Spreading depolarization triggered by elevated potassium is weak or absent in the rodent lower brain
Bibliographic record
Abstract
We examined in live coronal slices from rat and mouse which brain regions generate potassium-triggered spreading depolarization (SD Kt ). This technique simulates cortical spreading depression, which underlies migraine aura in the intact brain. An SD Kt episode was evoked by increasing bath [K + ] o and recorded as a propagating front of elevated light transmittance representing transient neuronal swelling in gray matter of neocortex, hippocampus, striatum, and thalamus. In contrast, SD Kt was not imaged in hypothalamic nuclei or brainstem with exception of those nuclei near the dorsal brainstem surface. In rat slices, single neurons were whole-cell current clamped during SD Kt . “Higher” neurons depolarized to near zero millivolts indicating SD Kt generation. In contrast, seven types of neurons in hypothalamus and brainstem only slowly depolarized without generating SD Kt , supporting our imaging findings. Therefore, SD Kt is not a default of CNS neurons but rather displays a region-specific susceptibility, similar to anoxic depolarization, which we have proposed is correlated with a region’s vulnerability to traumatic brain injury. In the higher brain, SD Kt may be a vestigial spreading depolarization that originally evolved to shut down and vasoconstrict gray matter regions more exposed to impact and contusion.
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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 | 0.001 |
| 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".