Contralesional hippocampal spreading depolarization promotes functional recovery after stroke
Bibliographic record
Abstract
Ischemic stroke, brain tissue infarction following obstructed cerebral blood flow, leads to long-term neurological deficits and death. While neocortex is a commonly affected region with established preclinical models, less is known about deeper brain strokes, despite having unique neurological outcomes. We induced focal ischemic stroke while simultaneously monitoring neuronal activity in awake behaving Thy1-GCaMP6f mice by delivering and collecting light through bilateral fiberoptic implants. Unilateral hippocampal stroke resulted in atypical wandering behavior coincident with ipsilesional terminal spreading depolarization (sustained increase in GCaMP6f fluorescence). Ischemia induced seizures that propagated to the contralesional hippocampus triggering a transient spreading depolarization, predominantly in females. Hippocampal stroke impaired contextual fear conditioning acquired pre-stroke. Yet, 7 days post-stroke, contextual fear conditioning was only improved in mice with contralesional spreading depolarization. Blunting peri-stroke contralesional spreading depolarization prevented recovery of hippocampus-dependent learning. Together, we show that regionally isolated deleterious and beneficial spreading depolarizations can occur concurrently in the murine brain during acute stroke. Neural mechanisms underlying deep brain strokes are not fully understood. Here authors demonstrate that spreading depolarizations occur in the intact contralesional hippocampus during unilateral stroke. These spreading depolarizations are more common in female mice and allow preservation of hippocampus-dependent learning.
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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".