Divergent Synaptic Scaling of Miniature EPSCs following Activity Blockade in Dissociated Neuronal Cultures
Bibliographic record
Abstract
Neurons can respond to decreased network activity with a homeostatic increase in the amplitudes of miniature EPSCs (mEPSCs). The prevailing view is that mEPSC amplitudes are uniformly multiplied by a single factor, termed “synaptic scaling.” Deviations from purely multiplicative scaling have been attributed to biological differences, or to a distortion imposed by a detection threshold limit. Here, we demonstrate in neurons dissociated from cortices of male and female mice that the shift in mEPSC amplitudes observed in the experimental data cannot be reproduced by simulation of uniform multiplicative scaling, with or without the distortion caused by applying a detection threshold. Furthermore, we demonstrate explicitly that the scaling factor is not uniform but is close to 1 for small mEPSCs, and increases with increasing mEPSC amplitude across a substantial portion of the data. This pattern was also observed for previously published data from dissociated mouse hippocampal neurons and dissociated rat cortical neurons. The finding of “divergent scaling” shifts the current view of homeostatic plasticity as a process that alters all synapses on a neuron equally to one that must accommodate the differential effect observed for small versus large mEPSCs. Divergent scaling still accomplishes the essential homeostatic task of modifying synaptic strengths in the opposite direction of the activity change, but the consequences are greatest for those synapses which individually are more likely to bring a neuron to threshold. SIGNIFICANCE STATEMENTIn homeostatic plasticity, the responses to chronic increases or decreases in network activity act in the opposite direction to restore normal activity levels. Homeostatic plasticity is likely to play a role in diseases associated with long-term changes in brain function, such as epilepsy and neuropsychiatric illnesses. One homeostatic response is the increase in synaptic strength following a chronic block of activity. Research is focused on finding a globally expressed signaling pathway, because it has been proposed that the plasticity is uniformly expressed across all synapses. Here, we show that the plasticity is not uniform. Our work suggests that homeostatic signaling molecules are likely to be differentially expressed across synapses.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".