Forming temporal expectations plays an instrumental role for the optimization of behavior and allocation of attentional resources. Although the effects of temporal expectations on visual attention are well-established, the question of whether temporal predictions modulate the behavioral outputs of the autonomic nervous system such as the pupillary response remains unanswered. Therefore, this study aimed to obtain an online measure of pupil size while human participants were asked to differentiate between visual targets presented after varying time intervals since trial onset. Specifically, we manipulated temporal predictability in the presentation of target stimuli consisting of letters which appeared after either a short or long delay duration (1.5 vs. 3 s) in the majority of trials (75%) within different test blocks. In the remaining trials (25%), no target stimulus was present to investigate the trajectory of preparatory pupillary response under a low level of temporal uncertainty. The results revealed that the rate of preparatory pupillary response was contingent upon the time of target appearance such that pupils dilated at a higher rate when the targets were expected to appear after a shorter as compared to a longer delay period irrespective of target presence. The finding that pupil size can track temporal regularities and exhibit differential preparatory response between different delay conditions points to the existence of a distributed neural network subserving temporal information processing which is crucial for cognitive functioning and goal-directed behavior.
ChunM.M. & PotterM.C. (2001).
The attentional blink and task switching within and across modalities. In ShapiroK. (Ed.) The limits of Attention: Temporal Constraints in Human Information Processing (pp. 20–35). New York NY USA: Oxford University Press.
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. J. Neurosci.187426–7435.
GilzenratM.S.NieuwenhuisS.JepmaM. & CohenJ.D. (2010).
Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function. Cogn. Affect. Behav. Neurosci.10252–269.
KononowiczT.W.Van RijnH. & MeckW.H. (in press).
Timing and time perception: A critical review of neural timing signatures before, during, and after the to-be-timed interval. In WixtedJ. (Editor-in-Chief) and SerencesJ. (Ed. Vol. II) Sensation Perception and Attention Volume II – Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience (4th ed.) (pp. 1–35). New York NY USA: Wiley.
Reuter-LorenzP.OonkH.BarnesL. & HughesH. (1995).
Effects of warning signals and fixation point offsets on the latencies of pro- versus antisaccades: Implications for an interpretation of the gap effect. Exp. Brain Res.103287–293.
TaylorJ.R.ElsworthJ.D.LawrenceM.S.SladekJ.R.RothR.H. & RedmondD.E. (1999).
Spontaneous blink rates correlate with dopamine levels in the caudate nucleus of MPTP-treated monkeys. Exp. Neurol.158214–220.
TerhuneD.B.SullivanJ.G. & SimolaJ.M. (2016).
Time dilates after spontaneous blinking. Curr. Biol. 26R59–R60.ThomaschkeR.WagenerA.KieselA. & HoffmannJ. (2011).
The scope and precision of specific temporal expectancy: Evidence from a variable foreperiod paradigm. Atten. Percept. Psychophys.73953–964.
TressoldiP.E.MartinelliM.SemenzatoL. & CappatoS. (2011).
Let your eyes predict: Prediction accuracy of pupillary responses to random alerting and neutral sounds. Sage Open1–7. doi: 10.1177/2158244011420451
Van RijnH.KononowiczT.W.MeckW.H.NgK.K. & PenneyT.B. (2011).
Contingent negative variation and its relation to time estimation: A theoretical evaluation. Front. Int. Neurosci.. 591. doi: 10.3389/fnint.2011.00091