We use our sense of time to identify temporal relationships between events and to anticipate actions. The degree to which we can exploit temporal contingencies depends on the variability of our measurements of time. We asked humans to reproduce time intervals drawn from different underlying distributions. As expected, production times were more variable for longer intervals. However, production times exhibited a systematic regression toward the mean. Consequently, estimates for a sample interval differed depending on the distribution from which it was drawn. A performance-optimizing Bayesian model that takes the underlying distribution of samples into account provided an accurate description of subjects' performance, variability and bias. This finding suggests that the CNS incorporates knowledge about temporal uncertainty to adapt internal timing mechanisms to the temporal statistics of the environment.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Mauk, M.D. & Buonomano, D.V. The neural basis of temporal processing. Annu. Rev. Neurosci. 27, 307–340 (2004).
Gallistel, C.R. & Gibbon, J. Time, rate, and conditioning. Psychol. Rev. 107, 289–344 (2000).
Rakitin, B.C. et al. Scalar expectancy theory and peak-interval timing in humans. J. Exp. Psychol. Anim. Behav. Process. 24, 15–33 (1998).
Brannon, E.M., Libertus, M.E., Meck, W.H. & Woldorff, M.G. Electrophysiological measures of time processing in infant and adult brains: Weber's Law holds. J. Cogn. Neurosci. 20, 193–203 (2008).
Gibbon, J. & Church, R.M. Comparison of variance and covariance patterns in parallel and serial theories of timing. J. Exp. Anal. Behav. 57, 393–406 (1992).
Reutimann, J., Yakovlev, V., Fusi, S. & Senn, W. Climbing neuronal activity as an event-based cortical representation of time. J. Neurosci. 24, 3295–3303 (2004).
Matell, M.S. & Meck, W.H. Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. Brain Res. Cogn. Brain Res. 21, 139–170 (2004).
Ahrens, M. & Sahani, M. Inferring elapsed time from stochastic neural processes. in Advances in Neural Information Processing Systems (eds. Platt, J.C. Koller, D. Singer, Y. & Roweis, S.) (MIT Press, Cambridge, Massachusetts, 2008).
Casella, G. & Berger, R.L. (Duxbury Resource Center, Pacific Grove, California, 2002).
Lewis, P.A. & Miall, R.C. The precision of temporal judgment: milliseconds, many minutes, and beyond. Phil. Trans. R. Soc. Lond. B 364, 1897–1905 (2009).
Treisman, M. Temporal discrimination and the indifference interval. Implications for a model of the “internal clock”. Psychol. Monogr. 77, 1–31 (1963).
Hollingworth, H.L. The central tendency of judgement. Arch. Psychol. 4, 44–52 (1913).
Parducci, A. Category judgment: a range-frequency model. Psychol. Rev. 72, 407–418 (1965).
Helson, H. Adaptation-level as a basis for a quantitative theory of frames of reference. Psychol. Rev. 55, 297–313 (1948).
Kersten, D., Mamassian, P. & Yuille, A. Object perception as Bayesian inference. Annu. Rev. Psychol. 55, 271–304 (2004).
Körding, K.P. & Wolpert, D.M. Bayesian integration in sensorimotor learning. Nature 427, 244–247 (2004).
Knill, D.C. & Richards, W. Perception as Bayesian Inference (Cambridge University Press, Cambridge, 1996).
Mamassian, P., Landy, M.S. & Maloney, L.T. Bayesian modeling of visual perception. in Probabilistic Models of the Brain: Perception and Neural Function (eds. Rao, R.P.N., Olshausen, B.A. & Lewicki, M.S.) 239–286 (MIT Press, Cambridge, Massachusetts, 2002).
Miyazaki, M., Nozaki, D. & Nakajima, Y. Testing Bayesian models of human coincidence timing. J. Neurophysiol. 94, 395–399 (2005).
Hudson, T.E., Maloney, L.T. & Landy, M.S. Optimal compensation for temporal uncertainty in movement planning. PLOS Comput. Biol. 4, e1000130 (2008).
Bernardo, J.M. & Smith, A.F.M. Bayesian Theory (Wiley, New York, 1994).
Stocker, A.A. & Simoncelli, E.P. Noise characteristics and prior expectations in human visual speed perception. Nat. Neurosci. 9, 578–585 (2006).
Trommershäuser, J., Maloney, L.T. & Landy, M.S. Statistical decision theory and the selection of rapid, goal-directed movements. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 20, 1419–1433 (2003).
Mamassian, P. Overconfidence in an objective anticipatory motor task. Psychol. Sci. 19, 601–606 (2008).
Ernst, M.O. & Banks, M.S. Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415, 429–433 (2002).
Jacobs, R.A. Optimal integration of texture and motion cues to depth. Vision Res. 39, 3621–3629 (1999).
Tassinari, H., Hudson, T.E. & Landy, M.S. Combining priors and noisy visual cues in a rapid pointing task. J. Neurosci. 26, 10154–10163 (2006).
Graf, E.W., Warren, P.A. & Maloney, L.T. Explicit estimation of visual uncertainty in human motion processing. Vision Res. 45, 3050–3059 (2005).
Körding, K.P. & Wolpert, D.M. The loss function of sensorimotor learning. Proc. Natl. Acad. Sci. USA 101, 9839–9842 (2004).
Raphan, M. & Simoncelli, E.P. Learning to be Bayesian without supervision. in Neural Information Processing Systems 1145–1152 (MIT Press, Cambridge, Massachusetts, 2006).
Toth, L.J. & Assad, J.A. Dynamic coding of behaviorally relevant stimuli in parietal cortex. Nature 415, 165–168 (2002).
Lauwereyns, J. et al. Feature-based anticipation of cues that predict reward in monkey caudate nucleus. Neuron 33, 463–473 (2002).
Shadlen, M.N. & Newsome, W.T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J. Neurophysiol. 86, 1916–1936 (2001).
Gold, J.I., Law, C.T., Connolly, P. & Bennur, S. The relative influences of priors and sensory evidence on an oculomotor decision variable during perceptual learning. J. Neurophysiol. 100, 2653–2668 (2008).
Janssen, P. & Shadlen, M.N. A representation of the hazard rate of elapsed time in macaque area LIP. Nat. Neurosci. 8, 234–241 (2005).
Maimon, G. & Assad, J.A. A cognitive signal for the proactive timing of action in macaque LIP. Nat. Neurosci. 9, 948–955 (2006).
Schultz, W. & Romo, R. Role of primate basal ganglia and frontal cortex in the internal generation of movements. I. Preparatory activity in the anterior striatum. Exp. Brain Res. 91, 363–384 (1992).
Meck, W.H., Penney, T.B. & Pouthas, V. Cortico-striatal representation of time in animals and humans. Curr. Opin. Neurobiol. 18, 145–152 (2008).
Cui, X., Stetson, C., Montague, P.R. & Eagleman, D.M. Ready...go: amplitude of the FMRI signal encodes expectation of cue arrival time. PLoS Biol. 7, e1000167 (2009).
Nobre, A., Correa, A. & Coull, J. The hazards of time. Curr. Opin. Neurobiol. 17, 465–470 (2007).
Rao, S.M., Mayer, A.R. & Harrington, D.L. The evolution of brain activation during temporal processing. Nat. Neurosci. 4, 317–323 (2001).
Allan, L.G. Perception of time. Percept. Psychophys. 26, 340–354 (1979).
Creelman, C.D. Human discrimination of auditory duration. J. Acoust. Soc. Am. 34, 582–593 (1962).
Lee, I.H. & Assad, J.A. Putaminal activity for simple reactions or self-timed movements. J. Neurophysiol. 89, 2528–2537 (2003).
Mita, A., Mushiake, H., Shima, K., Matsuzaka, Y. & Tanji, J. Interval time coding by neurons in the presupplementary and supplementary motor areas. Nat. Neurosci. 12, 502–507 (2009).
Okano, K. & Tanji, J. Neuronal activities in the primate motor fields of the agranular frontal cortex preceding visually triggered and self-paced movement. Exp. Brain Res. 66, 155–166 (1987).
Tanaka, M. Cognitive signals in the primate motor thalamus predict saccade timing. J. Neurosci. 27, 12109–12118 (2007).
Tanaka, M. Inactivation of the central thalamus delays self-timed saccades. Nat. Neurosci. 9, 20–22 (2006).
Buonomano, D.V. & Maass, W. State-dependent computations: spatiotemporal processing in cortical networks. Nat. Rev. Neurosci. 10, 113–125 (2009).
We are grateful to G. Horwitz for sharing resources and to both G. Horwitz and V. de Lafuente for their feedback on the manuscript. This work was supported by a fellowship from Helen Hay Whitney Foundation, the Howard Hughes Medical Institute and research grants EY11378 and RR000166 from the US National Institutes of Health.
The authors declare no competing financial interests.
About this article
Cite this article
Jazayeri, M., Shadlen, M. Temporal context calibrates interval timing. Nat Neurosci 13, 1020–1026 (2010). https://doi.org/10.1038/nn.2590
Hidden by bias: how standard psychophysical procedures conceal crucial aspects of peripheral visual appearance
Scientific Reports (2021)
Nature Human Behaviour (2021)
Small numerosity advantage for sequential enumeration on RSVP stimuli: an object individuation-based account
Psychological Research (2021)
Cross-dimensional magnitude interaction is modulated by representational noise: evidence from space–time interaction
Psychological Research (2021)