Track-and-Zoom Neural Analog-to-Digital Converter With Blind Stimulation Artifact Rejection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Closed-loop neuromodulation for the treatment of neurological disorders requires monitoring of the brain activity uninterruptedly even during neurostimulation. This article presents a bidirectional 32-channel CMOS neural interface that can record neural activity during stimulation. Each channel consists of a dc-coupled Δ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> Σ-modulated analog-to-digital converter (neural-ADC), which records slow potentials (<; 0.1 Hz) while accommodating rail-to-rail dc offset using a spectrum-shaping front-end. This front-end equalizes the neural signal spectrum before signal quantization, which reduces the energy consumption and silicon area. Upon detection of a large artifact by an in-channel event-triggered digital block, the modulator feedback DAC tracks the artifact with step sizes incrementing in a radix-2 exponential form, preventing the neural-ADC from saturation. Upon tracking the artifact, the multi-bit DAC step size is reduced to zoom into the input neural signal at the highest recording resolution. The modulator's multi-bit DAC is reused in a time-shared fashion as a current-mode stimulator with no area overhead. The Δ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> Σ-ADC consumes 1.7 μW from 0.6-V/1.2-V digital/analog supplies and time-shares the modulator's feedback DAC as the multi-bit current-mode stimulator operating at 3.3 V. The ADC occupies a silicon area of 0.023 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in the 130-nm CMOS and achieves a signal-to-noise-and-distortion ratio (SNDR) of 70 dB over the 500-Hz bandwidth and an equivalent noise efficiency factor (NEF) of 2.86 without a stand-alone front-end amplifier. The 32-channel bidirectionally interfacing prototype is validated in the in vivo whole brain of a rodent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it