Towards an implantale intelligent CMOS neurotrophic factor delivery micro neural prosthetic for Parkinson's disease
Bibliographic record
Abstract
Millions of patients around the world suffer from neurological disorders. Many of these diseases such as Parkinson's are due to degeneration of Dopaminergic neurons. Our ultimate goal is to develop an intelligent implantable CMOS neurotrophic factor delivery microsystem which can maintain therapeutic levels of chemical concentrations in the brain by protecting the healthy neurons and restoring damaged ones. The hybrid microsystem is composed of neural probes fitted with novel sensors that can sense micromolar concentration of neurotransmitters (dopamine) and embedded negative feedback circuits that control the flow of pharmacological agents in micro fluidic channels. Additionally MEMS (Micro Electro Mechanical System) pumps connected to the probes to inject micromolar concentration of neurotrophic factors such as GDNF into the brain in order to protect and restore dopaminergic neurons in the nigrostriatal pathway. The focus of this manuscript is on sensing, control and decision making circuitry. It consists of a current conveyer, a low noise low power amplifier, an integrator and a comparator with offset cancelation. Circuit is fabricated in CMOS 0.18 um with low power consumption of 921 nW while maintaining a bandwidth of 2.75K Hertz.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".