Selective plasticity of hippocampal GABAergic interneuron populations following kindling of different brain regions
Bibliographic record
Abstract
The vulnerability and plasticity of hippocampal GABAergic interneurons is a topic of broad interest and debate in the field of epilepsy. In this experiment, we used the electrical kindling model of epilepsy to determine whether seizures that originate in different brain regions have differential effects on hippocampal interneuron subpopulations. Long-Evans rats received 99 electrical stimulations of the hippocampus, amygdala, or caudate nucleus, followed by sacrifice and immunohistochemical or western blot analyses. We analyzed markers of dendritic (somatostatin), perisomatic (parvalbumin), and interneuron-selective (calretinin) inhibition, as well as an overall indicator (GAD67) of interneuron distribution across all major hippocampal subfields. Our results indicate that kindling produces selective effects on the number and morphology of different functional classes of GABAergic interneurons. In particular, limbic kindling appears to enhance dendritic inhibition, indicated by a greater number of somatostatin-immunoreactive (-ir) cells in the CA1 pyramidal layer and robust morphological sprouting in the dentate gyrus. We also found a reduction in the number of interneuron-selective calretinin-ir cells in the dentate gyrus of hippocampal-kindled rats, which suggests a possible reduction of synchronized dendritic inhibition. In contrast, perisomatic inhibition indicated by parvalbumin immunoreactivity appears to be largely resilient to the effects of kindling. Finally, we found a significant induction in the number of GAD67-cells in caudate-kindled rats in the dentate gyrus and CA3 hippocampal subfields. Taken together, our results demonstrate that kindling has subfield-selective effects on the different functional classes of hippocampal GABAergic interneurons. J. Comp. Neurol. 525:389-406, 2017. © 2016 Wiley Periodicals, Inc.
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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 | 0.000 |
| 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".