An Adaptive and Autonomous System-On-Chip with Data Analysis for μs-Latency Closed-Loop Optogenetics
Bibliographic record
Abstract
In this paper, we report a mixed-signal chip in 0.13-μm designed for long term autonomous operation that can trigger low-latency stimulation upon the detection of complex neural firing patterns. This adaptive autonomous neural IC (AANIC) includes: i) circuits for multi-site optogenetics stimulation and multi-unit electrophysiology recording, ii) specialized digital cores to detect, compress, and classify the neural signals in situ and iii) a programmable processor, connected to the specialized cores, running the closed-loop algorithm. The AANIC can process 10 neural channels in parallel, and stimulate through two independent precise current-sources, and is integrated within a tiny wireless optogenetic platform. The AANIC has a latency of 0.6 ms, a power of 165 μW/Ch, an effective number of bits (ENOB) of 8.68 bits (OSR=25), a tunable bandwidth (1-6.5 kHz), and is tested in vivo in freely-moving experiments involving a mouse model of temporal lobe epilepsy expressing ChR2 in its inhibitory neurons.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".