Disrupting dorsal hippocampus impairs category learning in rats

IF 2.2 4区 心理学 Q3 BEHAVIORAL SCIENCES
Matthew B. Broschard , Jangjin Kim , Bradley C. Love , Hunter E. Halverson , John H. Freeman
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引用次数: 0

Abstract

Categorization requires a balance of mechanisms that can generalize across common features and discriminate against specific details. A growing literature suggests that the hippocampus may accomplish these mechanisms by using fundamental mechanisms like pattern separation, pattern completion, and memory integration. Here, we assessed the role of the rodent dorsal hippocampus (HPC) in category learning by combining inhibitory DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) and simulations using a neural network model. Using touchscreens, we trained rats to categorize distributions of visual stimuli containing black and white gratings that varied along two continuous dimensions. Inactivating the dorsal HPC impaired category learning and generalization, suggesting that the rodent HPC plays an important role during categorization. Hippocampal inactivation had no effect on a control discrimination task that used identical trial procedures as the categorization tasks, suggesting that the impairments were specific to categorization. Model simulations were conducted with variants of a neural network to assess the impact of selective deficits on category learning. The hippocampal inactivation groups were best explained by a model that injected random noise into the computation that compared the similarity between category stimuli and existing memory representations. This model is akin to a deficit in mechanisms of pattern completion, which retrieves similar memory representations using partial information.

破坏背侧海马会损害大鼠的分类学习能力
分类需要平衡各种机制,既能概括共同特征,又能区分具体细节。越来越多的文献表明,海马可通过使用模式分离、模式完成和记忆整合等基本机制来完成这些机制。在这里,我们结合抑制性 DREADDs(专门由设计师药物激活的设计师受体)和神经网络模型模拟,评估了啮齿动物背侧海马(HPC)在类别学习中的作用。通过使用触摸屏,我们训练大鼠对包含黑白光栅的视觉刺激分布进行分类,这些光栅沿两个连续维度变化。失活背侧海马体会影响分类学习和泛化,这表明啮齿动物的海马体在分类过程中发挥着重要作用。海马失活对使用与分类任务相同的试验程序的对照辨别任务没有影响,这表明损伤是分类任务特有的。我们利用神经网络的变体进行了模型模拟,以评估选择性缺陷对分类学习的影响。在比较类别刺激和现有记忆表征之间相似性的计算中注入随机噪声的模型最能解释海马失活组。这一模型类似于模式完成机制的缺陷,即利用部分信息检索相似的记忆表征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.10
自引率
7.40%
发文量
77
审稿时长
12.6 weeks
期刊介绍: Neurobiology of Learning and Memory publishes articles examining the neurobiological mechanisms underlying learning and memory at all levels of analysis ranging from molecular biology to synaptic and neural plasticity and behavior. We are especially interested in manuscripts that examine the neural circuits and molecular mechanisms underlying learning, memory and plasticity in both experimental animals and human subjects.
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