A Tale of Two Brains- Cortical localization and neurophysiology in the 19th and 20th century
Bibliographic record
Abstract
Introduction: Other authors have well described the importance of experimental physiology in the development of brain sciences and the individual discoveries of the founding fathers of modern neurology. Here is discussed the birth of neurological sciences in the 19th and 20th century and their epistemological origins.Discussion: In the span of two hundred years, we saw the emergence of two different brains: the neuroanatomical brain, exemplified by cortical localization and the anatomo-clinical approach pioneered by Jean-Martin Charcot, and the neurophysiological brain, exemplified by Santiago Ramon y Cajal’s neuron doctrine and pre-modern electrophysiology. We can distinguish between brain function, understood as the attribution of physiological functions to discrete anatomical structures, and brain functioning, understood as an approach to nervous system functioning and physiology that emphasizes mechanisms.Conclusion: In the 19th and 20th century, the brain became an organ with a physiology that could be understood. However, we saw the development of two different conceptions of the brain, which continue to influence neurological sciences to this day.Relevance: With modern cognitive neuroscience, functional neuroanatomy, cellular and molecular neurophysiology and neural networks, neurological sciences all have different analytical units, which are tributaries of the 19th and 20th century development of the neuroanatomical and neurophysiological brains.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".