Stress-induced neuronal hypertrophy decreases the intrinsic excitability in stress habituation
Bibliographic record
Abstract
Abstract A rapid activation of the hypothalamic-pituitary-adrenal (HPA) axis is a hallmark stress response to an imminent threat, but its chronic activation can be detrimental. Thus, the long-term survival of animals requires experience-dependent fine-tuning of the stress response. However, the cellular mechanisms underlying the ability to decrease the stress responsiveness of the HPA axis remain largely unsolved. Using a stress habituation model in male mice and slice patch-clamp electrophysiology, we studied hypothalamic corticotropin-releasing hormone neurons that form the apex of the HPA axis. We found that the intrinsic excitability of these neurons substantially decreased after daily repeated restraint stress in a time course that coincided with their loss of stress responsiveness in vivo . This plasticity of intrinsic excitability co-developed with an expansion of surface membrane area, resulting in an increase in input conductance with minimal changes in conductance density. Moreover, multi-photon and electron microcopy data found that repeated stress augmented ruffling of the plasma membrane, suggesting an ultrastructural plasticity that efficiently accommodates membrane area expansion with proportionally less expansion of gross cell volume. Overall, we report a novel structure-function relationship for intrinsic excitability plasticity that correlates with habituation of the neuroendocrine stress response. Significance statement The long-term survival of animals requires experience-dependent fine-tuning of stress response. Using a mouse model of repeated stress that develops habituation of the hypothalamic-pituitary-adrenal (HPA) axis, our study demonstrates a robust decrease in the intrinsic excitability of the output neuroendocrine neurons of the HPA axis. Mechanistically, we show that repeated stress increases the cell size of these neurons (i.e. surface membrane area). This cell-size change increases input conductance, and hence decreases excitability. Our findings challenge a conventional view that plasticity of intrinsic excitability relies on changes on membrane excitability resulting from up- and down-regulation of various voltage-gated ion channels. Our study reports a novel structure-function relationship for intrinsic excitability plasticity that correlates with habituation of the neuroendocrine stress response.
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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".