Synaptic homeostasis transiently leverages Hebbian mechanisms for a multiphasic response to inactivity
Bibliographic record
Abstract
Summary Neurons use various forms of negative feedback to maintain their synaptic strengths within an operationally useful range. While this homeostatic plasticity is thought to distinctly counteract the destabilizing positive feedback of Hebbian plasticity, there is considerable overlap in the molecular components mediating both forms of plasticity. The varying kinetics of these components spurs additional inquiry into the dynamics of synaptic homeostasis. We discovered that upscaling of synaptic weights in response to prolonged inactivity is nonmonotonic. Surprisingly, this seemingly oscillatory adaptation involved transient appropriation of molecular effectors associated with Hebbian plasticity, namely CaMKII, L-type Ca 2+ channels, and Ca 2+ -permeable AMPARs, and homeostatic elements such as calcineurin. We created a dynamic model that shows how traditionally “Hebbian” and “homeostatic” mechanisms can cooperate to autoregulate postsynaptic Ca 2+ levels. We propose that this combination of mechanisms allows excitatory synapses to adapt to prolonged activity changes and safeguard the capability to undergo future strengthening on demand.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".