Neurogenic hippocampal targets of deep brain stimulation
Bibliographic record
Abstract
Deep brain stimulation (DBS) is being used to treat movement, neurological, and psychiatric disorders; recently it has been successfully applied to patients with treatment-resistant depression or in minimally conscious state. In addition to its clinical importance, DBS presents a powerful approach to target specific neural circuits and determine the functional relationship between the components of these circuits. We examined the effect of high-frequency stimulation of a crucial component of the limbic circuitry, the anterior thalamic nuclei (ATN), on the generation of new neurons in the dentate gyrus (DG) of the hippocampus, another component of the same circuitry. Adult hippocampal neurogenesis emerges as a strong correlate of antidepressant treatments; however, in most cases, the progenitor cell population targeted by a specific treatment is not known. Using reporter mouse lines designed to quantify changes in selected classes of neural progenitors, we found that high-frequency stimulation of the ATN increases symmetric divisions of a defined class of neural progenitors in the DG; this effect is later manifested as an increased number of new neurons. The affected class of neural progenitors is also affected by the antidepressant fluoxetine (Prozac) and physical exercise (running). This indicates that neurogenic stimuli of different natures can converge on the same neurogenic target in the DG. Our results also suggest that hippocampal neurogenesis may be used as a sensitive indicator of the limbic circuitry activation induced by DBS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".