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Record W2062820973 · doi:10.1002/hipo.10113

Effects of hippocampal cholinergic deafferentation on learning strategy selection in a visible platform version of the water maze

2003· article· en· W2062820973 on OpenAlexaff
Jennifer L. Bizon, Jung‐Soo Han, Carol Hudon, Michela Gallagher

Bibliographic record

VenueHippocampus · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversité Laval
FundersNational Institute on Aging
KeywordsNeuroscienceHippocampal formationBasal forebrainStriatumHippocampusPsychologyCholinergicAcetylcholineMorris water navigation taskVentral striatumForebrainCholinergic neuronWater mazeCentral nervous systemDopamineBiologyPharmacology

Abstract

fetched live from OpenAlex

Recent evidence has suggested that the relative levels of acetylcholine (ACh) between brain structures may be an important factor in the choice of behavioral strategy in settings in which either hippocampal or dorsal striatal brain systems can be employed both effectively and independently (McIntyre and Gold. 1999. Soc Neurosci Abs 25:1388). The current investigation used the neurotoxin 192 IgG-saporin to deplete the hippocampus of ACh selectively, while leaving ACh in other brain regions, including dorsal striatum, intact. Rats were then trained on a version of the Morris water maze, in which behavioral strategies attributed to the hippocampus and dorsal striatum are placed in direct competition. It was predicted that rats with hippocampal ACh depletion would display a cue bias. Contrary to this prediction, depleting hippocampal ACh did not bias against and, in fact, promoted use of a hippocampal place strategy in this task, as indicated by choice in competition tests and performance on hidden platform training trials. These data add to a growing literature demonstrating that the septohippocampal cholinergic system is not required for accurate spatial learning and suggest a complex role for basal forebrain projections in processing information about the spatial environment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.004
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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 teacher head, 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

Citations35
Published2003
Admission routes1
Has abstractyes

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