Early social deprivation shapes neuronal programming of the social decision‐making network in a cooperatively breeding fish
Bibliographic record
Abstract
The early social environment an animal experiences may have pervasive effects on its behaviour. The social decision-making network (SDMN), consisting of interconnected brain nuclei from the forebrain and midbrain, is involved in the regulation of behaviours during social interactions. In species with advanced sociality such as cooperative breeders, offspring are exposed to a large number and a great diversity of social interactions every day of their early life. This diverse social environment may have life-long consequences on the development of several neurophysiological systems within the SDMN, although these effects are largely unknown. We studied these life-long effects in a cooperatively breeding fish, Neolamprologus pulcher, focusing on the expression of genes involved in the monoaminergic and stress response systems in the SDMN. N. pulcher fry were raised until an age of 2 months either with their parents, subordinate helpers and same-clutch siblings (+F), or with same-clutch siblings only (-F). Analysis of the expression of glucocorticoid receptor, mineralocorticoid receptor, corticotropin releasing factor, dopamine receptors 1 and 2, serotonin transporter and DNA methyltransferase 1 genes showed that early social experiences altered the neurogenomic profile of the preoptic area. Moreover, the dopamine receptor 1 gene was up-regulated in the preoptic area of -F fish compared to +F fish. -F fish also showed up-regulation of GR1 expression in the dorsal medial telencephalon (functional equivalent to the basolateral amygdala), and in the dorsolateral telencephalon (functional equivalent to the hippocampus). Our results suggest that early social environment has life-long effects on the development of several neurophysiological systems within the SDMN.
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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 | 0.000 |
| 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".