Moderate Cortical Cooling Eliminates Thalamocortical Silent States during Slow Oscillation
Bibliographic record
Abstract
Reduction in temperature depolarizes neurons by a partial closure of potassium channels but decreases the vesicle release probability within synapses. Compared with cooling, neuromodulators produce qualitatively similar effects on intrinsic neuronal properties and synapses in the cortex. We used this similarity of neuronal action in ketamine-xylazine-anesthetized mice and non-anesthetized mice to manipulate the thalamocortical activity. We recorded cortical electroencephalogram/local field potential (LFP) activity and intracellular activities from the somatosensory thalamus in control conditions, during cortical cooling and on rewarming. In the deeply anesthetized mice, moderate cortical cooling was characterized by reversible disruption of the thalamocortical slow-wave pattern rhythmicity and the appearance of fast LFP spikes, with frequencies ranging from 6 to 9 Hz. These LFP spikes were correlated with the rhythmic IPSP activities recorded within the thalamic ventral posterior medial neurons and with depolarizing events in the posterior nucleus neurons. Similar cooling of the cortex during light anesthesia rapidly and reversibly eliminated thalamocortical silent states and evoked thalamocortical persistent activity; conversely, mild heating increased thalamocortical slow-wave rhythmicity. In the non-anesthetized head-restrained mice, cooling also prevented the generation of thalamocortical silent states. We conclude that moderate cortical cooling might be used to manipulate slow-wave network activity and induce neuromodulator-independent transition to activated states. Significance statement: In this study, we demonstrate that moderate local cortical cooling of lightly anesthetized or naturally sleeping mice disrupts thalamocortical slow oscillation and induces the activated local field potential pattern. Mild heating has the opposite effect; it increases the rhythmicity of thalamocortical slow oscillation. Our results demonstrate that slow oscillation can be influenced by manipulations to the properties of cortical neurons without changes in neuromodulation.
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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) | 0.001 | 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 | 0.001 |
| 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".