Thalamic Influence Over Adaptive Cortical Dynamics Across Conscious States
Bibliographic record
Abstract
Summary The human brain must support both stable and flexible neural dynamics in order to adapt to changing contexts that are inherently non-linear. The thalamus has been linked to the coordination of these opposing dynamical regimens in the cerebral cortex, however existing methodological approaches have not integrated sufficient neurobiological details with a sensitive measure of neural dynamics that permits sensitivity to time-series non-linearities. Inspired by the field of fluid dynamics, we use a novel approach to show that spontaneous fMRI data exhibits non-trivial fluctuations in predictability over time, akin to a river that has sections of smooth and predictable (laminar) versus rough and unpredictable (non-laminar) fluid flow. We use a combination of pharmacological fMRI, macaque electrophysiology and a large-scale biophysical model of the thalamocortical system to provide robust evidence that the thalamus provides versatile control over globally linear dynamics in the cerebral cortex that characterize conscious states.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".