Hippocampal Kindling Leads to Motor Map Expansion
Bibliographic record
Abstract
PURPOSE: To determine whether seizure activity, repeatedly elicited in the hippocampus, could alter the functional organization of neocortical movement representations (motor maps) and whether a relation exists between the number of afterdischarges recorded in the sensorimotor neocortex and the size of the motor maps. METHODS: We electrically kindled the right ventral hippocampus of Long-Evans hooded rats, twice daily, for 40 sessions and recorded the afterdischarges in the stimulated hippocampus and right sensorimotor neocortex. Between 3 and 7 days after the last seizure, we used high-resolution intracortical microstimulation to derive the forelimb-movement representations in the left (un-implanted) sensorimotor neocortex. RESULTS: In the hippocampal kindled rats, we observed a dramatic expansion of the area of neocortex that would elicit forelimb movements compared with sham-kindled controls. The number of afterdischarges recorded in the neocortex was significantly and positively correlated with the size of the motor maps. CONCLUSIONS: Seizures propagating from the hippocampus have long-distance effects on the functional organization of motor maps.
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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".