Stimulation of the human cortex and the experience of pain: Wilder Penfield's observations revisited
Bibliographic record
Abstract
Thanks to the seminal work of Wilder Graves Penfield (1891-1976) at the Montreal Neurological Institute, electrical stimulation is used worldwide to localize the epileptogenic cortex and to map the functionally eloquent areas in the context of epilepsy surgery or lesion resections. In the functional map of elementary and experiential responses he described through >20 years of careful exploration of the human cortex via stimulation of the cortical surface, Penfield did not identify any 'pain cortical area'. We reinvestigated this issue by analysing subjective and videotaped behavioural responses to 4160 cortical stimulations using intracerebral electrodes implanted in all cortical lobes that were carried out over 12 years during the presurgical evaluation of epilepsy in 164 consecutive patients. Pain responses were scarce (1.4%) and concentrated in the medial part of the parietal operculum and neighbouring posterior insula where pain thresholds showed a rostrocaudal decrement. This deep cortical region remained largely inaccessible to the intraoperative stimulation of the cortical surface carried out by Penfield after resection of the parietal operculum. It differs also from primary sensory areas described by Penfield et al. in the sense that, with our stimulation paradigm, pain represented only 10% of responses. Like Penfield et al., we obtained no pain response anywhere else in the cortex, including in regions consistently activated by pain in most functional imaging studies, i.e. the first somatosensory area, the lateral part of the secondary somatosensory area, anterior and mid-cingulate gyri (mid-cingulate cortex), anterior frontal, posterior parietal and supplementary motor areas. The medial parietal operculum and posterior insula are thus the only areas where electrical stimulation is able to trigger activation of the pain cortical network and thus the experience of somatic pain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".