Homeostatic plasticity in patients with disorders of consciousness detected by combined stimulation: a study protocol
Bibliographic record
Abstract
Background: Non-invasive neuromodulation (NIN) techniques have been widely utilized in treating patients with disorders of consciousness (DoC), but their therapeutic effects have been inconsistent. Given the reliance of NIN techniques on synaptic plasticity, and the potential impairment of synaptic plasticity (particularly homeostatic plasticity) resulting from severe brain injury, it is possible that the variation in therapeutic effects is due to alterations in homeostatic plasticity in patients with DoC. Therefore, this study will use preconditioning TMS to examine the retention of homeostatic plasticity in patients with DoC. Methods: We will enroll 30 patients with DoC and 15 healthy controls and randomize the order of their sessions. According to the priming protocol, the trial was divided into three different sessions with a 2-day break between each session. The session will involve a 10-min duration of transcranial direct current stimulation (tDCS) priming, followed by a 192-s period of transcranial magnetic stimulation (TMS) test. Transcranial stimulation will be specifically targeted toward the left primary motor cortex. Measurements of motor evoked potentials will be taken at several time points: baseline, after tDCS, and after TMS. Coma Recovery Scale-Revised will be conducted both baseline and after TMS. Discussion: Studying whether homeostatic plasticity is preserved in patients with DoC is beneficial for gaining a better understanding of their brain condition. If the homeostatic plasticity of patients with DoC is impaired, then NIN, which are based on altering synaptic plasticity in healthy individuals to achieve stimulating effects, may not be directly translatable to the therapeutic interventions for patients with DoC. Instead, the homeostatic plasticity of patients should be restored before implementing the intervention.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".