Bibliographic record
Abstract
This article reviews especially the early history of glutamate and GABA as neurotransmitters in vertebrates. The proposal that some amino acids could mediate synaptic transmission in the CNS initially met with much resistance. Both GABA and its parent glutamate are abundant in the brain; but, unlike glutamate, GABA had no obvious metabolic function. By the late 1950s, the switch of interest from electrical to chemical transmission invigorated the search for central transmitters. Its identification with Factor I, a brain extract that inhibited crustacean muscle, focused interest on GABA as a possible inhibitory transmitter. In the first microiontophoretic tests, though GABA strongly inhibited spinal neurons, these effects were considered 'non-specific'. Strong excitation by glutamate (and other acidic amino acids) led to the same conclusion. However, their great potency and rapid actions on cortical neurons convinced other authors that these endogenous amino acids are probably synaptic transmitters. This was partly confirmed by showing that both IPSPs and GABA greatly increased Cl() conductance, their effects having similar reversal potentials. Many anticonvulsants proving to be GABA antagonists, by the 1970s GABA became widely accepted as a mediator of IPSPs. Progress was much slower for glutamate. Being generated on distant dendrites, EPSPs could not be easily compared with glutamate-induced excitation, and the search for specific antagonists was long hampered by the lack of blockers and the variety of glutamate receptors. These difficulties were gradually overcome by the application of powerful techniques, such as single channel recording, cloning receptors, as well as new pharmacological tools.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".