Longitudinal monitoring of mesoscopic cortical activity in a mouse model of microinfarcts reveals dissociations with behavioral and motor function
Bibliographic record
Abstract
Small vessel disease is characterized by sporadic obstruction of small vessels leading to neuronal cell death. These microinfarcts often escape detection by conventional magnetic resonance imaging and are identified only upon postmortem examination. Our work explores a brain-wide microinfarct model in awake head-fixed mice, where occlusions of small penetrating arterioles are reproduced by endovascular injection of fluorescent microspheres. Mesoscopic functional connectivity was mapped longitudinally in awake GCaMP6 mice using genetically encoded calcium indicators for transcranial wide-field calcium imaging. Microsphere occlusions were quantified and changes in cerebral blood flow were measured with laser speckle imaging. The neurodeficit score in microinfarct mice was significantly higher than in sham, indicating impairment in motor function. The novel object recognition test showed a reduction in the discrimination index in microinfarct mice compared to sham. Graph-theoretic analysis of functional connectivity did not reveal significant differences in functional connectivity between sham and microinfarct mice. While behavioral tasks revealed impairments following microinfarct induction, the absence of measurable functional alterations in cortical activity has a less straightforward interpretation. The behavioral alterations produced by this model are consistent with alterations observed in human patients suffering from microinfarcts and support the validity of microsphere injection as a microinfarct model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".