Evidence map›Paper›PMID 38709845›Full record

ArticlePLoS computational biology2024

Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of Aβ pathology.

Udaysankar Chockanathan, Krishnan Padmanabhan

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

2 authors.

Udaysankar ChockanathanDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.ORCID 0000-0002-4469-1371
Krishnan PadmanabhanDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America.ORCID 0000-0002-3255-8346

Funding

University of Rochester Mentoring Environment: Nurturing Training Opportunities in Research (UR-MENTOR)T32GM007356 · NIGMS · UNIVERSITY OF ROCHESTER · PI O'BANION, M. KERRY · 1985 to 2023
$15.1M
CRCNS: Linking Synaptic Populations and Computation Using Statistical MechanicsR01NS135763 · NINDS · UNIVERSITY OF ROCHESTER · PI Krishnan Padmanabhan · 2023 to 2026
$984k
MATING INDUCED ACTIVATION OF THE RAT PROGESTIN RECEPTORF31MH011392 · NIMH · UNIVERSITY OF MASSACHUSETTS AMHERST · PI AUGER, ANTHONY P · 1996 to 1997
–
NIGMS NIH HHS T32 GM007356NIMH NIH HHS F31 MH011392NINDS NIH HHS R01 NS135763
6 · The paper itself

Abstract

Alzheimer's Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behavioral deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventral CA1 (vCA1), two hippocampal areas known to be structurally and functionally diverse, in the APP/PS1 mouse model of amyloidosis. Despite similar levels of Aβ pathology, dCA1 and vCA1 showed distinct disruptions in neuronal population activity as animals navigated a virtual reality environment. In dCA1, pairwise correlations and entropy, a measure of the diversity of activity patterns, were decreased in APP/PS1 mice relative to age-matched C57BL/6 controls. However, in vCA1, APP/PS1 mice had increased pair-wise correlations and entropy as compared to age matched controls. Finally, using maximum entropy models, we connected the microscopic features of population activity (correlations) to the macroscopic features of the population code (entropy). We found that the models' performance increased in predicting dCA1 activity, but decreased in predicting vCA1 activity, in APP/PS1 mice relative to the controls. Taken together, we found that Aβ exerts distinct effects across different hippocampal regions, suggesting that the various behavioral deficits of AD may reflect underlying heterogeneities in neuronal circuits and the different disruptions that Aβ pathology causes in those circuits.

Indexed as

Alzheimer DiseaseAmyloid beta-Protein PrecursorCA1 Region, HippocampalAmyloid beta-PeptidesAnimalsComputational BiologyDisease Models, AnimalMaleMiceMice, Inbred C57BLMice, TransgenicNeuronsPresenilin-1Amyloid beta-PeptidesAmyloid beta-Protein PrecursorPresenilin-1

Identifiers

PMID38709845
PMCPMC11098488

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LicenceCC BY
Read underepoch 390

Registered trials

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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.