Differential Contribution of Reticulospinal Cells to the Control of Locomotion Induced By the Mesencephalic Locomotor Region
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In lampreys as in other vertebrates, the reticulospinal (RS) system relays inputs from the mesencephalic locomotor region (MLR) to the spinal locomotor networks. Semi-intact preparations of larval sea lamprey were used to determine the relative contribution of the middle (MRRN) and the posterior (PRRN) rhombencephalic reticular nuclei to swimming controlled by the MLR. Intracellular recordings were performed to examine the inputs from the MLR to RS neurons. Stimulation of the MLR elicited monosynaptic excitatory responses of a higher magnitude in the MRRN than in the PRRN. This differential effect was not attributed to intrinsic properties of RS neurons. Paired recordings showed that at threshold intensity for swimming, spiking activity was primarily elicited in RS cells of the MRRN. Interestingly, cells of the PRRN began to discharge at higher stimulation intensities only when MRRN cells had reached their maximal discharge rate. Glutamate antagonists were ejected in either nucleus to reduce their activity. Ejections over the MRRN increased the stimulation threshold for evoking locomotion and resulted in a marked decrease in the swimming frequency and the strength of the muscle contractions. Ejections over the PRRN decreased the frequency of swimming. This study provides support for the concept that RS cells show a specific recruitment pattern during MLR-induced locomotion. RS cells in the MRRN are primarily involved in initiation and maintenance of low-intensity swimming. At higher frequency locomotor rhythm, RS cells in both the MRRN and the PRRN are recruited.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it