Functional Architecture of Executive Control and Associated Event-Related Potentials
Bibliographic record
Abstract
Medial frontal cortex enables executive control by monitoring relevant information and using it to adapt behavior. In macaques performing a saccade countermanding (stop-signal) task, we recorded EEG over and neural spiking across all layers of the supplementary eye field (SEF). We report the laminar organization of concurrently activated neurons monitoring the conflict between incompatible responses and the timing of events serving goal maintenance and executive control. We also show their relation to coincident event-related potentials (ERP). Neurons signaling response conflict were largely broad-spiking found across all layers. Neurons signaling the interval until specific task events were largely broad-spiking neurons concentrated in L3 and L5. Neurons predicting the duration of control and sustaining the task goal until the release of operant control were a mix of narrow- and broad-spiking neurons confined to L2/3. We complement these results with the first report of a monkey homologue of the N2/P3 ERP complex associated with response inhibition. N2 polarization varied with error likelihood and P3 polarization varied with the duration of expected control. The amplitude of the N2 and P3 were predicted by the spike rate of different classes of neurons located in L2/3 but not L5/6. These findings reveal important, new features of the cortical microcircuitry supporting executive control and producing associated ERP.
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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 | 0.001 |
| 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".