Global Intracellular Slow-Wave Dynamics of the Thalamocortical System
Bibliographic record
Abstract
It is widely accepted that corticothalamic neurons recruit the thalamus in slow oscillation, but global slow-wave thalamocortical dynamics have never been experimentally shown. We analyzed intracellular activities of neurons either from different cortical areas or from a variety of specific and nonspecific thalamic nuclei in relation to the phase of global EEG signal in ketamine-xylazine anesthetized mice. We found that, on average, slow-wave active states started off within frontal cortical areas as well as higher-order and intralaminar thalamus (posterior and parafascicular nuclei) simultaneously. Then, the leading edge of active states propagated in the anteroposterior/lateral direction over the cortex at ∼40 mm/s. The latest structure we recorded within the slow-wave cycle was the anterior thalamus, which followed active states of the retrosplenial cortex. Active states from different cortical areas tended to terminate simultaneously. Sensory thalamic ventral posterior medial and lateral geniculate nuclei followed cortical active states with major inhibitory and weak tonic-like "modulator" EPSPs. In these nuclei, sharp-rising, large-amplitude EPSPs ("drivers") were not modulated by cortical slow waves, suggesting their origin in ascending pathways. The thalamic active states in other investigated nuclei were composed of depolarization: some revealing "driver"- and "modulator"-like EPSPs, others showing "modulator"-like EPSPs only. We conclude that sensory thalamic nuclei follow the propagating cortical waves, whereas neurons from higher-order thalamic nuclei display "hub dynamics" and thus may contribute to the generation of cortical slow waves.
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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) | 0.001 | 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".