Complex forelimb movements and cortical topography evoked by intracortical microstimulation in male and female mice
Bibliographic record
Abstract
The motor cortex is crucial for the voluntary control of skilled movement in mammals and is topographically organized into representations of the body (motor maps). Intracortical microstimulation of the motor cortex with long-duration pulse trains (LD-ICMS; ~500 ms) evokes complex movements, occurring in multiple joints or axial muscles, with characteristic movement postures and cortical topography across a variety of mammalian species. Although the laboratory mouse is extensively used in basic and pre-clinical research, high-resolution motor maps elicited with electrical LD-ICMS in both sexes of the adult mouse has yet to be reported. To address this knowledge gap, we performed LD-ICMS of the forelimb motor cortex in both male (n = 10) and naturally cycling female (n = 8) C57/BL6J mice under light ketamine-xylazine anesthesia. Complex and simple movements were evoked from historically defined caudal (CFA) and rostral (RFA) forelimb areas. Four complex forelimb movements were identified consisting of Elevate, Advance, Dig, and Retract postures with characteristic movement sequences and endpoints. Furthermore, evoked complex forelimb movements and cortical topography in mice were organized within the CFA in a unique manner relative to a qualitative comparison with the rat.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".