Dopaminergic Suppression of Synaptic Transmission in the Lateral Entorhinal Cortex
Bibliographic record
Abstract
Dopaminergic projections to the superficial layers of the lateral entorhinal cortex can modulate the strength of olfactory inputs to the region. We have found that low concentrations of dopamine facilitate field EPSPs in the entorhinal cortex, and that higher concentrations of dopamine suppress synaptic responses. Here, we have used whole-cell current clamp recordings from layer II neurons to determine the mechanisms of the suppression. Dopamine (10 to 50 microM) hyperpolarized membrane potential and reversibly suppressed the amplitude of EPSPs evoked by layer I stimulation. Both AMPA- and NMDA-mediated components were suppressed, and paired-pulse facilitation was also enhanced indicating that the suppression is mediated largely by reduced glutamate release. Blockade of D(2)-like receptors greatly reduced the suppression of EPSPs. Dopamine also lowered input resistance, and reduced the number of action potentials evoked by depolarizing current steps. The drop in input resistance was mediated by activation of D(1)-like receptors, and was prevented by blocking K(+) channels with TEA. The dopaminergic suppression of synaptic transmission is therefore mediated by a D(2) receptor-dependent reduction in transmitter release, and a D(1) receptor-dependent increase in a K(+) conductance. This suppression of EPSPs may dampen the strength of sensory inputs during periods of elevated mesocortical dopamine activity.
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 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) | 0.000 | 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".