High‐voltage compliant microelectrode array drivers for intracortical microstimulation
Bibliographic record
Abstract
Summary We present in this paper two low‐power high‐impedance microelectrode array drivers (MEDs) dedicated for visual intracortical microstimulation. These output stages of a new microstimulator are highly configurable and able to deliver higher compliance voltage (20 V for anodic and cathodic phases) across microelectrode‐tissue interface impedance compared with previously reported designs. Each MED is featured with a high‐voltage switch‐matrix, 3.3 V/20 V current mirrors, an on‐chip 32‐bit serial‐in parallel‐out shift register, and the new forbidden state logic circuits. Both systems are able to deliver eight bipolar or 16 monopolar stimulation simultaneously. The first MED is able to deliver one stimulation current level and the second one provides four different current amplitudes simultaneously to 16 electrodes. Two microchips have been designed and fabricated using Teledyne DALSA 0.8 µm 5V/ 20v double‐diffused metal‐oxide‐semiconductor field‐effect transistor (Teledyne DALSA Semiconductor, Bromont, Québec, Canada) technology to meet the required high‐voltage compliance. The nominal values of largest supply voltages are ±10 V. The maximum stimulation current per input channel is 400 μA and per output channel through an emulated microelectrode impedance of 100 kΩ is 100 μA. The measured output compliance voltage is 10 V/phase (anodic or cathodic) for the specified supply voltages. Increment of supply voltages to ±13 V allows 220 μA stimulation current per output channel enhancing the output compliance voltage up to 20 V/phase. The measured quiescent power consumptions of the proposed microelectrode array drivers are 316 and 735 μW, respectively. Post‐layout simulation and measurement results of two MEDs and comparison with other designs have been reported in this paper. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.004 | 0.001 |
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".