Clinical Electrophysiology of the Upper and Lower Motor Neuron in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Electrophysiology is important in amyotrophic lateral sclerosis (ALS). It helps in the assessment of disease severity and rate of progression, and it plays a role in evaluating the efficacy of therapeutic trials. Presently, electrophysiology is the only means of confirming suspected ALS, and this has been incorporated into the El Escorial criteria. Needle electromyography identifies disease in clinically "unaffected muscles" including bulbar musculature, confirms involvement of anterior horn cells, and can detect early involvement of respiratory muscles (intercostals and diaphragm). Conduction studies are imperative to rule out motor neuropathy with multifocal conduction block. Various techniques (cortical threshold, cortical silent period, double stimulation) employing transcranial magnetic stimulation have demonstrated that the motor cortex in ALS is hyperexcitable. Central motor conduction is normal in ALS but uniquely slow in the D9OA SOD1 mutation. Using peristimulus time histograms (PSTHs) it is possible to estimate the size of a unitary excitatory postsynaptic potential (EPSP). In ALS the EPSP is typically desynchronized. With time it becomes reduced in amplitude and a slow conducting component becomes recognizable in the primary peak of the PSTH. This reflects conduction through a slow motor pathway. Abnormalities of the PSTH are not seen in Kennedy's disease, implying that the changes seen in ALS are due to supraspinal mechanisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".