Genetically identified spinal interneurons integrating tactile afferents for motor control
Bibliographic record
Abstract
Our movements are shaped by our perception of the world as communicated by our senses. Perception of sensory information has been largely attributed to cortical activity. However, a prior level of sensory processing occurs in the spinal cord. Indeed, sensory inputs directly project to many spinal circuits, some of which communicate with motor circuits within the spinal cord. Therefore, the processing of sensory information for the purpose of ensuring proper movements is distributed between spinal and supraspinal circuits. The mechanisms underlying the integration of sensory information for motor control at the level of the spinal cord have yet to be fully described. Recent research has led to the characterization of spinal neuron populations that share common molecular identities. Identification of molecular markers that define specific populations of spinal neurons is a prerequisite to the application of genetic techniques devised to both delineate the function of these spinal neurons and their connectivity. This strategy has been used in the study of spinal neurons that receive tactile inputs from sensory neurons innervating the skin. As a result, the circuits that include these spinal neurons have been revealed to play important roles in specific aspects of motor function. We describe these genetically identified spinal neurons that integrate tactile information and the contribution of these studies to our understanding of how tactile information shapes motor output. Furthermore, we describe future opportunities that these circuits present for shedding light on the neural mechanisms of tactile processing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".