Peripheral Nerve Ligation Elicits Widespread Alterations in Cortical Sensory Evoked and Spontaneous Activity
Bibliographic record
Abstract
Peripheral neuropathies result in adaptation in primary sensory and other regions of cortex, and provide a framework for understanding the localized and widespread adaptations that arise from altered sensation. Mesoscale cortical imaging achieves high temporal resolution of activity using optical sensors of neuronal activity to simultaneously image across a wide expanse of cortex and capture this adaptation using sensory-evoked and spontaneous cortical activity. Saphenous nerve ligation in mouse is an animal model of peripheral neuropathy that produces hyperalgesia circumscribed to the hindlimb. We performed saphenous nerve ligation or sham, followed by mesoscale cortical imaging using voltage sensitive dye (VSD) after ten days. We utilized subcutaneous electrical stimulation at multiple stimulus intensities to characterize sensory responses after ligation or sham, and acquired spontaneous activity to characterize functional connectivity and large scale cortical network reorganization. Relative to sham animals, the primary sensory-evoked response to hindlimb stimulation in ligated animals was unaffected in magnitude at all stimulus intensities. However, we observed a diminished propagating wave of cortical activity at lower stimulus intensities in ligated animals after hindlimb, but not forelimb, sensory stimulation. We simultaneously observed a widespread decrease in cortical functional connectivity, where midline association regions appeared most affected. These results are consistent with localized and broad alterations in intracortical connections in response to a peripheral insult, with implications for novel circuit level understanding and intervention for peripheral neuropathies and other conditions affecting sensation.
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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) | 0.002 | 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".