A New Group-Training Procedure for Habituation Demonstrates That Presynaptic Glutamate Release Contributes to Long-Term Memory in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
In the experiments reported here we have developed a new group-training protocol for assessing long-term memory for habituation in Caenorhabditis elegans. We have replicated all of the major findings of the original single-worm protocol using the new protocol: (1) distributed training produced long-term retention of training, massed training did not; (2) distributed training at long interstimulus intervals (ISIs) produced long-term retention, short ISIs did not; and (3) long-term memory for distributed training is protein synthesis-dependent as it could be blocked by heat shock during the inter-block interval. In addition, we have shown that long-term memory for habituation is graded, depending on the number of blocks of stimuli in training. The inter-block interval must be >40 min for long-term retention of training to occur. Finally, we have tested long-term memory for habituation training in a strain of worms with a mutation in a vesicular glutamate transporter in the sensory neurons that transduce tap (eat-4). The results from these eat-4 worms indicate that glutamate release from the sensory neurons has an important role in the formation of long-term memory for habituation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".