Spiking-Bursting Activity in the Thalamic Reticular Nucleus Initiates Sequences of Spindle Oscillations in Thalamic Networks
Bibliographic record
Abstract
Recent intracellular and local field potential recordings from thalamic reticular (RE) neurons in vivo as well as computational modeling of the isolated RE nucleus suggest that, at relatively hyperpolarized levels of membrane potentials, the inhibitory postsynaptic potentials (IPSPs) between RE cells can be reversed and gamma-aminobutyric acid-A (GABA(A)) -mediated depolarization can generate persistent spatio-temporal patterns in the RE nucleus. Here we investigate how this activity affects the spatio-temporal properties of spindle oscillations with computer models of interacting RE and thalamocortical (TC) cells. In a one-dimensional network of RE and TC cells, sequences of spindle oscillations alternated with localized patterns of spike-burst activity propagating inside the RE network. New sequences of spindle oscillations were initiated after removal of I(h)-mediated depolarization of the TC cells. The length of the interspindle lulls depended on the intrinsic and synaptic properties of RE and TC cells and was in the range of 3-20 s. In a two-dimensional model, GABA(A)-mediated 2-3 Hz oscillations persisted in the RE nucleus during interspindle lulls and initiated spindle sequences at many foci within the RE-TC network simultaneously. This model predicts that the intrinsic properties of the reticular thalamus may contribute to the synchrony of spindle oscillations observed in vivo.
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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 | 0.000 |
| 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".