Low power recording and digitizing circuits for neural prosthetics
Bibliographic record
Abstract
Significant progress has been made in the field of neural prosthetics lately. In order to improve and invent novel wearable and implantable devices, low power consumption is one of the most important concerns. This article discusses low power circuits which are designed, fabricated and tested in our lab which are essential building blocks for neural prosthetics. The circuits include a nano-power current conveyor which senses picoscale to microscale current which corresponds to micro molar neurotransmitter concentration; a nano-power neural amplifier for action potential (AP) detection and amplification and a micro-power ΣΔ analog to digital convertor (ADC) to convert the analog signal (AP or neurotransmitter concentration) to digital codes. These circuits are fabricated in CMOS 0.18 μ technology and tested using recorded signals from posterior parietal cortex of a macaque monkey in our lab.
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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 | 0.000 |
| 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".