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Resistance and area matching cut RMS impedance error in ten passive dendrite path models with 10 µm bins at six 0–100 Hz frequencies

We tested whether a compact cable model can keep voltage transfer through narrow dendrite sections. We used diameter profiles from three expansion-microscopy paths and seven electron-microscopy paths. The model had passive membrane, a soma load, and no side branches. Each 10 µm bin kept membrane area. The tested correction also kept axial resistance. We compared six impedance entries at 0, 1, 3, 10, 30, and 100 Hz with detailed models of the same geometry. The correction improved all ten path models. Median RMS relative error fell from 6.141% to 0.2632% for expansion microscopy and from 2.913% to 0.03618% for electron microscopy. Every corrected path RMS error was below 0.32%. The largest individual error was 1.062% on the primary grid and 7.162% at 1,000 Hz. Parameter and orientation controls kept the improvement. Reference refinement, exact uniform cable solutions, and independent circuit solves checked the calculations. Fresh source checks matched all 23 selected CSV files. A separate run repeated all nine numerical outputs exactly. The paths are selected and can share cell structure. The test does not separate constrictions from taper or measurement noise. No new animal voltage was measured. The contribution is a local numerical rule and a measured-geometry benchmark, with code, source data, provenance, figures, and offline repeat steps.

dendritic shaft constriction · passive cable · model reduction · axial resistance · membrane area · connectome simulation · impedance

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References

3
  1. usesdoi:10.1126/sciadv.aec4911

    We use the reported passive model values and the biological context for the released dendrite profiles. The source study established constrictions and their effects.

  2. usesdoi:10.5281/zenodo.14037025

    We use 23 selected original CSV members, pinned by member SHA-256 and archive byte range. Ten paths pass the main quality and length rules. The original data are CC BY 4.0.

  3. doi:10.1038/s41467-019-13932-6

    This prior method establishes impedance-based reduction of neuron models. We cite it as prior work. We do not compare our local bin rule with its performance.

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