A self-initiated cue-reward learning procedure for neural recording in rodents

一种用于啮齿动物神经记录的自主线索奖励学习程序

阅读:1

Abstract

BACKGROUND: Single-unit recording in Pavlovian conditioning tasks requires the use of within-subject designs as well as sampling a considerable number of trials per trial type and session, which increases the total trial count. Pavlovian conditioning, on the other hand, requires a long average intertrial interval (ITI) relative to cue duration for cue-specific learning to occur. These requirements combined can make the session duration unfeasibly long. NEW METHOD: To circumvent this issue, we developed a self-initiated variant of the Pavlovian magazine-approach procedure in rodents. Unlike the standard procedure, where the animals passively receive the trials, the self-initiated procedure grants animals agency to self-administer and self-pace trials from a predetermined, pseudorandomized list. Critically, whereas in the standard procedure the typical ITI is in the order of minutes, our procedure uses a much shorter ITI (10 s). RESULTS: Despite such a short ITI, discrimination learning in the self-initiated procedure is comparable to that observed in the standard procedure with a typical ITI, and superior to that observed in the standard procedure with an equally short ITI. COMPARISON WITH EXISTING METHOD(S): The self-initiated procedure permits delivering 100 trials in a ∼1-h session, almost doubling the number of trials safely attainable over that period with the standard procedure. CONCLUSIONS: The self-initiated procedure enhances the collection of neural correlates of cue-reward learning while producing good discrimination performance. Other advantages for neural recording studies include ensuring that at the start of each trial the animal is engaged, attentive and in the same location within the conditioning chamber.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。