The left and right rodent hippocampi exhibit striking lateralization in some of the very neural substrates considered to be critical for hippocampal cognitive function. Despite this, there is an overwhelming lack of consideration for hemispheric differences in studies of the rodent hippocampus. Asymmetries identified so far suggest that a bilateral model of the hippocampus will be essential for an understanding of this brain region, and perhaps of the brain more widely. Although hypotheses have been proposed to explain how the left and right hippocampi contribute to behavior and cognition, these hypotheses have either been refuted by more recent studies or have been limited in the scope of data they explain. Here, I will first review data on human and rodent hippocampal lateralization. The implications of these data suggest that considering the hippocampus as a bilateral structure with functional lateralization will be critical moving forward in understanding the function and mechanisms of this brain region. In exploring these implications, I will then propose a hypothesis of the hippocampus as a bilateral structure. This discrete‐continuous hypothesis proposes that the left and right hippocampi contribute to spatial memory and navigation in a complementary manner. Specifically, the left hemisphere stores spatial information as discrete, salient locations, and the right hemisphere represents space continuously, contributing to route computation and flexible spatial navigation. Consideration of hippocampal lateralization in designing future studies may provide insight into the function of the hippocampus and resolve debates concerning its function.

中文翻译：

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啮齿动物海马体作为双侧结构：半球侧化综述

左右啮齿动物海马体在一些被认为对海马体认知功能至关重要的神经基质中表现出显着的侧化。尽管如此，在啮齿动物海马体的研究中，绝大多数都没有考虑到半球差异。迄今为止发现的不对称性表明，海马体的双侧模型对于理解这个大脑区域，甚至更广泛地理解大脑至关重要。尽管已经提出假设来解释左右海马如何促进行为和认知，但这些假设要么被最近的研究驳斥，要么在他们解释的数据范围内受到限制。在这里，我将首先回顾人类和啮齿动物海马侧化的数据。这些数据的含义表明，将海马体视为具有功能性单侧化的双侧结构对于理解该大脑区域的功能和机制至关重要。在探索这些含义时，我将提出海马体作为双侧结构的假设。这种离散-连续假设提出左右海马体以互补的方式促进空间记忆和导航。具体来说，左半球将空间信息存储为离散的显着位置，右半球连续表示空间，有助于路线计算和灵活的空间导航。