State-Dependent GABAergic Inhibition of Sciatic Nerve-Evoked Responses of Dorsal Spinocerebellar Tract Neurons
Bibliographic record
Abstract
Peripheral nerve-evoked potentials recorded in the cerebellum 35 yr ago inferred that sensory transmission via the dorsal spinocerebellar tract (DSCT) is reduced occasionally and only during eye movements of active sleep compared with wakefulness or quiet sleep. A reduction or withdrawal of primary afferent input and/or ongoing inhibition of individual lumbar DSCT neurons may underlie this occurrence. This study distinguished between these possibilities by examining whether peripheral nerve-evoked responses recorded from individual DSCT neurons are suppressed specifically during active sleep, and if so, whether GABA mediates this phenomenon. Synaptic responses to threshold stimuli applied to the sciatic nerve were characterized by a single spike response at short latency and/or a longer latency burst of action potentials. During the state of quiet wakefulness, response magnitude did not differ from that observed during quiet sleep. During active sleep, short and long latency responses were suppressed by 26 and 14%, respectively, and returned to pre-active sleep levels following awakening from active sleep. Sciatic nerve-evoked early and late responses were further analyzed in a paired fashion around computer-tagged eye movement events that hallmark the state of active sleep. Response magnitude was suppressed by 14.4 and 11.5%, respectively, during eye movement events of active sleep. The GABA(A) antagonist bicuculline, applied juxtacellularly by microiontophoresis, abolished response suppression during non-eye movement periods and eye movement events of active sleep. In conclusion, synaptic transmission via DSCT neurons is inhibited by GABA tonically during non-eye movement periods and phasically during eye movement events of active sleep.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".