BRAIN K99/R00. HPC experimental & computational systems neuro. Ephys4life.
Postdoc @NUFeinbergMed with John Disterhoft and co-mentor Sara Solla, PhD from MIT with Matt Wilson, BS from Carnegie Mellon 🔬🧠🐀🌈
(((Dr Hannah Wirtshafter))) 🔬
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Thank you thank you thank you to all my coauthors, any and all people who gave feedback, and the NIH FOR SUPPORTING THIS RESEARCH!!
Would love any questions/complaints/feedback :)
The new paper shows that CA1 reorganizes to task demands.
The population geometry paper shows what the organization can do.
The population geometry paper shows what the organization can do.
Together, the two papers argue:
CA1 is not simply a spatial map with task signals layered on top.
When a task demands it, temporally structured task coding can dominate -- EVEN during navigation.
In other words, space stops being the hippocampus's organizing principle.
In this revised preprint, we show that during trace learning:
- Population activity forms structured trajectories in low-dimensional space
- These trajectories reflect task structure over time
- And they align across days & animals
That raised a deeper question:
If CA1 reorganizes during task engagement,
what shape does that reorganization take?
That’s what our revised manifold paper addresses:
Conserved hippocampal population geometry supports task generalization
https://www.biorxiv.org/content/10.1101/2024.10.24.620127v6
Conserved hippocampal population geometry supports task generalization
How learning generalizes across contexts is a fundamental question in neuroscience, as successful behavior often requires transferring acquired knowledge to new environments. Conditioning tasks provide a clear example of such generalization, with learned responses rapidly expressed across distinct spatial contexts. A central challenge in understanding the neural basis of this ability is determining how the hippocampus represents task-related information across environments, given that its spatial representations remap with context. Here, we used calcium imaging to record hippocampal population activity as rats performed a conditioning task across multiple spatial contexts. To characterize task-related population structure, we applied dimensionality reduction and alignment methods to construct low-dimensional manifolds of hippocampal activity. We found that task-related population activity occupied a stable geometric structure across contexts, despite pronounced remapping of spatial representations. Strikingly, this task-related geometry was conserved not only across contexts within individual animals but also across animals, revealing a shared organization of task representations in the hippocampus. These findings provide a population-level account of how task-related information is preserved across changing spatial environments and suggest that hippocampal task representations follow shared population-level geometric organization across individuals. ### Competing Interest Statement The authors have declared no competing interest. National Institute of Mental Health, K99 MH135062 National Institute on Aging, R37 AG008796/AG/NIA National Institute of Neurological Disorders and Stroke, R01 NS113804/NS/NINDS
At the population level, task–task similarity > everything else.
Task periods put CA1 into a distinct state.
And this wasn't a small modulation, it was a large-scale reweighting of the code.
And no, this wasn’t speed.
And yes, animals were running during the trace window.
And no, task activity wasn’t confined to place fields.
And no, task activity wasn’t restricted to ripple/sitting states.
The signal survived all of that.
During task performance we saw two big things happen:
3× more neurons increased event rate to the task than were spatially tuned
Spatial reliability dropped significantly
The task didn’t just get pasted on top of the spatial map.
It shifted the dominant population structure.
When non-spatial responses show up, they’re often interpreted as place field gating or arousal.
But most of that work was done in immobile or restrained animals.
But our rats were freely moving the whole time, and the task was administered at random times and locations
This builds directly on our (heavily) revised manifold paper:
Conserved hippocampal population geometry supports task generalization
https://www.biorxiv.org/content/10.1101/2024.10.24.620127v6
Together, they argue that task engagement can shift the dominant population structure in CA1 -- even during navigation.
Conserved hippocampal population geometry supports task generalization
How learning generalizes across contexts is a fundamental question in neuroscience, as successful behavior often requires transferring acquired knowledge to new environments. Conditioning tasks provide a clear example of such generalization, with learned responses rapidly expressed across distinct spatial contexts. A central challenge in understanding the neural basis of this ability is determining how the hippocampus represents task-related information across environments, given that its spatial representations remap with context. Here, we used calcium imaging to record hippocampal population activity as rats performed a conditioning task across multiple spatial contexts. To characterize task-related population structure, we applied dimensionality reduction and alignment methods to construct low-dimensional manifolds of hippocampal activity. We found that task-related population activity occupied a stable geometric structure across contexts, despite pronounced remapping of spatial representations. Strikingly, this task-related geometry was conserved not only across contexts within individual animals but also across animals, revealing a shared organization of task representations in the hippocampus. These findings provide a population-level account of how task-related information is preserved across changing spatial environments and suggest that hippocampal task representations follow shared population-level geometric organization across individuals. ### Competing Interest Statement The authors have declared no competing interest. National Institute of Mental Health, K99 MH135062 National Institute on Aging, R37 AG008796/AG/NIA National Institute of Neurological Disorders and Stroke, R01 NS113804/NS/NINDS