PEDOT:PSS-coated platinum electrodes for neural stimulation
Bibliographic record
Abstract
Safe and long-term electrical stimulation of neurons requires charge injection without damaging the electrode and tissue. A common strategy to diminish adverse effects includes the modification of electrodes with materials that increases the charge injection capacity. Due to its high capacitance, the conducting polymer PEDOT:PSS is a promising coating material; however, the neural stimulation performance in terms of stability and safety remains largely unexplored. Here, PEDOT:PSS-coated platinum (Pt-PEDOT:PSS) microelectrodes are examined for neural stimulation and compared to bare platinum (Pt) electrodes. Microelectrodes in a bipolar configuration are used to deliver current-controlled, biphasic pulses with charge densities ranging from 64 to 255 μC cm−2. Stimulation for 2 h deteriorates bare Pt electrodes through corrosion, whereas the PEDOT:PSS coating prevents dissolution of Pt and shows no degradation. Acute stimulation of primary cortical cells cultured as neurospheres shows similar dependency on charge density for Pt and Pt-PEDOT:PSS electrodes with a threshold of 127 μC cm−2 and increased calcium response for higher charge densities. Continuous stimulation for 2 h results in higher levels of cell survival for Pt-PEDOT:PSS electrodes. Reduced cell survival on Pt electrodes is most profound for neurospheres in proximity of the electrodes. Extending the stimulation duration to 6 h increases cell death for both types of electrodes; however, neurospheres on Pt-PEDOT:PSS devices still show significant viability whereas stimulation is fatal for nearly all cells close to the Pt electrodes. This work demonstrates the protective properties of PEDOT:PSS that can be used as a promising approach to extend electrode lifetime and reduce cell damage for safe and long-term neural stimulation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".