Literature DB >> 28102509

Mice optimize timed decisions about probabilistic outcomes under deadlines.

Ezgi Gür1, Fuat Balcı2.   

Abstract

Optimal performance in temporal decisions requires the integration of timing uncertainty with environmental statistics such as probability or cost functions. Reward maximization under response deadlines constitutes one of the most stringent examples of these problems. The current study investigated whether and how mice can optimize their timing behavior in a complex experimental setting under a response deadline in which reward maximization required the integration of timing uncertainty with a geometrically increasing probability/decreasing cost function. Mice optimized their performance under seconds-long response deadlines when the underlying function was reward probability but approached this level of performance when the underlying function was reward cost, only under the assumption of logarithmically scaled subjective costs. The same subjects were then tested in a timed response inhibition task characterized by response rules that conflicted with the initial task, not responding earlier than a schedule as opposed to not missing the deadline. Irrespective of original test groups, mice optimized the timing of their inhibitory control in the second experiment. These results provide strong support for the ubiquity of optimal temporal risk assessment in mice.

Entities:  

Keywords:  Interval timing; Optimality; Reward function; Reward maximization; Timing uncertainty

Mesh:

Year:  2017        PMID: 28102509     DOI: 10.1007/s10071-017-1073-y

Source DB:  PubMed          Journal:  Anim Cogn        ISSN: 1435-9448            Impact factor:   3.084


  3 in total

1.  Numerical averaging in mice.

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

2.  Striatal dopamine and the temporal control of behavior.

Authors:  Benjamin J De Corte; Lucia M Wagner; Matthew S Matell; Nandakumar S Narayanan
Journal:  Behav Brain Res       Date:  2018-09-10       Impact factor: 3.332

3.  Recalibrating timing behavior via expected covariance between temporal cues.

Authors:  Benjamin J De Corte; Rebecca R Della Valle; Matthew S Matell
Journal:  Elife       Date:  2018-11-02       Impact factor: 8.140

  3 in total

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