Back

Cellular mechanisms underlying social regulation of the posterior tubercular nucleus in zebrafish (Danio rerio)

Adams, C. L.; Scott, E.; Issa, F. A.

2026-01-29 neuroscience
10.64898/2026.01.27.701991 bioRxiv
Show abstract

Social status profoundly influences animal behavior through neural plasticity, yet the cellular mechanisms that mediate reconfiguration of neuromodulatory systems remain poorly understood. Here, we investigated status-dependent structural changes in the posterior tubercular nucleus (PTN) of adult zebrafish. Animals were assigned to four social conditions: communal, isolated, dominant, or subordinate. Using markers for cell proliferation (PCNA) and birth-dating (BrdU), we demonstrate that social dominance significantly enhances neurogenesis, leading to an increased population of PTN dopaminergic neurons. In contrast, subordinate and isolated fish exhibited suppressed neurogenesis and elevated expression of superoxide dismutase 1 (SOD1), suggesting that chronic social stress induces an oxidative burden that may lead to neuronal loss. Furthermore, we identified evidence of neurotransmitter phenotypic plasticity; subordinate fish displayed a significantly higher ratio of glutamatergic (vglut2a) to dopaminergic (dat) expression in PTN neurons compared to dominants, suggesting a status-dependent shift in neuromodulatory identity. Multivariate principal component analysis further revealed distinct neurobiological profiles that separate social ranks, suggesting that status-dependent plasticity is a coordinated multi-modal response. Collectively, our results improve our understanding of how social experience reshapes the zebrafish brain through integrated changes in cell proliferation, cellular shift in cellular identity and regulation of cellular viability; thus, providing a potential mechanism for the maintenance of stable behavioral phenotypes in competitive social environments.

Published in Frontiers in Neural Circuits (predicted rank #5) · training set

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.