Target-Specific Encoding of Response Inhibition: Increased Contribution of AMPA to NMDA Receptors at Excitatory Synapses in the Prefrontal Cortex
Bibliographic record
Abstract
Impulse control suppresses actions that are inappropriate in one context, but may be beneficial in others. The medial prefrontal cortex (mPFC) mediates this process by providing a top-down signal to inhibit competing responses, although the mechanism by which the mPFC acquires this ability is unknown. To that end, we examined synaptic changes in the mPFC associated with learning to inhibit an incorrect response. Rats were trained in a simple response inhibition task to withhold responding until a signal was presented. We then measured synaptic plasticity of excitatory synapses in the mPFC, using whole-cell patch-clamp recordings, in brain slices prepared from trained rats. Response inhibition training significantly increased the relative contribution of AMPA receptors to the overall EPSC in prelimbic, but not infralimbic, neurons of the mPFC. This potentiation of synaptic transmission closely paralleled the acquisition and extinction of response inhibition. Using a retrograde fluorescent tracer, we observed that these plastic changes were selective for efferents projecting to the ventral striatum, but not the dorsal striatum or amygdala. Therefore, we suggest that response inhibition is encoded by a selective strengthening of a subset of corticostriatal projections, uncovering a synaptic mechanism of impulse control. This information could be exploited in therapeutic interventions for disorders of impulse control, such as addiction, attention deficit-hyperactivity disorder, and schizophrenia.
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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) | 0.001 | 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".