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

Abstract

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.

Neuronal tuning to threat exposure remains stable in the mouse prefrontal cortex over multiple days

“…Our finding of a preserved structure of population activity both in time and across subjects bears similarity to and extends upon previous reports: Stable latent dynamics of population activity despite changing cell identities on different recording days have been observed in monkey motor cortex upon learning of a motor task [34]. Moreover, latent dynamics of population activity in motor cortex [35], orbitofrontal cortex [36], and hippocampus [37][38][39] are preserved across individuals executing learned tasks and appear in sensory-motor cortex during foraging for rewards [40]. Our results imply that stable and preserved population activity patterns are not restricted to cognitive or motor behaviors but that they also characterize the mPFC during innate stress coping.…”

The Individualized Neural Tuning Model: Precise and generalizable cartography of functional architecture in individual brains

“…However, in theory, the algorithm itself can be applied to any kind of data matrices. In our previous hyperalignment algorithms, the searchlight procedure originally developed based on response profiles (RHA) (Feilong et al, 2018; Guntupalli et al, 2016; Haxby et al, 2020; Jiahui et al, 2020) has been applied successfully to connectivity profiles (CHA) (Feilong et al, 2021; Guntupalli et al, 2018; Nastase et al, 2020) and a hybrid of both (H2A) (Busch et al, 2021); and the original algorithm developed based on fMRI data of humans (Haxby et al, 2011) has been applied successfully to electrophysiology recording data of rodent neurons (Chen et al, 2021). We leave it to future works to assess the generalizability of the INT model to other functional profiles, modalities, and species.…”

From monkeys to humans: observation-based EMG brain–computer interface decoders for humans with paralysis

“…Recently, Safaie et al used similar alignment techniques to show that latent signals in M1 were preserved across monkeys as they performed a center-out reaching task using a planar manipulandum; latent signals were also preserved in the dorsolateral striatum of mice that grasped and pulled a joystick (Safaie et al 2022). Other recent studies revealed that low-dimensional neural structure within the hippocampus and the sensorimotor cortex is preserved across rats for a variety of behaviors, ranging from locomotion along a linear track inside a maze to unconstrained movement in an arena (Rubin et al 2019, Chen et al 2021, Nieh et al 2021, Melbaum et al 2022.…”