The dynamic relationship of brain‐derived neurotrophic factor and oxytocin: Introducing the concept of neurosocial plasticity
Bibliographic record
Abstract
The human brain functions as a highly integrated system. Interconnected cellular and molecular networks within this system process sensory information, cognitive functions, and motor responses. The brain also exhibits a remarkable potential for plasticity-driven adaptive learning and memory. Importantly, neuroplasticity serves as a key mechanism of neuroprotection while also enabling the brain to compensate for injury through adaptive structural remodeling. Understanding the brain as a dynamic system requires examining how its components interact to produce adaptive physiological responses and complex behaviors, such as social interactions. Key molecules, such as brain-derived neurotrophic factor (BDNF) and oxytocin (OT), play pivotal roles in maintaining the brain's dynamic complexity and integrative functioning. In this review, we introduce the concept of "neurosocial plasticity", which refers to the brain's ability to adapt both neural circuitry and social behavior through the dynamic interaction between BDNF and OT. This concept highlights how BDNF-OT interactions may support both neural plasticity and the capacity for adaptive social functioning. We then explore how their co-localization, co-expression, and co-regulation may regulate neural and social plasticity, ultimately shaping the brain's adaptability and the development of social behaviors across various contexts.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".