A 13μm CMOS SoC for simultaneous multichannel optogenetics and electrophysiological brain recording
Bibliographic record
Abstract
Optogenetics and multi-unit electrophysiological recording are state-of-the-art approaches in neuroscience to observe neural microcircuits in vivo [1]. Thereby, brain-implantable devices incorporating optical stimulation and low-noise data acquisition means have been designed based on custom integrated circuits (IC) to study the brain of small freely behaving laboratory animals. However, no existing IC provides multichannel optogenetic photo-stimulation along with multi-unit electrophysiological recording capability within the same die [2-5]. They also lack critical features: they are not multichannel and/or do not include an ADC [6], or they address only one signal modality [5-6], i.e., either local field potentials (LFP) or action potentials (AP). In this paper, we report an IC for simultaneous multichannel optogenetics and electrophysiological recording addressing both LFP and AP signals all at once. This 0.13μm CMOS chip, which includes 4/10 stimulation/recording channels, is enclosed inside a small wireless optogenetic platform, and is demonstrated with simultaneous in vivo optical stimulation and electrophysiological recordings with a virally mediated Channelrhodopsin-2 (ChR2) rat.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".