Multimodal Stimulation in a Microfluidic Device Facilitates Studies of Interneurons in Sensory Integration in <i>C. elegans</i>
Bibliographic record
Abstract
Animals' perception and behavior involve integration of multiple sensory modalities. Caenorhabditis elegans is a useful model for studying multimodal sensory integration, as it has well-characterized neuronal circuits in a relatively simple nervous system. However, most studies based on functional imaging have only been conducted on single modal stimuli, because well-controlled multimodal experiments for C. elegans are technically difficult. For instance, no single systems currently deliver precise stimuli with spatial, temporal, and intensity control, despite prior hypotheses that interneurons do integrate these sensory inputs to control behavior. Here, a microfluidic platform that can easily deliver spatially and temporally controlled combination stimuli to C. elegans is presented. With this platform, both sensory and interneuron activity is measured in response to mechanical and chemical stimulations in a quantitative and high-throughput manner. It is found that the activity of command interneuron PVC can be modulated by prior stimulation both within the same and across different modalities. The roles of monoaminergic and peptidergic signaling are further examined on the process of multimodal integration through PVC activity. The approach exemplified here is envisioned to be broadly applicable in different contexts to elucidate underlying mechanisms and identify genes affecting multisensory integration.
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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".