Social Complexity During Early Development has Long‐Term Effects on Neuroplasticity in the Social Decision‐Making Network
Bibliographic record
Abstract
In social species, early social experience shapes the development of appropriate social behaviours during conspecific interactions referred to as social competence. However, the underlying neuronal mechanisms responsible for the acquisition of social competence are largely unknown. A key candidate to influence social competence is neuroplasticity, which functions to restructure neural networks in response to novel experiences or alterations of the environment. One important mediator of this restructuring is the neurotrophin BDNF, which is well conserved among vertebrates. We studied the highly social fish Neolamprologus pulcher, in which the impact of early social experience on social competence has been previously shown. We investigated experimentally how variation in the early social environment impacts markers of neuroplasticity by analysing the relative expression of the bdnf gene and its receptors p75NTR and TrkB across nodes of the social decision-making network. In fish raised in larger groups, bdnf and TrkB were upregulated in the anterior tuberal nucleus, compared to fish raised in smaller groups, while TrkB was downregulated and bdnf was upregulated in the lateral part of the dorsal telencephalon. In the preoptic area (POA), all three genes were upregulated in fish raised in large groups, suggesting that early social experiences might lead to changes of the neuronal connectivity in the POA. Our results highlight the importance of early social experience in programming the constitutive expression of neuroplasticity markers, suggesting that the effects of early social experience on social competence might be due to changes in neuroplasticity.
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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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".