A phase I trial of deep brain stimulation of memory circuits in Alzheimer's disease
Bibliographic record
Abstract
OBJECTIVE: Alzheimer disease (AD) is characterized by functional impairment in the neural elements and circuits underlying cognitive and memory functions. We hypothesized that fornix/hypothalamus deep brain stimulation (DBS) could modulate neurophysiological activity in these pathological circuits and possibly produce clinical benefits. METHODS: We conducted a phase I trial in 6 patients with mild AD receiving ongoing medication treatment. Patients received continuous stimulation for 12 months. Three main lines of investigation were pursued including: (1) mapping the brain areas whose physiological function was modulated by stimulation using standardized low-resolution electromagnetic tomography, (2) assessing whether DBS could correct the regional alterations in cerebral glucose metabolism in AD using positron emission tomography (PET), and 3) measuring the effects of DBS on cognitive function over time using clinical scales and instruments. RESULTS: DBS drove neural activity in the memory circuit, including the entorhinal, and hippocampal areas and activated the brain's default mode network. PET scans showed an early and striking reversal of the impaired glucose utilization in the temporal and parietal lobes that was maintained after 12 months of continuous stimulation. Evaluation of the Alzheimer's Disease Assessment Scale cognitive subscale and the Mini Mental State Examination suggested possible improvements and/or slowing in the rate of cognitive decline at 6 and 12 months in some patients. There were no serious adverse events. INTERPRETATION: There is an urgent need for novel therapeutic approaches for AD. Modulating pathological brain activity in this illness with DBS merits further investigation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".