Against vivisection: Charcot and Pitres’ discovery of the human motor cortex and the birth of modern neurosurgery and of the surgical treatment of epilepsy
Bibliographic record
Abstract
This article addresses the discrepancy between Edouard Hitzig's and David Ferrier's findings on the cortical localization of movements in animals and Jean-Martin Charcot's findings in humans. The results of Hitzig's and Ferrier's vivisections were criticized by experimentalists in England and France as discordant, irreproducible, and inconclusive, and they were rejected by clinicians as irrelevant. Charcot addressed the gap between animal and human motor function by correlating motor deficits and focal epileptic seizures in patients to their autopsy findings. By this method he discovered the functional organization of the human motor cortex and produced the first accurate human motor brain map. Ferrier, William Osler, and Hughlings Jackson acknowledged Charcot's findings, and his findings guided the first neurosurgeons in localizing and resecting intracranial mass lesions presenting with focal epileptic seizures. Although his contributions in these fields have been neglected by modern historians, Charcot made significant contributions to the neurobiology of the human motor system, to epileptology, and to the birth of modern neurosurgery.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.032 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 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".