Acute Low Alcohol Disrupts Hippocampus-Striatum Neural Correlate of Learning Strategy by Inhibition of PKA/CREB Pathway in Rats
Bibliographic record
Abstract
The hippocampus and striatum guide place-strategy and response-strategy learning, respectively, and they have dissociable roles in memory systems, which could compensate in case of temporary or permanent damage. Although acute alcohol (AA) treatment had been shown to have adverse effects on hippocampal function, whether it causes the functional compensation and the underlying mechanisms is unknown. In this study, rats treated with a low dose of AA avoided a hippocampus-dependent spatial strategy, instead preferring a striatum-dependent response strategy. Consistently, the learning-induced increase in hippocampal, but not striatal, pCREB was rendered less pronounced due to diminished activity of pPKA, but not pERK or pCaMKII. As rats approached the turn-decision area, Sp-cAMP, a PKA activator, was found to mitigate the inhibitory effect of AA on intra- and cross-structure synchronized neuronal oscillations, and rescue response-strategy bias and spatial learning deficits. Our study provides strong evidence of the critical link between neural couplings and strategy selection. Moreover, the PKA/CREB-signaling pathway is involved in the suppressive effect of AA on neural correlates of place-learning strategy. The novel important evidence provided here shows the functional couplings between the hippocampus and striatum in spatial learning processing and suggests possible avenues for therapeutic intervention.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".