Behavioral Attributes of Social Groups Determine the Strength and Direction of Selection on Neural Investment
Bibliographic record
Abstract
The evolution of social systems can place novel selective forces on investment in expensive neural tissue by changing cognitive demands. Previous hypotheses about the impact of sociality on neural investment have received equivocal support when tested across diverse taxonomic groups and social structures. We suggest previous models for social behavior-brain relationships have overlooked important variation in social groups. Social groups vary significantly in structure and function, and the specific attributes of a social group may be more relevant to setting cognitive demands than sociality in general. We have identified intragroup competition, relationship differentiation, information sharing, dominance hierarchies, and task specialization and redundancy as attributes of social behavior which may impact selection for neural investment, and outline how variation in these attributes can result in increased or decreased neural investment with transitions to sociality in different taxa. Finally, we test some of the predictions generated using this framework in a phylogenetic comparison of neural tissue investment in Anelosimus social spiders. Social Anelosimus spiders engage in cooperative prey capture and brood care, which allows for individual redundancy in the completion of these tasks. We hypothesized that in social spider species, the presence of redundancy would reduce selection for individual neural investment relative to subsocial species. We found that social species had significantly decreased investment in the arcuate body, the cognitive center of the spider brain, supporting our predictions. Future comparative tests of brain evolution in social species should account for the special behavioral characteristics that accompany social groups in the subject taxa.
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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".