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RECORD 是一个高通量、可定制的系统,揭示了啮齿动物在类似觅食的决策过程中所利用的行为策略。

RECORD, a high-throughput, customizable system that unveils behavioral strategies leveraged by rodents during foraging-like decision-making.

机构信息

Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA.

Computational Science Program, University of Texas at El Paso, El Paso, TX, USA.

出版信息

Commun Biol. 2024 Jul 6;7(1):822. doi: 10.1038/s42003-024-06489-8.

Abstract

Translational studies benefit from experimental designs where laboratory organisms use human-relevant behaviors. One such behavior is decision-making, however studying complex decision-making in rodents is labor-intensive and typically restricted to two levels of cost/reward. We design a fully automated, inexpensive, high-throughput framework to study decision-making across multiple levels of rewards and costs: the REward-COst in Rodent Decision-making (RECORD) system. RECORD integrates three components: 1) 3D-printed arenas, 2) custom electronic hardware, and 3) software. We validated four behavioral protocols without employing any food or water restriction, highlighting the versatility of our system. RECORD data exposes heterogeneity in decision-making both within and across individuals that is quantifiably constrained. Using oxycodone self-administration and alcohol-consumption as test cases, we reveal how analytic approaches that incorporate behavioral heterogeneity are sensitive to detecting perturbations in decision-making. RECORD is a powerful approach to studying decision-making in rodents, with features that facilitate translational studies of decision-making in psychiatric disorders.

摘要

转化研究受益于使用人类相关行为的实验设计,其中一种行为是决策。然而,在啮齿动物中研究复杂的决策需要大量的工作,通常仅限于成本/回报的两个层次。我们设计了一个完全自动化、成本低、高通量的框架,用于研究多个层次的奖励和成本的决策:啮齿动物决策中的奖励-成本(RECORD)系统。RECORD 集成了三个组件:1)3D 打印竞技场,2)定制电子硬件,和 3)软件。我们验证了四个行为协议,没有采用任何食物或水限制,突出了我们系统的多功能性。RECORD 数据暴露了个体内和个体间决策的异质性,这种异质性可以被定量地限制。使用羟考酮自我给药和酒精消费作为测试案例,我们揭示了如何将行为异质性纳入分析方法能够敏感地检测到决策中的扰动。RECORD 是一种强大的研究啮齿动物决策的方法,其特点有助于研究精神障碍中的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732a/11227549/dd2c60447f45/42003_2024_6489_Fig1_HTML.jpg

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