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通过计算设计的训练协议在老鼠中增强关联学习

Xu O Zhang¹, Yili Zhang¹, Claire E Cho¹

¹Department of Neurobiology and Anatomy, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas.

Biological psychiatry global open science

|February 1, 2024

概括

一个计算模型通过调整试验间隔 (ITI) 来优化学习协议. 这一策略增强了老鼠的恐惧灭绝记忆,表明了改善人类认知的潜在应用.

科学领域:

神经科学是一个神经科学.
计算生物学计算生物学
行为科学行为科学

背景情况:

学习涉及具有特定时间激活模式的蛋白激酶.
在Aplysia中,优化的试验间隔 (ITI) 通过协调蛋白激酶A (PKA) 和细胞外信号调节激酶 (ERK) 激活来增强非关联性学习.
目前尚不清楚这种策略是否有利于哺乳动物的关联学习.

研究的目的:

调查以计算模型驱动的方法来优化ITI是否可以增强哺乳动物的关联学习.
确定优化学习协议对大鼠恐惧调节和灭绝记忆的影响.
探索优化协议对学习分子标记物的影响,例如酸化cAMP反应元素结合 (pCREB) 蛋白.

主要方法:

模拟了1000个不同ITI的训练协议,以确定基于大鼠海马PKA和ERK动态的最佳协议.
在听觉恐惧调节和灭绝实验中,对成年雄性大鼠应用了最佳和控制协议.
利用免疫组织化学测量与恐惧获取相关的大脑区域的pCREB水平.

主要成果:

与不规则的ITI相结合的最佳调节方案损害了灭绝记忆的获取,但增强了恐惧记忆的检索和在特定的足震强度下自发的恢复.
最佳灭绝协议显著改善了上下文恐惧记忆的灭绝,并减少了自发恢复.
最优的调节方案增加了牙状回形中的pCREB水平,表明长期增强的潜能.

结论:

以计算模型驱动的行为干预可以有效地增强哺乳动物的关联学习.
优化ITI,以酶动态为指导,为改善恐惧灭绝和记忆提供了一个新的策略.
这些发现表明,增强人类认知功能的潜在应用.

关键词:

联想式记忆是一种联想式的记忆.计算模型计算模型恐惧是对恐惧进行调节的.恐惧灭绝灭绝的恐惧长期增强潜力长期增强潜力间隔学习的学习空间.

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