Call‐specific patterns of neural activation in auditory processing of Richardson’s ground squirrel alarm calls
Bibliographic record
Abstract
INTRODUCTION: Richardson's ground squirrels use alarm calls to warn conspecifics about potential predatory threats. Chirp calls typically indicate high levels of threat from airborne predators, while whistle calls are associated with lower levels of threat from terrestrial predators. These types of calls primarily elicit escape behaviors and increased vigilance in receivers, respectively. While much is known about the neural mechanisms involved in the production of vocalizations, less is known about the mechanisms important for the perception of alarm calls by receivers, and whether changes in perceived risk are associated with unique patterns of neuronal activation. Thus, to determine whether alarm calls associated with different levels of predation risk result in differential neuronal activation, we used immunohistochemistry to identify and quantify c-Fos immunopositive cells in brain regions important in stress, fear, danger, and reward, following alarm call reception. METHODS: We exposed 29 female Richardson's ground squirrels (10 control, 10 whistle receivers, and 9 chirp receivers) to playbacks of whistles, chirps, or a no-vocalization control. We then assessed neuronal activation via c-Fos immunohistochemistry in 12 brain regions. RESULTS: Ground squirrels receiving high-threat "chirp" vocalizations had reduced neuronal activation in the medial amygdala and superior colliculus compared with controls. It is likely that changes in activity in these brain regions serve to alter the balance between approach and avoidance in turn promoting escape behaviors. CONCLUSIONS: Thus, we conclude that in Richardson's ground squirrels, these brain regions are important for the perception of risk resulting from receiving alarm calls and allow for appropriate behavioral responses by receivers.
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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 | 0.000 | 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) | 0.000 | 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".