Pedigrees of Neurobehavioral Circuits: Tracing the Evolution of Novel Behaviors by Comparing Motor Patterns, Muscles, and Neurons in Members of Related Taxa
Bibliographic record
Abstract
Comparisons of homologous elements in neurobehavioral circuits that have diverged during speciation to mediate different behaviors should reveal the nature of evolutionary changes in nervous systems. When the pedigree of a particular behavior can be traced-by comparing motor patterns and their neural substrates in related taxa whose phylogeny is known from other (non-neurobehavioral) criteria-divergent and convergent evolutionary changes can be distinguished and the order of their occurrence reconstructed. An example of reconstructing a behavioral pedigree (for the novel mode of swimming in the crab Emerita [Hippidae]) is presented, and implications about the evolution and organization of neurobehavioral circuits engendered by this and some other studies of functionally defined neuronal networks are reviewed. Specific neural differences in related animals can only be attributed to natural selection when they can be related to species differences in function or behavior. Differences that cannot be so related, as well as apparently non-adaptive characters in individual nervous systems, are attributed to ontogenetic processes, which apparently, in some cases, introduced and, in other cases, resisted change through evolutionary time. More expressly-comparative investigations of discrete neurobehavioral circuits are needed for an understanding of the interdependence of evolutionary processes and ontogenetic and functional constraints on the organization of neuronal systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".