Literature DB >> 26733674

Mice plan decision strategies based on previously learned time intervals, locations, and probabilities.

Tuğçe Tosun1, Ezgi Gür1, Fuat Balcı2.   

Abstract

Animals can shape their timed behaviors based on experienced probabilistic relations in a nearly optimal fashion. On the other hand, it is not clear if they adopt these timed decisions by making computations based on previously learnt task parameters (time intervals, locations, and probabilities) or if they gradually develop their decisions based on trial and error. To address this question, we tested mice in the timed-switching task, which required them to anticipate when (after a short or long delay) and at which of the two delay locations a reward would be presented. The probability of short trials differed between test groups in two experiments. Critically, we first trained mice on relevant task parameters by signaling the active trial with a discriminative stimulus and delivered the corresponding reward after the associated delay without any response requirement (without inducing switching behavior). During the test phase, both options were presented simultaneously to characterize the emergence and temporal characteristics of the switching behavior. Mice exhibited timed-switching behavior starting from the first few test trials, and their performance remained stable throughout testing in the majority of the conditions. Furthermore, as the probability of the short trial increased, mice waited longer before switching from the short to long location (experiment 1). These behavioral adjustments were in directions predicted by reward maximization. These results suggest that rather than gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision strategies by directly integrating their previous knowledge of task parameters into their timed behavior, supporting the model-based representational account of temporal risk assessment.

Entities:  

Keywords:  decision making; interval timing; mice; probabilities; temporal risk assessment

Mesh:

Year:  2016        PMID: 26733674      PMCID: PMC4725500          DOI: 10.1073/pnas.1518316113

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  27 in total

Review 1.  Time, rate, and conditioning.

Authors:  C R Gallistel; J Gibbon
Journal:  Psychol Rev       Date:  2000-04       Impact factor: 8.934

Review 2.  Neuropsychological mechanisms of interval timing behavior.

Authors:  M S Matell; W H Meck
Journal:  Bioessays       Date:  2000-01       Impact factor: 4.345

3.  Immediacy versus anticipated delay in the time-left experiment: a test of the cognitive hypothesis.

Authors:  D T Cerutti; J E R Staddon
Journal:  J Exp Psychol Anim Behav Process       Date:  2004-01

4.  Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons.

Authors:  Matthew S Matell; Warren H Meck; Miguel A L Nicolelis
Journal:  Behav Neurosci       Date:  2003-08       Impact factor: 1.912

Review 5.  Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes.

Authors:  Matthew S Matell; Warren H Meck
Journal:  Brain Res Cogn Brain Res       Date:  2004-10

Review 6.  What makes us tick? Functional and neural mechanisms of interval timing.

Authors:  Catalin V Buhusi; Warren H Meck
Journal:  Nat Rev Neurosci       Date:  2005-10       Impact factor: 34.870

7.  Bayesian theories of conditioning in a changing world.

Authors:  Aaron C Courville; Nathaniel D Daw; David S Touretzky
Journal:  Trends Cogn Sci       Date:  2006-06-21       Impact factor: 20.229

8.  Response bias and the discrimination of stimulus duration.

Authors:  D A Stubbs
Journal:  J Exp Anal Behav       Date:  1976-03       Impact factor: 2.468

Review 9.  Choice, uncertainty and value in prefrontal and cingulate cortex.

Authors:  Matthew F S Rushworth; Timothy E J Behrens
Journal:  Nat Neurosci       Date:  2008-03-26       Impact factor: 24.884

10.  Interval timing in genetically modified mice: a simple paradigm.

Authors:  F Balci; E B Papachristos; C R Gallistel; D Brunner; J Gibson; G P Shumyatsky
Journal:  Genes Brain Behav       Date:  2007-08-13       Impact factor: 3.449

View more
  8 in total

1.  What is timed in a fixed-interval temporal bisection procedure?

Authors:  Adam E Fox; Katelyn E Prue; Elizabeth G E Kyonka
Journal:  Learn Behav       Date:  2016-12       Impact factor: 1.986

Review 2.  Finding numbers in the brain.

Authors:  C R Gallistel
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-02-19       Impact factor: 6.237

3.  Count-based decision-making in mice: numerosity vs. stimulus control.

Authors:  Pınar Toptaş; Ezgi Gür; Fuat Balcı
Journal:  Anim Cogn       Date:  2022-07-17       Impact factor: 2.899

4.  Mice expressing P301S mutant human tau have deficits in interval timing.

Authors:  Travis Larson; Vaibhav Khandelwal; Matthew A Weber; Mariah R Leidinger; David K Meyerholz; Nandakumar S Narayanan; Qiang Zhang
Journal:  Behav Brain Res       Date:  2022-06-17       Impact factor: 3.352

5.  Numerical averaging in mice.

Authors:  Ezgi Gür; Yalçın Akın Duyan; Fuat Balcı
Journal:  Anim Cogn       Date:  2020-11-04       Impact factor: 3.084

6.  An approach to monitoring home-cage behavior in mice that facilitates data sharing.

Authors:  Edoardo Balzani; Matteo Falappa; Fuat Balci; Valter Tucci
Journal:  Nat Protoc       Date:  2018-05-17       Impact factor: 13.491

7.  Rodents monitor their error in self-generated duration on a single trial basis.

Authors:  Tadeusz Władysław Kononowicz; Virginie van Wassenhove; Valérie Doyère
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-01       Impact factor: 12.779

8.  Using Temporal Expectation to Assess Auditory Streaming in Mice.

Authors:  Gaëlle A Chapuis; Paul T Chadderton
Journal:  Front Behav Neurosci       Date:  2018-09-11       Impact factor: 3.558

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.