Time-to-contact (TTC) estimation is critical for daily activities, assessing when a moving object will reach a location. TTC tasks are used to study motion processing. In the TTC tasks, time structure (T) refers to the ratio of the durations of the motions in two phases: (a) one in which the stimulus is visible before it reaches occlusion point and (b) one in which it is invisible after it reaches occlusion point. The condition of T = 1.0, which indicates that the time spent moving is the same across the two segments, is called an equal time structure; otherwise, it is called an unequal time structure condition (T ≠ 1.0). The present study investigated the effect of cognitive load on TTC estimation across different time structures using a dual-task paradigm across two experiments. Experiment 1 showed that when visual velocity was available, high cognitive load enhanced participants performance in T ≠ 1.0, but had no effect on T = 1.0. Experiment 2, isolating visual velocity information, showed no significant differences in performance across different cognitive loads. These findings indicated that cognitive load could have a differential effect on TTC estimation in relation to visual velocity cues and time structure, offering insights into optimizing cognitive processes associated with time judgments.
BauresR.BalestraM.RositoM.VanRullenR. (2018). The detrimental influence of attention on time-to-contact perception. Attention, Perception, & Psychophysics, 80(6), 1591–1598. https://doi.org/10.3758/s13414-018-1523-x
4.
BauresR.DeLuciaP. R.OlsonM.OberfeldD. (2017). Asymmetric interference in concurrent time-to-contact estimation: Cousin or twin of the psychological refractory period effect?Attention, Perception, & Psychophysics, 79(2), 698–711. https://doi.org/10.3758/s13414-016-1244-y
5.
BauresR.FourteauM.ThebaultS.GazardC.PasquioL.MeneghiniG.PerrinJ.RositoM.DurandJ. B.RouxF. E. (2021). Time-to-contact perception in the brain. Journal of Neuroscience Research, 99(2), 455–466. https://doi.org/10.1002/jnr.24740
BeilockS. L.CarrT. H.MacMahonC.StarkesJ. L. (2002). When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology: Applied, 8(1), 6. https://doi.org/10.1037/1076-898X.8.1.6
8.
BenguiguiN.RipollH.BroderickM. P. (2003). Time-to-contact estimation of accelerated stimuli is based on first-order information. Journal of Experimental Psychology: Human Perception and Performance, 29(6), 1083–1101. https://doi.org/10.1037/0096-1523.29.6.1083
9.
BennettS. J.BarnesG. R. (2006). Combined smooth and saccadic ocular pursuit during the transient occlusion of a moving visual object. Experimental Brain Research, 168(3), 313–321. https://doi.org/10.1007/s00221-005-0101-3
10.
BennettS. J.BauresR.HechtH.BenguiguiN. (2010). Eye movements influence estimation of time-to-contact in prediction motion. Experimental Brain Research, 206, 399–407. https://doi.org/10.1007/s00221-010-2416-y
11.
BoscoG.Delle MonacheS.LacquanitiF. (2012). Catching what we can’t see: manual interception of occluded fly-ball trajectories. PLoS One, 7(11), e49381. https://doi.org/10.1371/journal.pone.0049381
12.
BoscoG.MonacheS. D.GravanoS.IndovinaI.La ScaleiaB.MaffeiV.ZagoM.LacquanitiF. (2015). Filling gaps in visual motion for target capture. Frontiers in Integrative Neuroscience, 9, 13. https://doi.org/10.3389/fnint.2015.00013
13.
BrendelE.HechtH.DeLuciaP. R.GamerM. (2014). Emotional effects on time-to-contact judgments: Arousal, threat, and fear of spiders modulate the effect of pictorial content. Experimental Brain Research, 232, 2337–2347.
14.
BreskaA.DeouellL. Y. (2014). Automatic bias of temporal expectations following temporally regular input independently of high-level temporal expectation. Journal of Cognitive Neuroscience, 26(7), 1555–1571. https://doi.org/10.1162/jocn_a_00564
ChangC.-J.JazayeriM. (2018). Integration of speed and time for estimating time to contact. Proceedings of the National Academy of Sciences of the United States of America, 115(12), E2879–E2887. https://doi.org/10.1073/pnas.1713316115
CoullJ. T.NobreA. C. (1998). Where and when to pay attention: The neural systems for directing attention to spatial locations and to time intervals as revealed by both PET and fMRI. Journal of Neuroscience, 18(18), 7426–7435.
19.
CoullJ. T.NobreA. C. (2008). Dissociating explicit timing from temporal expectation with fmri. Current Opinion in Neurobiology, 18(2), 137–144. https://doi.org/10.1016/j.conb.2008.07.011
20.
CoullJ. T.FrithC.BüchelC.NobreA. (2000). Orienting attention in time: behavioural and neuroanatomical distinction between exogenous and endogenous shifts. Neuropsychologia, 38(6), 808–819. https://doi.org/10.1016/s0028-3932(99)00132-3
21.
CoullJ. T.NobreA. C.FrithC. D. (2001). The noradrenergic α2 agonist clonidine modulates behavioural and neuroanatomical correlates of human attentional orienting and alerting. Cerebral Cortex, 11(1), 73–84. https://doi.org/10.1093/cercor/11.1.73
22.
de la RosaM. D.SanabriaD.CapizziM.CorreaA. (2012). Temporal preparation driven by rhythms is resistant to working memory interference. Frontiers in Psychology, 3, Article 308. https://doi.org/10.3389/fpsyg.2012.00308
23.
DeLuciaP. R. (1991). Pictorial and motion-based information for depth perception. Journal of Experimental Psychology: Human Perception and Performance, 17(3), 738–748. https://doi.org/10.1037/0096-1523.17.3.738
24.
DeLuciaP. R. (2013). Effects of size on collision perception and implications for perceptual theory and transportation safety. Current Directions in Psychological Science, 22(3), 199–204. https://doi.org/10.1177/0963721412471679
25.
DeLuciaP. R.LiddellG. W. (1998). Cognitive motion extrapolation and cognitive clocking in prediction motion task. Journal of Experimental Psychology: Human Perception and Performance, 24(3), 901–914. https://doi.org/10.1037/0096-1523.24.3.901
26.
EngleR. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11(1), 19–23. https://doi.org/10.1111/1467-8721.00160
27.
EngleR. W. (2018). Working memory and executive attention: A revisi. Perspectives on Psychological Science, 13(2), 190–193. https://doi.org/10.1177/1745691617720478
28.
FaulF.ErdfelderE.LangA.-G.BuchnerA. (2007). G*power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146
29.
GibsonJ. J. (1979). The ecological approach to visual perception. Houghton Mifflin.
30.
GibsonJ. J. (2014). The ecological approach to visual perception: Classic edition. Psychology Press.
31.
HuC.-P.KongX.WagenmakersE.-J.LyA.PengK. (2018). The Bayes factor and its implementation in JASP: A practical primer [贝叶斯因子及其在 JASP 中的实现]. Advances in Psychological Science, 26(6), 951–965.
32.
HubbardT. L. (2020). Representational gravity: Empirical findings and theoretical implications. Psychonomic Bulletin & Review, 27(1), 36–55. https://doi.org/10.3758/s13423-019-01660-3
33.
JASP Team. (2023). JASP (Version 0.17.1) [Computer software]. University of Amsterdam.
JeffreysH. (1961). Theory of probability (3rd ed.). Oxford University Press.
36.
JonikaitisD.DeubelH.De’SperatiC. (2009). Time gaps in mental imagery introduced by competing saccadic tasks. Vision Research, 49(17), 2164–2175. https://doi.org/10.1016/j.visres.2009.05.021
37.
KingC.PrimeS. L. (2019). Auditory pitch glides influence time-to-contact judgements of visual stimuli. Experimental Brain Research, 237(8), 1907–1917. https://doi.org/10.1007/s00221-019-05561-8
38.
KiyonagaA.EgnerT. (2013). Working memory as internal attention: Toward an integrative account of internal and external selection processe. Psychonomic Bulletin & Review, 20(2), 228–242. https://doi.org/10.3758/s13423-012-0359-y
39.
KwonO.-S.KnillD. C. (2013). The brain uses adaptive internal models of scene statistics for sensorimotor estimation and planning. Proceedings of the National Academy of Sciences of the United States of America, 110(11), E1064–E1073. https://doi.org/10.1073/pnas.1214869110
40.
LandM. F.McLeodP. (2000). From eye movements to actions: how batsmen hit the ball. Nature Neuroscience, 3(12), 1340–1345. https://doi.org/10.1038/81887
41.
LeeD. N. (1976). A theory of visual control of braking based on information about time-to-collision. Perception, 5(4), 437–459. https://doi.org/10.1068/p050437
42.
LiX.BaurèsR.CremouxS. (2023). Hand movements influence the perception of time in a prediction motion task. Attention, Perception, & Psychophysics, 85(4), 1276–1286. https://doi.org/10.3758/s13414-023-02690-9
43.
LingS.CarrascoM. (2006). Sustained and transient covert attention enhance the signal via different contrast response functions. Vision Research, 46(8–9), 1210–1220. https://doi.org/10.1016/j.visres.2005.05.008
MakinA. D.PoliakoffE. (2011). Do common systems control eye movements and motion extrapolation?Quarterly Journal of Experimental Psychology, 64(7), 1327–1343. https://doi.org/10.1080/17470218.2010.548562
47.
MannD. L.SpratfordW.AbernethyB. (2013). The head tracks and gaze predicts: How the world’s best batters hit a ball. PLoS One, 8(3), e58289. https://doi.org/10.1371/journal.pone.0058289
48.
McIntyreJ.ZagoM.BerthozA.LacquanitiF. (2001). Does the brain model Newton’s laws?Nature Neuroscience, 4(7), 693. https://doi.org/10.1038/89477
49.
MotoyoshiI.IshiiT.KamachiM. G. (2015). Limited attention facilitates coherent motion processing. Journal of Vision, 15(13), 1. https://doi.org/10.1167/15.13.1
50.
OliversC. N.NieuwenhuisS. (2005). The beneficial effect of concurrent task-irrelevant mental activity on temporal attention. Psychological Science, 16(4), 265–269. https://doi.org/10.1111/j.0956-7976.2005.01526.x
51.
OliversC. N.NieuwenhuisS. (2006). The beneficial effects of additional task load, positive affect, and instruction on the attentional blink. Journal of Experimental Psychology: Human Perception and Performance, 32(2), 364. https://doi.org/10.1037/0096-1523.32.2.364
52.
PeirceJ.GrayJ. R.SimpsonS.MacAskillM.HoechenbergerR.SogoH.KastmanE.LindelovJ. K. (2019). Psychopy2: Experiments in behavior made easy. Behavior Research Methods, 51(1), 195–203. https://doi.org/10.3758/s13428-018-01193-y
QinK.ChenW.CuiJ.ZengX.LiY.LiY.YouX. (2022). The influence of time structure on prediction motion in visual and auditory modalities. Attention, Perception, & Psychophysics, 84(6), 1994–2001. https://doi.org/10.3758/s13414-021-02369-z
55.
QinK.LiY.ChenW.LiY.YouX. (2022). Effects of time structure and velocity cues on time to collision [时间结构和速度线索对碰撞时间估计的影响]. Journal of Psychological Science, 45(4), 803–810.
56.
QinK.LiuY.LiY.LiY.YouX. Q. (2022). The influence of time structure on number prediction motion. Quarterly Journal of Experimental Psychology, 76, 1862–1871. https://doi.org/10.1177/17470218221129853
57.
QinK.LiuY.LiuS.LiY.LiY.YouX. (2023). Neural mechanisms for integrating time and visual velocity cues in a prediction motion task: An fNIRS study. Psychophysiology, 61, e14425. https://doi.org/10.1111/psyp.14425
58.
RemingtonE.JazayeriM. (2017). Late bayesian inference in sensorimotor behavior. bioRxiv, 130062. https://doi.org/10.1101/130062
59.
ResulajA.KianiR.WolpertD. M.ShadlenM. N. (2009). Changes of mind in decision-making. Nature, 461(7261), 263–266. https://doi.org/10.1038/nature08275
60.
RushtonS. K.WannJ. P. (1999). Weighted combination of size and disparity: a computational model for timing a ball catch. Nature Neuroscience, 2(2), 186–190. https://doi.org/10.1038/5750
61.
ScharlauI.HorstmannG. (2006). Perceptual latency priming and illusory linemotion: Facilitation by gradients of attention?Advances in Cognitive Psychology, 2(1), 87. https://doi.org/10.2478/v10053-008-0047-7
62.
SchlichtE. J.SchraterP. R. (2007). Impact of coordinate transformation uncertainty on human sensorimotor control. Journal of Neurophysiology, 97(6), 4203–4214. https://doi.org/10.1152/jn.00160.2007
63.
SmeetsJ. B.BrennerE.TrebuchetS.MestreD. R. (1996). Is judging time-to-contact based on “tau”?Perception, 25(5), 583–590. https://doi.org/10.1068/p250583
64.
SoberS. J.SabesP. N. (2005). Flexible strategies for sensory integration during motor planning. Nature Neuroscience, 8(4), 490–497. https://doi.org/10.1038/nn1427
65.
SoechtingJ. F.JuveliJ. Z.RaoH. M. (2009). Models for the extrapolation of target motion for manual interception. Journal of Neurophysiology, 102(3), 1491–1502. https://doi.org/10.1152/jn.00398.2009
66.
SokolovA.PavlovaM. (2003). Timing accuracy in motion extrapolation: Reverse effects of target size and visible extent of motion at low and high speeds. Perception, 32(6), 699–706. https://doi.org/10.1068/p3397
67.
SperingM.GegenfurtnerK. R. (2008). Contextual effects on motion perception and smooth pursuit eye movements. Brain Research, 1225, 76–85. https://doi.org/10.1016/j.brainres.2008.04.061
68.
SwellerJ.Van MerrienboerJ. J.PaasF. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296. https://doi.org/10.1023/A:1022193728205
69.
TresilianJ. R. (1990). Perceptual information for the timing of interceptive action. Perception, 19(2), 223–239. https://doi.org/10.1068/p190223
70.
TresilianJ. R. (1991). Empirical and theoretical issues in the perception of time to contact. Journal of Experimental Psychology: Human Perception and Performance, 17(3), 865–876. https://doi.org/10.1037/0096-1523.17.3.865
WagenmakersE.-J.LoveJ.MarsmanM.JamilT.LyA.VerhagenJ.SelkerR.GronauQ. F.DropmannD.BoutinB. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25, 58–76. https://doi.org/10.3758/s13423-017-1323-7
73.
WangY.Van den BerghD.AustF.LyA.WagenmakersE.-J.HuC. (2023). The implementation of Bayesian ANOVA in JASP: A practical primer [贝叶斯方差分析在 JASP中的实现]. Psychology: Techniques and Application, 11(9), 528–541.
74.
WexlerM.KlamF. (2001). Movement prediction and movement production. Journal of Experimental Psychology: Human Perception and Performance, 27(1), 48–64. https://doi.org/10.1037/0096-1523.27.1.48
WuF.GuQ.ShiZ.GaoZ.ShenM. (2018). Striding over the “classical statistical inference trap”—application of Bayes factors in psychological studies [跳出传统假设检验方法的陷阱——贝叶斯因子在心理学研究领域的应用]. Chinese Journal of Applied Psychology, 24(3), 195–202.
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
