Molecular Events Underlying the Enhancement of Conditioned Taste Aversion by D-Cycloserine
Bibliographic record
Abstract
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].
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".