Data from: Texas field crickets (Gryllus texensis) use visual cues to place learn but perform poorly when intra- and extra-maze cues conflict
Bibliographic record
Abstract
Central place foraging field crickets are an ideal system for studying the adaptive value of learning and memory, but more research is needed on ecology-relevant cognition in these invertebrates. Here, we test the visuospatial place learning of Texas field crickets (Gryllus texensis) in a radial arm maze. Our study expands previous work on G. texensis cognition for accuracy measures and extends our previous findings on females to both sexes. Additionally, our study examines whether crickets use intra- or extra-maze cues to locate a food reward using a maze rotation putting the cues in conflict. We found that male and female crickets improved performance over trials when measured by accuracy variables but not latency variables; thigmotaxis negatively impacted performance in both sexes. In a reward-absent trial, both male and female crickets demonstrated place memory. When intra- and extra-maze cues conflicted during a rotation trial, crickets' performance was not better than chance. Our rotation results suggest that crickets may experience reciprocal overshadowing of conflicting cues – a result most often seen in other taxa with conflicting multi-modal cues. We conclude that crickets do not rely solely on: (1) a single-cue association; (2) route-following; or (3) their own scent cues to navigate the maze. Instead, male and female Texas field crickets seem to learn the location of the reward using a combination of proximal and distal cues. The possibility to test large numbers of wild-caught or laboratory-reared individuals opens the door to future investigations on the evolutionary ecology of visuospatial learning in these invertebrates.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".