Probing hippocampal stimulation in experimental temporal lobe epilepsy with functional MRI
Bibliographic record
Abstract
Electrical neurostimulation is currently used to manage epilepsy, but the most effective approach for minimizing seizure occurrence is uncertain. While functional MRI (fMRI) can reveal which brain areas are affected by stimulation, simultaneous deep brain stimulation (DBS)-fMRI examinations in patients are rare and the possibility to investigate multiple stimulation protocols is limited. In this study, we utilized the intrahippocampal kainate mouse model of mesial temporal lobe epilepsy (mTLE) to systematically examine the brain-wide responses to electrical stimulation using fMRI. We compared fMRI responses of saline-injected controls and epileptic mice during stimulation in the septal hippocampus (HC) at 10 Hz and demonstrated the effects of different stimulation amplitudes (80-230 μA) and frequencies (1-100 Hz) in epileptic mice. Motivated by recent studies exploring 1 Hz stimulation to prevent epileptic seizures, we furthermore investigated the effect of prolonged 1 Hz stimulation with fMRI. Compared to sham controls, epileptic mice showed less propagation to the contralateral HC, but significantly stronger responses in the ipsilateral HC and a wider spread to the entorhinal cortex and septal region. Varying the stimulation amplitude had little effect on the resulting activation patterns, whereas the stimulation frequency represented the key parameter and determined whether the induced activation remained local or spread from the hippocampal formation into cortical areas. Prolonged stimulation of epileptic mice at 1 Hz caused a slight reduction in local excitability. In this way, our study contributes to a better understanding of these stimulation paradigms.
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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 | 0.001 |
| 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".