Psychomotor seizures, Penfield, Gibbs, Bailey and the development of anterior temporal lobectomy: A historical vignette
Bibliographic record
Abstract
Psychomotor seizures, referred to as limbic or partial complex seizures, have had an interesting evolution in diagnosis and treatment. Hughlings Jackson was the first to clearly relate the clinical syndrome and likely etiology to lesions in the uncinate region of the medial temporal lobe. With the application of electroencephalography (EEG) to the study of human epilepsy as early as 1934 by Gibbs, Lennox, and Davis in Boston, electrical recordings have significantly advanced the study of epilepsy. In 1937, Gibbs and Lennox proposed the term "psychomotor epilepsy" to describe a characteristic EEG pattern of seizures accompanied by mental, emotional, motor, and autonomic phenomena. Concurrently, typical psychomotor auras and dreamy states were produced by electrical stimulation of medial temporal structures during epilepsy surgery by Penfield in Montreal. In 1937, Jasper joined Penfield, EEG was introduced and negative surgical explorations became less frequent. Nevertheless, Penfield preferred to operate only on space occupying lesions. A milestone in psychomotor seizure diagnosis was in the year 1946 when Gibbs, at the Illinois Neuropsychiatric Institute, Chicago, reported that the patient falling asleep during EEG was a major activator of the psychomotor discharges and electrographic ictal episodes becoming more prominently recorded. Working with Percival Bailey, Gibbs was proactive in applying EEG to define surgical excision of the focus in patients with intractable psychomotor seizures. By early 1950s, the Montreal group began to clearly delineate causative medial temporal lesions such as hippocampal sclerosis and tumors in the production of psychomotor seizures.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".