A Smart Neuroscience Platform with Wireless Power Transmission for Simultaneous Optogenetics and Electrophysiological Recording
Bibliographic record
Abstract
This paper presents a fully wireless neuroscience platform for enabling uninterrupted optogenetic experiments with live laboratory rodents. The system includes a wireless power transmission (WPT) home-cage using a 4-coil resonant link, a motion tracking system, a multichannel optogenetic headstage and a base station. The WPT home-cage uses a new hybrid parallel power transmitter (TX) coil array and segmented multicoil resonators to achieve high power transmission efficiency (PTE) and deliver high power across distances as high as 20 cm. The multicoil power receiver (RX) uses a RX coil with a diameter of 1.0 cm and a resonator coil with a diameter of 1.5 cm. The WPT home-cage average power transfer efficiency is 29.4%, at a nominal distance of 7 cm, for a power carrier frequency of 13.56 MHz. It has maximum and minimum PTE of 50% and 12% along the Z axis, and can deliver a constant power of 74 mW to supply the miniature neural headstage. The neural headstage includes 1 optical stimulation channel and 4 recording channels. We show that the hybrid WPT home-cage can properly power up the headstage without interruption, while the motion tracking system can track the activity of the animal in real time for enabling simultaneous behavioural and physiological assessment.
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.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".