Between-subject prediction reveals a shared representational geometry in the rodent hippocampus

Summary 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 vs. unique to an individual.