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A computational model of the interaction between external and internal cues for the control of hippocampal place cells

机译：外部和内部线索与控制海马局部细胞的互动的计算模型

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Place cell activity in the hippocampus depends in a complex way on the information from two major sensory sources: External (e.g., visual) cues and internal cues (self-motion, vestibular cues). Dissociation of the two inputs in the presence of the animal modifies the place fields in ways that depend on the magnitude of the difference: If the mismatch is small, place fields typically follow the external cues, but if the mismatch is large, their activity is determined mainly by the internal cues. The dynamics underlying the interaction between the external and internal cues in the hippocampus is not completely known, but is an important issue in understanding the hippocampus' role in spatial learning and navigation. In this paper, we propose an attractor model of the hippocampus which captures the interaction between external and internal sensory inputs to the hippocampus. The proposed mechanism accounts for the difference seen in the experimental results in the case of a small versus a large discrepancy between the visual and idiothetic information.
机译：在海马中放置细胞活动依赖于来自两个主要感官来源的信息：外部（例如，视觉）提示和内部提示（自动运动，前庭提示）。在动物的存在下，两个输入的解散以取决于差异的幅度的方式修改了地位领域：如果不匹配是小的，那么地方场通常遵循外部提示，但如果不匹配大，则它们的活动是主要由内部提示决定。海马外部和内部线索之间的相互作用的动态并不完全知道，但却是了解海马在空间学习和导航中的作用。在本文中，我们提出了一种海马的吸引力模型，其捕获外部和内部感官输入到海马之间的相互作用。所提出的机制占实验结果中所见的差异，在较小的视觉和成熟信息之间的巨大差异。

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