Enhanced <i>I</i><sub>h</sub> Depresses Rat Entopeduncular Nucleus Neuronal Activity From High-Frequency Stimulation or Raised K<sub>e</sub><sup>+</sup>
Bibliographic record
Abstract
High-frequency stimulation (HFS) is used to treat a variety of neurological diseases, yet its underlying therapeutic action is not fully elucidated. Previously, we reported that HFS-induced elevation in [K(+)](e) or bath perfusion of raised K(e)(+) depressed rat entopeduncular nucleus (EP) neuronal activity via an enhancement of an ionic conductance leading to marked depolarization. Herein, we show that the hyperpolarization-activated (I(h)) channel mediates the HFS- or K(+)-induced depression of EP neuronal activity. The perfusion of an I(h) channel inhibitor, 50 microM ZD7288 or 2 mM CsCl, increased input resistance by 23.5 +/- 7% (ZD7288) or 35 +/- 10% (CsCl), hyperpolarized cells by 3.4 +/- 1.7 mV (ZD7288) or 2.3 +/- 0.9 mV (CsCl), and decreased spontaneous action potential (AP) frequency by 51.5 +/- 12.5% (ZD7288) or 80 +/- 13.5% (CsCl). The I(h) sag was absent with either treatment, suggesting a block of I(h) channel activity. Inhibition of the I(h) channel prior to HFS or 6 mM K(+) perfusion not only prevented the previously observed decrease in AP frequency, but increased neuronal activity. Under voltage-clamp conditions, I(h) currents were enhanced in the presence of 6 mM K(+). Calcium is also involved in the depression of EP neuronal activity, since its removal during raised K(e)(+) application prevented this attenuation and blocked the I(h) sag. We conclude that the enhancement of I(h) channel activity initiates the HFS- and K(+)-induced depression of EP neuronal activity. This mechanism could underlie the inhibitory effects of HFS used in deep brain stimulation in output basal ganglia nuclei.
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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 | 0.001 |
| 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".