GABA Expression and Regulation by Sensory Experience in the Developing Visual System
Bibliographic record
Abstract
The developing retinotectal system of the Xenopus laevis tadpole is a model of choice for studying visual experience-dependent circuit maturation in the intact animal. The neurotransmitter gamma-aminobutyric acid (GABA) has been shown to play a critical role in the formation of sensory circuits in this preparation, however a comprehensive neuroanatomical study of GABAergic cell distribution in the developing tadpole has not been conducted. We report a detailed description of the spatial expression of GABA immunoreactivity in the Xenopus laevis tadpole brain at two key developmental stages: stage 40/42 around the onset of retinotectal innervation and stage 47 when the retinotectal circuit supports visually-guided behavior. During this period, GABAergic neurons within specific brain structures appeared to redistribute from clusters of neuronal somata to a sparser, more uniform distribution. Furthermore, we found that GABA levels were regulated by recent sensory experience. Both ELISA measurements of GABA concentration and quantitative analysis of GABA immunoreactivity in tissue sections from the optic tectum show that GABA increased in response to a 4 hr period of enhanced visual stimulation in stage 47 tadpoles. These observations reveal a remarkable degree of adaptability of GABAergic neurons in the developing brain, consistent with their key contributions to circuit development and function.
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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".