Dopamine D1‐like receptor modulates layer‐ and frequency‐specific short‐term synaptic plasticity in rat prefrontal cortical neurons
Bibliographic record
Abstract
The mesocortical dopamine (DA) input to the prefrontal cortex (PFC) is crucial for processing short-term working memory (STWM) to guide forthcoming behavior. Short-term plasticity-like post-tetanic potentiation (PTP, < 3 min) and short-term potentiation (STP, < 10 min) may underlie STWM. Using whole-cell voltage-clamp recordings, mixed glutamatergic excitatory postsynaptic currents (EPSCs) evoked by layer III or layer V stimulation (0.5 or 0.067 Hz) were recorded from layer V pyramidal neurons. With 0.5 Hz basal stimulation of layer III, brief tetani (2 x 50 Hz) induced a homosynaptic PTP (decayed: approximately 1 min). The D1-like antagonist SCH23390 (1 microm) increased the PTP amplitude and decay time without inducing changes to the tetanic response. The tetani may evoke endogenous DA release, which activates a presynaptic D1-like receptor to inhibit glutamate release to modulate PTP. With a slower (0.067 Hz) basal stimulation, the same tetani induced STP (lasting approximately 4 min, but only at 2x intensity only) that was insignificantly suppressed by SCH23390. With stimulation of layer-V-->V inputs at 0.5 Hz, layer V tetani yielded inconsisitent responses. However, at 0.067 Hz, tetani at double the intensity resulted in an STP (lasting approximately 6 min), but a long-term depression after SCH23390 application. Endogenous DA released by tetanic stimulation can interact with a D1-like receptor to induce STP in layer V-->V synapses that receive slower (0.067 Hz) frequency inputs, but suppresses PTP at layer III-->V synapses that receive higher (0.5 Hz) frequency inputs. This D1-like modulation of layer- and frequency-specific synaptic responses in the PFC may contribute to STWM processing.
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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".