (Eds.), Neurobiology of Interval Timing. Advances in Expe-rimental Medicine and Biology, vol 829 (pp. 75–99). New York, NY: Springer. doi:10.1007/978-1-4939-1782-2_5
Van Rijn, H., Kononowicz, T. W., Meck, W. H., Ng, K. K., & Penney, T. B. (2011). Contingent negative variation and its relation to time estimation: A theoreti-cal evaluation. Frontiers in Integrative Neuroscience, 5(91), 1–5. doi:10.3389/fn-int.2011.00091
How many clocks do we have? Acta Psychologica, 129(3), 365–375. doi:10.1016/J. ACTPSY.2008.09.002
Van Wassenhove, V. (2017). Time consciousness in a computational mind/brain.
Journal of Consciousness Studies, 24(3–4), 177–202.
Vicario, C. M., Pecoraro, P., Turriziani, P., Koch, G., Caltagirone, C., & Oliveri, M. (2008). Relativistic compression and expansion of experiential time in the left and right space. PLoS ONE, 3(3), e1716. doi:10.1371/journal.pone.0001716 Wächter, M., & Asfour, T. (2015). Hierarchical segmentation of manipulation
ac-tions based on object relaac-tions and motion characteristics. Proceedings of the 17th International Conference on Advanced Robotics, ICAR 2015, 270273, 549–556. doi:10.1109/ICAR.2015.7251510
Wagenmakers, E. (2007). A practical solution to the pervasive problems of p values.
Psychonomic Bulletin & Review, 14(5), 779–804. doi:10.3758/BF03194105
Walsh, V. (2003). A Theory of Magnitude: Common cortical metrics of time, spa-ce and quantity. Trends in Cognitive Scienspa-ces, 7(11), 483–488. doi:10.1016/j. tics.2003.09.002
Walsh, V. (2015). A Theory of Magnitude: The parts that sum to number. In R. C. Kadosh & A. Dowker (Eds.), The Oxford Handbook of Numerical Cogniti-on (pp. 553–565). Oxford, U.K.: Oxford University Press. doi:10.1093/oxford-hb/9780199642342.013.64
Wang, J., Narain, D., Hosseini, E. A., & Jazayeri, M. (2018). Flexible timing by temporal scaling of cortical responses. Nature Neuroscience, 21(1), 102–110. doi:10.1038/s41593-017-0028-6
Wearden, J. H. (2001). Internal clocks and the representation of time. In C. Hoerl & T. McCormack (Eds.), Time and memory: Issues in philosophy and psychology (pp. 37–58). Oxford, UK: Clarendon Press.
Wearden, J. H. (2016). The psychology of time perception. London: Palgrave Mac-millan UK. doi:10.1057/978-1-137-40883-9
Wearden, J. H., & Lejeune, H. (2008). Scalar properties in human timing: Con-formity and violations. The Quarterly Journal of Experimental Psychology, 61(4), 569–587. doi:10.1080/17470210701282576
Wearden, J. H., Todd, N. P. M., & Jones, L. A. (2006). When do auditory/visual differences in duration judgements occur? The Quarterly Journal of Experimental
Psychology, 59(10), 1709–1724. doi:10.1080/17470210500314729
Weger, U. W., & Pratt, J. (2008). Time flies like an arrow: Space-time compatibi-lity effects suggest the use of a mental timeline. Psychonomic Bulletin & Review,
15(2), 426–430. doi:10.3758/PBR.15.2.426
Wiener, M., & Kanai, R. (2016). Frequency tuning for temporal perception and prediction. Current Opinion in Behavioral Sciences, 8. doi:10.1016/j.co-beha.2016.01.001
Wiener, M., Turkeltaub, P., & Coslett, H. B. (2010). The image of time: A vo-xel-wise meta-analysis. NeuroImage, 49(2), 1728–1740. doi:10.1016/j.neuroi-mage.2009.09.064
longer. Journal of Vision, 7(10), 2.1-5. doi:10.1167/7.10.2.Introduction
Zäch, P., & Brugger, P. (2008). Subjective time in near and far representational spa-ce. Cognitive and Behavioral Neurology: Official Journal of the Society for Behavioral
and Cognitive Neurology, 21(1), 8–13. doi:10.1097/WNN.0b013e31815f237c
Zakay, D. (1993). Time estimation methods—Do they influence prospective durati-on estimates? Perceptidurati-on, 22(1), 91–101. doi:10.1068/p220091
Zhang, Y., Chen, Y., Bressler, S. L., & Ding, M. (2008). Response preparation and inhibition: The role of the cortical sensorimotor beta rhythm. Neuroscience,
156(1), 238–246. doi:10.1016/j.neuroscience.2008.06.061
Zorzi, M., & Testolin, A. (2017). An emergentist perspective on the origin of num-ber sense. Philosophical Transactions of the Royal Society B: Biological Sciences,
