A fully implantable multichip neural interface with a new scalable current-reuse front-end
Bibliographic record
Abstract
This paper presents a fully implantable brain machine interface based on a new CMOS system-on-a-chip (SOC) including a low-power multi-channel current-reuse analog front-end (AFE), a multi-band wireless transceiver and a power management unit retrieving power from a 13.56 MHz carrier through a new 5-coil inductive link. In addition to this SOC, the proposed interface includes a low-power microcontroller, a wideband antenna and a double-sided power recovery coil. All components are bonded on a thin flexible printed circuit board. The AFE uses a new current-reuse circuit topology based on a current-mirror opamp which is scalable to very large number of recording channels, thanks to its small implementation area and its low-power consumption. It includes a low-noise amplifier (LNA) and a programmable gain amplifier (PGA) presenting tree selectable gains of 35 dB, 43.1 dB and 49.5 dB. The SOC is fabricated in a CMOS 180-nm process and has a size of 1.3 mm × 1.8 mm. The AFE has a low-power consumption of 9 μW (4.5 μw for LNA and 4.5 μw for PGA) per channel, for an input referred noise of 3.2 μV. A 5-coil wireless power link is utilized with an efficiency of 28% and a maximum power delivered to the load of 81 mW through a 1 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> flexible coil. The ultra wideband edge combining BPSK transmitter reaches a maximum data rate of 800 Mbps at 6.7 pJ/bit, and the 2.4-GHz OOK receiver reaches a maximum data rate of 100 Mbps. The whole system consumes 12.3 mW and weights 0.163 g. Finally, we present biological results obtained in-vivo from the cortex of an anesthetized mouse.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".