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Olfactory learning in the rat pup: A model that may permit visualization of a mammalian memory trace

2004· review· en· W2013279514 on OpenAlex
John H. McLean, Carolyn W. Harley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuroreport · 2004
Typereview
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCREBNeurosciencePhosphorylationOlfactory bulbBiological neural networkMemory consolidationNeurogenesisBiologyOdorIntracellularOlfactionCentral nervous systemCell biologyTranscription factorHippocampusBiochemistry

Abstract

fetched live from OpenAlex

Over the past 10 years considerable insight into intracellular interactions leading to long-term memory formation have been gleaned from various neural circuits within invertebrate and vertebrate species. This review suggests that, while certain intracellular signaling pathways are commonly involved across species, it is important to analyze specific neural systems because critical differences among systems appear to exist. The olfactory bulb has been used by our group to estimate the influence of neuromodulatory systems (serotonin and norepinephrine) on intracellular processes leading to learning. We describe here how activation of noradrenergic input to mitral cells increases cAMP leading to CREB phosphorylation when paired with a conditioning stimulus, odor. CREB phosphorylation is causal in odor preference learning leading to long-term memory for the odor. However, the relationship between cAMP activation and CREB phosphorylation is not straight forward; overstimulation of cAMP pathways impedes learning and prevents CREB phosphorylation. Excessive CREB phosphorylation also interferes with learning.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.338
GPT teacher head0.362
Teacher spread0.025 · 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