The complexity of high-frequency electric fields degrades electrosensory inputs: implications for the jamming avoidance response in weakly electric fish
Bibliographic record
Abstract
Sensory systems encode environmental information that is necessary for adaptive behavioural choices, and thus greatly influence the evolution of animal behaviour and the underlying neural circuits. Here, we evaluate how the quality of sensory information impacts the jamming avoidance response (JAR) in weakly electric fish. To sense their environment, these fish generate an oscillating electric field: the electric organ discharge (EOD). Nearby fish with similar EOD frequencies perform the JAR to increase the difference between their EOD frequencies, i.e. their difference frequency (DF). The fish determines the sign of the DF: when it has a lower frequency (DF > 0), EOD frequency is decreased and vice versa . We study the sensory basis of the JAR in two species: Apteronotus leptorhynchus have a high frequency ( ca 1000 Hz), spatio-temporally heterogeneous electric field, whereas Eigenmannia sp. have a low frequency ( ca 300 Hz), spatially uniform field. We show that the increased complexity of the Apteronotus field decreases the reliability of sensory cues used to determine the DF. Interestingly, Apteronotus responds to all JAR stimuli by increasing EOD frequency, having lost the neural pathway that produces JAR-related decreases in EOD frequency. Our results suggest that electric field complexity may have influenced the evolution of the JAR by degrading the related sensory information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".