Dosing of Electrical Parameters in Deep Brain Stimulation (DBS) for Intractable Depression: A Review of Clinical Studies
Bibliographic record
Abstract
Background: The electrical parameters used for deep brain stimulation (DBS) in movement disorders have been relatively well studied, however for the newer indications of DBS for psychiatric indications these are less clear. Based on the movement disorder literature, use of the correct stimulation parameters should be crucial for clinical outcomes. This review examines the stimulation parameters used in DBS studies for treatment resistant depression (TRD) and their relevance to clinical outcome and brain targets. Methods: We examined the published studies on DBS for TRD archived in major databases. Data on stimulus parameters (frequency, pulse width, amplitude), stimulation mode, brain target, efficacy, safety, and duration of follow up were extracted from 29 observational studies including case reports of patients with treatment resistant unipolar, bipolar and co-morbid depression. Results: The algorithms commonly used to optimize efficacy were increasing amplitude followed by changing the electric contacts or increasing pulse width. High frequency stimulation (> 100Hz) was applied in most cases across brain targets. Keeping the high frequency stimulation constant, three different combinations of parameters were mainly used: (i) short pulse width (60-90 us) and low amplitude (0-4V), (ii) short pulse width and high amplitude (5-10 V), iii) long pulse width (120-450 us) and low amplitude. There were individual variations in clinical response to electrical dosing and also in the time of clinical recovery. There was no significant difference in mean stimulation parameters between responders and non-responders suggesting a role for stimulation unrelated factors in response. Conclusions: Although limited by open trials and small sample size, three optimal stimulation parameter combinations emerged from this review. Studies are needed to assess the comparative efficacy and safety of these combinations, such as a registry of data from patients undergoing DBS for TRD with individual data on stimulation parameters.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".