Stabilization of thalamo‐cortical long‐term potentiation by the amygdala: cholinergic and transcription‐dependent mechanisms
Bibliographic record
Abstract
Synaptic potentiation allows neurons to enhance excitability and store information for extended time periods. We examined the role of the amygdaloid complex, known to facilitate long-term memory encoding, to influence synaptic strength at thalamo-cortical synapses. In urethane-anaesthetized rats, theta-burst stimulation of the dorsal lateral geniculate nucleus of the thalamus induced early phase (1-2 h) long-term potentiation (LTP) of the field postsynaptic potential (fPSP) recorded in the ipsilateral primary visual cortex. Electrical stimulation (100 Hz) of the amygdala 5 min after thalamic stimulation converted early phase LTP to stable late-phase (> 4 h) LTP. This effect was not correlated with the degree of electrocorticographic activation of V1 induced by amygdala stimulation. Amygdala stimulation without thalamic theta-burst stimulation did not change thalamo-cortical fPSPs. The centrally acting cholinergic-muscarinic receptor antagonist scopolamine (1 mg/kg, i.p.), but not peripherally acting methyl-scopolamine, completely blocked the amygdala-induced conversion of early to late-phase thalamo-cortical LTP. Further, ventricular application of the transcription inhibitor anisomycin (250 micro g) reduced amygdala-induced late-phase LTP induction. These results demonstrate that the amygdaloid complex transforms time-limited synaptic enhancement of thalamo-cortical transmission into long lasting increases in synaptic strength. These processes are mediated, at least in part, by cholinergic and transcription-dependent mechanisms. These amygdaloid-induced effects provide a potential mechanism underlying long-term enhancement of sensory transmission and information encoding in thalamo-cortical networks.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".