Homeostatic coordination and up-regulation of neural activity by activity-dependent myelination
Bibliographic record
Abstract
This repository contains the custom algorithms developed and used to generate the results we report in our study. The resulting data, used to generate figures can also be found below. Please read the file README.txt for details on how to use the codes and how the data is organized. Manuscript title: Homeostatic coordination and up-regulation of neural activity by activity-dependent myelination Manuscript abstract: Activity-dependent myelination (ADM) is the mechanism by which myelin changes as a function of neural activity, and is fundamental in brain plasticity. Mediated by structural changes in glia, ADM notably regulates axonal conduction velocity. It remains unclear how neural activity impacts myelination to orchestrate the timing of neural signaling, and how ADM shapes neural activity. We developed a model of spiking neurons enhanced with neuron-oligodendrocyte feedback. We modeled the effect of ADM plasticity on conduction velocity and examined its influence on neural activity. We found that ADM implements a homeostatic gain control mechanism that enhances firing rates and correlations in neural activity through the temporal coordination of action potentials. Stimuli interact with ADM plasticity to trigger bidirectional and reversible changes in conduction delays as may occur during learning. Furthermore, ADM-mediated coordination of action potentials enhances information transmission. These results highlight the role of ADM in shaping neural activity and communication.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.035 |
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".