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Record W1974192130 · doi:10.1101/lm.7.3.140

Operant Conditioning in <i>Lymnaea</i>: Evidence for Intermediate- and Long-term Memory

2000· article· en· W1974192130 on OpenAlexafffund
Ken Lukowiak, Nimet Adatia, Darin Krygier, Naweed I. Syed

Bibliographic record

VenueLearning & Memory · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of Calgary
FundersAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsLymnaea stagnalisDuration (music)Session (web analytics)Long-term memoryPsychologyLymnaeaConditioningAudiologyNeuroscienceTraining (meteorology)Developmental psychologyBiologyMedicineCognitionSnailComputer science

Abstract

fetched live from OpenAlex

Aerial respiration of the pond snail, Lymnaea stagnalis, can be operantly conditioned; however, the parameters necessary to produce long-term (LTM) or intermediate term memory (ITM) have not previously been investigated. We conducted training using procedures that varied in the duration of the training session, the number of training sessions per day or the amount of time between subsequent training sessions (SI). We found that by varying the duration and frequency of the training session learning could be differentially produced. Furthermore, the ability to form LTM was dependent not only on the duration of the training session was also the interval between training sessions, the SI. Thus it was possible to produce ITM, which persists for up to 3 hr, and not form LTM, which persists at least 18 hr. Learning, ITM, and LTM can be differentially produced by altering the SI, the duration of the training session, or the number of training sessions per day. These findings may allow us to begin to elucidate the underlying neural mechanisms of learning, ITM, and LTM.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.344
Teacher spread0.290 · 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

Citations152
Published2000
Admission routes2
Has abstractyes

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