Bibliographic record
Abstract
In the developing nervous system, ordered neuronal activity patterns can occur even in the absence of sensory input and to investigate how these arise, we have used the model system of the embryonic chicken spinal motor circuit, focusing on motor neurons of the lateral motor column (LMC). At the earliest stages of their molecular differentiation, we can detect differences between medial and lateral LMC neurons in terms of expression of neurotransmitter receptor subunits, including CHRNA5, CHRNA7, GRIN2A, GRIK1, HTR1A and HTR1B, as well as the KCC2 transporter. Using patch-clamp recordings we also demonstrate that medial and lateral LMC motor neurons have subtly different activity patterns that reflect the differential expression of neurotransmitter receptor subunits. Using a combination of patch-clamp recordings in single neurons and calcium-imaging of motor neuron populations, we demonstrate that inhibition of nicotinic, muscarinic or GABA-ergic activity, has profound effects of motor circuit activity during the initial stages of neuromuscular junction formation. Finally, by analysing the activity of large populations of motor neurons at different developmental stages, we show that the asynchronous, disordered neuronal activity that occurs at early stages of circuit formation develops into organised, synchronous activity evident at the stage of LMC neuron muscle innervation. In light of the considerable diversity of neurotransmitter receptor expression, activity patterns in the LMC are surprisingly similar between neuronal types, however the emergence of patterned activity, in conjunction with the differential expression of transmitter systems likely leads to the development of near-mature patterns of locomotor activity by perinatal ages.
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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 | 0.001 |
| 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 | 0.001 |
| 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".