Abstract
In the temporal bisection task, participants classify experienced stimulus durations as short or long based on their temporal similarity to previously learned reference durations. Temporal decision making in this task should be influenced by the experienced probabilities of the reference durations for adaptiveness. In this study, we tested the temporal bisection performance of mice (Mus musculus) under different short and long reference duration probability conditions implemented across two experimental phases. In Phase 1, the proportion of reference durations (compared to probe durations) was 0.5, whereas in Phase 2 it was increased to 0.8 to further examine the adjustment of choice behavior with more frequent reference duration presentations (under higher reinforcement rate). Our findings suggest that mice developed adaptive biases in their choice behaviors. These adjustments in choice behavior were nearly optimal as the mice maximized their gain to a great extent which required them to monitor stimulus probabilities as well as the level of variability in their temporal judgments. We further found that short but not long categorization response times were sensitive to stimulus probability manipulations, which in turn suggests an asymmetry between short and long categorizations. Finally, we investigated the latent decision processes underlying the bias manifested in subjects’ choice behavior within the diffusion model framework. Our results revealed that probabilistic information influenced the starting point and the rate of evidence accumulation process. Overall, the stimulus probability effects on choice behavior were modulated by the reinforcement rate. Our findings illustrate that mice can adapt their temporal behaviors with respect to the probabilistic contingencies in the environment.






Similar content being viewed by others
References
Balcı F (2014) Interval timing, dopamine and motivation. Timing Time Percept 2:379–410. doi:10.1163/22134468-00002035
Balcı F, Gallistel CR (2006) Cross-domain transfer of quantitative discriminations: is it all a matter of proportion? Psychon Bull Rev 13:636–642. doi:10.3758/BF03193974
Balcı F, Simen P (2014) Decision processes in temporal discrimination. Acta Psychol (Amst) 149:157–168. doi:10.1016/j.actpsy.2014.03.005
Balcı F, Papachristos EB, Gallistel CR, Brunner D, Gibson J, Shumyatsky GP (2008) Interval timing in genetically modified mice: a simple paradigm. Genes Brain Behav 7:373–384. doi:10.1111/j.1601-183x.2007.00348.x
Balcı F, Freestone D, Gallistel CR (2009) Risk assessment in man and mouse. Proc Natl Acad Sci USA 106:2459–2463. doi:10.1073/pnas.0812709106
Balcı F, Freestone D, Simen P, deSouza L, Cohen JD, Holmes P (2011) Optimal temporal risk assessment. Front Integr Neurosci 5:1–15. doi:10.3389/fnint.2011.00056
Bogacz R, Brown E, Moehlis J, Holmes P, Cohen JD (2006) The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychol Rev 113:700–765. doi:10.1037/0033-295X.113.4.700
Buhusi C, Meck WH (2005) What makes us tick? Functional and neural mechanisms of interval timing. Nat Rev Neurosci 6:755–765. doi:10.1038/nrn1764
Çavdaroğlu B, Zeki M, Balcı F (2014) Time-based reward maximization. Phil Trans R Soc B 369:20120461. doi:10.1098/rstb.2012.0461
Church RM, Deluty MZ (1977) Bisection of temporal intervals. J Exp Psychol Anim Behav Process 3:216–228. doi:10.1037/0097-7403.3.3.216
Çoşkun F, Sayalı ZC, Gürbüz E, Balcı F (2015) Optimal time discrimination. Q J Exp Psychol (Hove) 68:381–401. doi:10.1080/17470218.2014.944921
Dunovan KE, Tremel JJ, Wheeler ME (2014) Prior probability and feature predictability interactively bias perceptual decisions. Neuropsychologia 61:210–221. doi:10.1016/j.neuropsychologia.2014.06.024
Edwards W (1965) Optimal strategies for seeking information: models for statistics, choice reaction times, and human information processing. J Math Psychol 2:312–329. doi:10.1016/0022-2496(65)90007-6
Freestone D, Balcı F, Simen P, Church RM (2015) Optimal response rates in humans and rats. J Exp Psychol Anim Learn Cognit 41:39–51. doi:10.1037/xan0000049
Galtress T, Kirkpatrick K (2009) Reward value effects on timing in the peak procedure. Learn Motiv 40:109–131. doi:10.1016/j.lmot.2008.05.004
Galtress T, Kirkpatrick K (2010) Reward magnitude effects on temporal discrimination. Learn Motiv 41:108–124. doi:10.1016/j.lmot.2010.01.002
Gibbon J (1977) Scalar expectancy theory and Weber’s law in animal timing. Psychol Rev 84:279–325. doi:10.1037/0033-295X.84.3.279
Gibbon J (1981) On the form and location of the psychometric bisection function for time. J Math Psychol 24:58–87. doi:10.1016/0022-2496(81)90035-3
Gibbon J, Church RM, Meck WH (1984) Scalar timing in memory. Ann NY Acad Sci 423:52–77. doi:10.1111/j.1749-6632.1984.tb23417.x
Gouvêa TS, Monteiro T, Soares S, Atallah BV, Paton JJ (2014) Ongoing behavior predicts perceptual report of interval duration. Front Neurorobot 8:10. doi:10.3389/fnbot.2014.00010
Hanks TD, Mazurek ME, Kiani R, Hopp E, Shadlen MN (2011) Elapsed decision time affects the weighting of prior probability in a perceptual decision task. J Neurosci 31:6339–6352. doi:10.1523/JNEUROSCI.5613-10.2011
Jazayeri M, Shadlen MN (2010) Temporal context calibrates interval timing. Nat Neurosci 12:1020–1026. doi:10.1038/nn.2590
Jozefowiez J, Staddon JER, Cerutti DT (2009) The behavioral economics of choice and interval timing. Psychol Rev 116:519–539. doi:10.1037/a0016171
Jozefowiez J, Polack CW, Machado A, Miller RR (2014) Trial frequency effects in human temporal bisection: implication for theories of timing. Behav Processes 101:81–88. doi:10.1016/j.beproc.2013.07.023
Kheifets A, Gallistel CR (2012) Mice take calculated risks. Proc Natl Acad Sci USA 109:8776–8779. doi:10.1073/pnas.1205131109
Leite FP, Ratcliff R (2011) What cognitive processes drive response biases? A diffusion model analysis. Judgm Decis Mak 6:651–687
Lindbergh CA, Kieffaber PD (2013) The neural correlates of temporal judgments in the duration bisection task. Neuropsychologia 51:191–196. doi:10.1016/j.neuropsychologia.2012.09.001
Ludvig EA, Balcı F, Longpre KM (2008) Timescale dependence in a conditional temporal discrimination procedure. Behav Process 77:357–363. doi:10.1016/j.beproc.2007.10.002
Lustig C, Meck WH (2005) Chronic treatment with haloperidol induces deficits in working memory and feedback effects of interval timing. Brain Cogn 58:9–16. doi:10.1016/j.bandc.2004.09.005
Machado A, Keen R (2003) Temporal discrimination in a long operant chamber. Behav Process 62:157–182. doi:10.1016/s0376-6357(03)00023-8
Maggi S et al (2014) A cross-laboratory investigation of timing endophenotypes in mouse behavior. Timing Time Percept 2:35–50. doi:10.1163/22134468-00002007
Maloney LT (2002) Statistical decision theory and biological vision. In: Heyer D, Mausfeld R (eds) Perception and the physical world: psychological and philosophical issues in perception. Wiley, New York, pp 145–189
Maloney LT, Zhang H (2010) Decision-theoretic models of visual perception and action. Vis Res 50:2362–2374. doi:10.1016/j.visres.2010.09.031
Mamassian P, Landy MS, Maloney LT (2002) Bayesian modeling of visual perception. In: Rao R, Lewicki M, Olshausen B (eds) Probabilistic models of the brain: perception and neural function. MIT Press, Cambridge, pp 13–36
Mulder MJ, van Maanen L (2013) Are accuracy and reaction time affected via different processes? PLoS One 8:e80222. doi:10.1371/journal.pone.0080222
Mulder MJ, Wagenmakers EJ, Ratcliff R, Boekel W, Forstmann BU (2012) Bias in the brain: a diffusion model analysis of prior probability and potential payoff. J Neurosci 32:2335–2343. doi:10.1523/JNEUROSCI.4156-11.2012
Penney TB, Gibbon J, Meck WH (2008) Categorical scaling of duration bisection in pigeons (Columba livia), mice (Mus musculus), and humans (Homo sapiens). Psychol Sci 19:1103–1109. doi:10.1111/j.1467-9280.2008.02210.x
Raslear TG (1985) Perceptual bias and response bias in temporal bisection. Percept Psychophys 38:261–268. doi:10.3758/bf03207153
Ratcliff R (1978) A theory of memory retrieval. Psychol Rev 85:59–108. doi:10.1037/0033-295X.85.2.59
Ratcliff R (1985) Theoretical interpretations of the speed and accuracy of positive and negative responses. Psychol Rev 92:212–225. doi:10.1037/0033-295X.92.2.212
Ratcliff R (1988) Continuous versus discrete information processing: modeling accumulation of partial information. Psychol Rev 95:238–255. doi:10.1037/0033-295x.95.2.238
Ratcliff R, McKoon G (2008) The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput 20:873–922. doi:10.1162/neco.2008.12-06-420
Ratcliff R, Rouder JN (1998) Modeling response times for two-choice decisions. Psychol Sci 9:347–356. doi:10.1111/1467-9280.00067
Ratcliff R, Smith PL (2004) A comparison of sequential sampling models for two-choice reaction time. Psychol Rev 111:333–367. doi:10.1037/0033-295x.111.2.333
Rodríguez-Gironés MA, Kacelnik A (1998) Response latencies in temporal bisection: implications for timing models. In: De Keyser V, D’Ydewalle G, Vandierendonck A (eds) Time and the dynamic control of behavior. Hogrefe & Huber, Seattle, pp 51–70
Simen P, Contreras D, Buck C, Hu P, Holmes P, Cohen JD (2009) Reward rate optimization in two-alternative decision making: empirical tests of theoretical predictions. J Exp Psychol Hum Percept Perform 35:1865–1897. doi:10.1037/a0016926
Simen P, Balcı F, deSouza L, Cohen JD, Holmes P (2011) A model of interval timing by neural integration. J Neurosci 31:9238–9253. doi:10.1523/JNEUROSCI.3121-10.2011
Simen P, Rivest F, Ludvig EA, Balcı F, Killeen P (2013) Timescale invariance in the pacemaker-accumulator family of timing models. Timing Time Percept 1:159–188. doi:10.1163/22134468-0000201
Stubbs DA (1976) Response bias and the discrimination of stimulus duration. J Exp Anal Behav 25:243–250. doi:10.1901/jeab.1976.25-243
Tipples J (2015) Rapid temporal accumulation in spider fear: evidence from hierarchical drift diffusion modeling. Emotion. doi:10.1037/emo0000079
Van Ravenzwaaij D, Mulder MJ, Tuerlinckx F, Wagenmakers EJ (2012) Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test. Front Psychol 3:132. doi:10.3389/fpsyg.2012.00132
Vandekerckhove J, Tuerlinckx F (2008) Diffusion model analysis with MATLAB: a DMAT primer. Behav Res Methods 40:61–72. doi:10.3758/brm.40.1.61
Wearden JH (1992) Temporal generalization in humans. J Exp Psychol Anim Behav Process 18:134–144. doi:10.1037/0097-7403.18.2.134
Wearden JH, Ferrara A (1995) Stimulus spacing effects in temporal bisection by humans. Q J Exp Psychol B 48:289–310. doi:10.1080/14640749508401454
Whitaker S, Lowe CF, Wearden JH (2008) When to respond? And how much? Temporal control and response output on mixed-fixed-interval schedules with unequally probable components. Behav Process 77:33–42. doi:10.1016/j.beproc.2007.06.001
Acknowledgments
This study was conducted at the Koç University Animal Research Facility. The authors thank Dr. Ali Cihan Taşkın, Mehmet Yücel, and Ahmet Kocabay for their assistance in animal care and technical support. This research was supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) 1001 (#111K402) Grant to FB.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare.
Ethical approval
All animal procedures were in accordance with the ethical standards of the Koç University Animal Research Local Ethics Committee.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Akdoğan, B., Balcı, F. Stimulus probability effects on temporal bisection performance of mice (Mus musculus). Anim Cogn 19, 15–30 (2016). https://doi.org/10.1007/s10071-015-0909-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10071-015-0909-6