Bibliographic record
Abstract
An in vivo preparation has been developed to study the mechanisms underlying spontaneous sleep oscillations. Dual and triple simultaneous intracellular recordings were made from neurons in small isolated cortical slabs (10 mm x 6 mm) in anesthetized cats. Spontaneously occurring slow sleep oscillations, present in the adjacent intact cortex, were absent in small slabs. However, the isolated slabs displayed brief active periods separated by long periods of silence, up to 60 s in duration. During these silent periods, 60% of neurons showed non-linear amplification of low-amplitude depolarizing activity. Nearly 40% of the cells, twice as many as in intact cortex, were classified as intrinsically bursting. In cortical network models based on Hodgkin-Huxley-like neurons, the summation of simulated spontaneous miniature excitatory postsynaptic potentials was sufficient to activate a persistent sodium current, initiating action potentials in single neurons that then spread through the network. Consistent with this model, enlarging the isolated cortical territory to an isolated gyrus (30 mm x 20 mm) increased the probability of initiating large-scale activity. In these larger territories, both the frequency and regularity of the slow oscillation approached that generated in intact cortex. The frequency of active periods in an analytical model of the cortical network accurately predicted the scaling observed in simulations and from recordings in cortical slabs of increasing size.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".