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Record W4387359330 · doi:10.1101/2023.10.03.560558

Mice require proprioception to establish long-term visuospatial memory

2023· preprint· en· W4387359330 on OpenAlexaff
Olivia Rutler, Serena Persaud, Stylianos Kosmidis, Jung M. Park, Nina Harano, Randy M. Bruno, Michael E. Goldberg

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsColumbia College
FundersNational Eye InstituteNational Institutes of Health
KeywordsGazeNeuroscienceProprioceptionSomatosensory systemPerceptionPsychologyRepresentation (politics)Hippocampal formationHippocampusSensory systemVestibular systemCognitive psychologyComputer visionComputer science

Abstract

fetched live from OpenAlex

Because the retina moves constantly, the retinotopic representation of the visual world is spatially inaccurate and the brain must transform this spatially inaccurate retinal signal to a spatially accurate signal usable for perception and action. One of the salient discoveries of modern neuroscience is the role of the hippocampus in establishing gaze-independent, long-term visuospatial memories. The rat hippocampus has neurons which report the animal's position in space regardless of its angle of gaze. Rats with hippocampal lesions are unable to find the location of an escape platform hidden in a pool of opaque fluid, the Morris Water Maze (MWM) based on the visual aspects of their surrounding environment. Here we show that the representation of proprioception in the dysgranular zone of primary somatosensory cortex is equivalently necessary for mice to learn the location of the hidden platform, presumably because without it they cannot create a long-term gaze-independent visuospatial representation of their environment from the retinal signal. They have no trouble finding the platform when it is marked by a flag, and they have no motor or vestibular deficits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.288
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicMemory and Neural Mechanisms→French-language works237,207→