MétaCan
Menu
Back to cohort
Record W7112450371

Molecular Events Underlying the Enhancement of Conditioned Taste Aversion by D-Cycloserine

2011· article· en· W7112450371 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2011
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsTaste aversionLong-term potentiationClassical conditioningForebrainAmygdalaAssociative learningParabrachial NucleusConditioning
DOInot available

Abstract

fetched live from OpenAlex

Conditioned taste aversion (CTA) is a form of associative learning in which an animal avoids and reacts aversively to a taste (conditioned stimulus, CS) that has been previously paired with a toxin or other malaise-inducing stimulus (unconditioned stimulus, US). CTA is unique among Pavlovian learning paradigms because conditioning is supported across long delays (minutes to hours) between taste and toxin [Garcia et al., 1966; Kalat & Rozin, 1973; Smith & Roll, 1967] and is robust in that an animal can form a strong aversion that can last for months [Houpt et al., 1996; Martin & Timmins, 1980; Steinert et al., 1980] after only a single trial of a taste-toxin pairing [Garcia & Koelling, 1967]. CTA learning is easily manipulated, as the strength or magnitude of the aversion is dependent on the concentration, saliency, and duration of the CS, as well as the amount or strength of the US [Barker, 1976; Dragoin, 1971; Nachman & Ashe, 1973]. The anatomical pathway involved in CTA is well characterized and includes the nucleus of the solitary tract, parabrachial nucleus, amygdala, and gustatory cortex [for a review, see Yamamoto, 2006]. The two forebrain regions, the amygdala and gustatory cortex, are particularly important as lesions of these areas cause deficits in CTA learning [Josselyn et al., 2004; Nerad et al., 1996], and both structures exhibit cellular changes during and after CTA acquisition, such as induction of long-term potentiation [Escobar & Bermudez-Ratoni, 2000], activation of immediate early genes such as c-fos [Lamprecht and Dudai, 1995], phosphorylation of markers such as MAPK [Berman et al., 1998], phosphorylation of NMDAR subunits such as NR2B [Rosenblum et al., 1997], and changes in the activation and expression of genes such as CREB, fra-2, and fen-1 [Desmedt et al., 2003; Kwon et al., 2008; Saavedra-Rodríguez et al., 2009]. As with other forms of associative learning, CTA is N-methyl-D-aspartate receptor (NMDAR)-dependent [Jimenez & Tapia, 2004]. Pharmacological inactivation of NMDARs attenuates or blocks CTA [e.g. Gutierrez et al., 1999] while activation by NMDAR agonists enhances CTA learning [Land & Riccio, 1997]. Data from our lab show that the NMDAR agonist, D-cycloserine (DCS), dose-dependently enhances taste learning, but only under certain parameters [Nunnink et al., 2007].

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 score0.010
Threshold uncertainty score0.501

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 head0.077
GPT teacher head0.248
Teacher spread0.171 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueDigiNole (Florida State University)Same topicMemory and Neural MechanismsFrench-language works237,207