Evidence map›Paper›PMID 41000666›Full record

ArticlebioRxiv : the preprint server for biology2025

Disruption of theta-timescale spiking impairs learning but spares hippocampal replay.

Abhilasha Joshi, Alison E Comrie, Samuel Bray, Abhijith Mankili, Jennifer A Guidera, Rhino Nevers, Xulu Sun, Emily Monroe, Viktor Kharazia, Ryan Ly and 6 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Abhilasha JoshiDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0002-0511-3747
Alison E ComrieDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0002-2251-4892
Samuel BrayDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0002-9696-6920
Abhijith MankiliHoward Hughes Medical Institute, University of California, San Francisco, CA, USA.ORCID 0000-0002-0620-259X
Jennifer A GuideraDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0003-4013-214X
Rhino NeversDepartment of Physiology, University of California, San Francisco, CA, USA.
Xulu SunDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0003-3076-0994
Emily MonroeDepartment of Physiology, University of California, San Francisco, CA, USA.
Viktor KharaziaDepartment of Physiology, University of California, San Francisco, CA, USA.
Ryan LyLawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0001-9238-0642
Daniela Astudillo MayaDepartment of Physiology, University of California, San Francisco, CA, USA.
Denisse Morales-RodriguezDepartment of Physiology, University of California, San Francisco, CA, USA.
Jai YuDepartment of Physiology, University of California, San Francisco, CA, USA.
Anna KiselevaKavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA, USA.
Victor PerezKavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA, USA.
Loren M FrankDepartment of Physiology, University of California, San Francisco, CA, USA.ORCID 0000-0002-1752-5677

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007618 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANDERSON, MARK S · 1985 to 2020
$29.6M
Investigating neural substrates of generalization from past experienceF30MH126483 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUIDERA, JENNIFER ANN · 2021 to 2024
$150k
Hippocampal-cortical interactions supporting memory and value-guided decision-makingF31MH124366 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COMRIE, ALISON E. · 2020 to 2022
$123k
NIGMS NIH HHS T32 GM007618NIMH NIH HHS F30 MH126483NIMH NIH HHS F31 MH124366
6 · The paper itself

Abstract

The ability to rapidly learn and retrieve salient information about new environments is critical for survival. In mammals, the hippocampus plays a crucial role in that learning. Specialized features of hippocampal population coding, including network-level theta oscillatory activity, location-specific firing of principal cells, and reactivation of experience during immobility (replay), have been implicated in rapid storage and retrieval of spatial information. Disruptions of theta and replay jointly, or replay alone, are sufficient to impair learning; however, the specific contribution of theta-associated temporal structure during locomotion remains unknown. In this study, we manipulated hippocampal spiking activity in rats specifically during locomotion by optogenetically activating septal parvalbumin-expressing GABAergic neurons. We developed a closed-loop, theta phase-specific stimulation protocol that reliably reduced theta power shortly after stimulation onset. This manipulation preserved the place codes of individual cells but disrupted the fine temporal structure of endogenous spatio-temporal representations (for example, theta sequences) at the pairwise and population level. Theta disruption during locomotion was also sufficient to cause pronounced deficits in learning the more cognitively challenging component of a spatial alternation task, even though disruption was applied on only ~66% of trials. Notably, network effects accompanying theta disruption were restricted to locomotor periods; we did not observe changes in replay rate, length, or content during immobility. Together, these results demonstrate the importance of the precise temporal microstructure of locomotion-associated spatial representations in the hippocampus for learning.

Identifiers

PMID41000666
PMCPMC12458185

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.