Stroke Induces Long-Lasting Deficits in the Temporal Fidelity of Sensory Processing in the Somatosensory Cortex
Bibliographic record
Abstract
Recovery from stroke is rarely complete as humans and experimental animals typically show lingering deficits in sensory function. One explanation for limited recovery could be that rewired cortical networks do not process sensory stimuli with the same temporal precision as they normally would. To examine how well peri-infarct and more distant cortical networks process successive vibro-tactile stimulations of the affected forepaw (a measure of temporal fidelity), we imaged cortical depolarizations with millisecond temporal resolution using voltage-sensitive dyes. In control mice, paired forepaw stimulations (ranging from 50 to 200 milliseconds apart) induced temporally distinct depolarizations in primary forelimb somatosensory (FLS1) cortex, and to a lesser extent in secondary FLS (FLS2) cortex. For mice imaged 3 months after stroke, the first forepaw stimulus reliably evoked a strong depolarization in the surviving region of FLS1 and FLS2 cortex. However, depolarizations to subsequent forepaw stimuli were significantly reduced or completely absent (for stimuli ≤100 milliseconds apart) in the FLS1 cortex, whereas FLS2 responses were relatively unaffected. Our data reveal that stroke induces long-lasting impairments in how well the rewired FLS1 cortex processes temporal aspects of sensory stimuli. Future therapies directed at enhancing the temporal fidelity of cortical circuits may be necessary for achieving full recovery of sensory functions.
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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) | 0.002 | 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".