Between-subject prediction reveals a shared representational geometry in the rodent hippocampus
Between-subject prediction reveals a shared representational geometry in the rodent hippocampus
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DOI：
10.1016/j.cub.2021.07.061
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发表时间：
2021-10-12
期刊：
影响因子：
9.2
通讯作者：
van der Meer, Matthijs A. A.
中科院分区：
文献类型：
--
作者：
Chen, Hung-Tu;Manning, Jeremy R.;van der Meer, Matthijs A. A.
啮齿动物的海马体在环境中构建统计上独立的表征（“全局重新映射”），并以明显随机的方式将单个神经元放电场分配到环境中的位置，这一过程被认为有助于海马体在情景记忆中的作用。这种随机映射意味着，根据一个受试者对同一经历的编码来预测另一受试者对给定经历的海马编码应该是具有挑战性的。与此预测相反，我们发现，通过在大鼠之间构建一个共同的表征空间，其中使用几何操作（旋转、反射和平移；“超对齐”）来对齐神经活动，我们可以基于（1）目标大鼠的“左”试验（L）和（2）来自不同源大鼠的L和R试验之间的关系来预测目标大鼠T迷宫上的“右”试验（R）的数据。这些跨受试者预测依赖于整体活动模式，包括放电率和场位置，并且优于许多控制映射，例如基于排列数据的预测，这些数据打破了单个神经元的 L 和 R 活动之间的关系，以及那些仅基于受试者内预测的预测。这项工作构成了成功跨学科预测海马体整体活动模式的原理证明，并为理解不同体验的结构提供了新的见解，从而使进一步的工作能够确定经验编码的哪些方面是个人共享的，哪些方面是个人独有的。
The rodent hippocampus constructs statistically independent representations across environments ("global remapping") and assigns individual neuron firing fields to locations within an environment in an apparently random fashion, processes thought to contribute to the role of the hippocampus in episodic memory. This random mapping implies that it should be challenging to predict hippocampal encoding of a given experience in one subject based on the encoding of that same experience in another subject. Contrary to this prediction, we find that by constructing a common representational space across rats in which neural activity is aligned using geometric operations (rotation, reflection, and translation; "hyperalignment"), we can predict data of "right"trials (R) on a T-maze in a target rat based on (1) the "left"trials (L) of the target rat and (2) the relationship between L and R trials from a different source rat. These cross-subject predictions relied on ensemble activity patterns, including both firing rate and field location, and outperformed a number of control mappings, such as those based on permuted data that broke the relationship between L and R activity for individual neurons and those based solely on within-subject prediction. This work constitutes proof of principle for successful cross-subject prediction of ensemble activity patterns in the hippocampus and provides new insights in understanding how different experiences are structured, enabling further work identifying what aspects of experience encoding are shared versus unique to an individual.