Variations in touch representation in the hummingbird and zebra finch forebrain
Bibliographic record
Abstract
Somatosensation is essential for animals to perceive the external world through touch, allowing them to detect physical contact, temperature, pain, and body position. Studies on rodent vibrissae have highlighted the organization and processing in mammalian somatosensory pathways. 1 , 2 Comparative research across vertebrates is vital for understanding evolutionary influences and ecological specialization on somatosensory systems. Birds, with their diverse morphologies, sensory abilities, and behaviors, serve as ideal models for investigating the evolution of somatosensation. Prior studies have uncovered tactile-responsive areas within the avian telencephalon, particularly in pigeons, 3 , 4 , 5 , 6 parrots, 7 and finches, 8 but variations in somatosensory maps and responses across avian species are not fully understood. This study aims to explore somatotopic organization and neural coding in the telencephalon of Anna's hummingbirds ( Calypte anna ) and zebra finches ( Taeniopygia guttata ) by using in vivo extracellular electrophysiology to record activity in response to controlled tactile stimuli on various body regions. These findings reveal unique representations of body regions across distinct forebrain somatosensory nuclei, indicating significant differences in the extent of areas dedicated to certain body surfaces, which may correlate with their behavioral importance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".