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For one exact C. elegans mean kernel pair at 0.2 per second, a passive bound required 2.24 fold readout variation with free pools and 4.24 fold with equal pools

Changes in a calcium readout can make a passive electrical circuit appear to amplify a two-way response. We derive a bound on this effect. Each cell has a positive readout factor with fold range at most G. The two direction pools have gain-ratio distributions whose total variation distance is at most delta. The product P of the two mean source-normalized transfers obeys P <= {[(1+delta)G+(1-delta)/G]/2}^2. The bound permits hidden passive cells and different circuit states. A two-state passive circuit approaches the bound. Equal pools give the classical Kantorovich bound. Free pools give P<=G^2. We apply the inverse bound to a fixed published panel of 66 C. elegans kernel pairs. If the fitted mean values are exact, the largest pair at 0.2 per second needs a maximum per-cell gain range with infimum 2.237 for free pools, or 4.238 for equal pools. At 1 per second the values are 1.917 and 3.552. We give 45 finite passive pair models that match the values above one at the two rates. These are separate models, not a joint worm fit. Products formed within matched states stay at most one when the readout ratio is fixed within each matched pair. We check the method with exact arithmetic, numerical optimization, passive graph models and source coefficients. The export has no event-level kernel errors or calibrated gain distributions. Thus the results give sensitivity limits and a measurement method, not a rejection of passive transfer in animals.

connectome · calcium imaging · gap junction · passive transfer · readout gain · state pooling · Kantorovich inequality · total variation · C. elegans · identifiability

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References

8
  1. usesAt 0.2 per second, six of 66 fitted C. elegans kernel pairs exceeded a passive return bound that holds after averaging with fixed cell filters sci:sha256:5464a016848704fc8c08b305cebf0861f7b0e5c8808a541ab4b6d70ab79dc0ad

    We reuse its attributed numerical facts and fixed 66-pair scope. It showed that variable readouts can break a passive return bound. We add a sharp bound for bounded gain ranges and unequal pools, finite reconstructions and a measurement method.

  2. usesAt Laplace rates of 0.2 and 1 per second, removing four of 106 C. elegans kernel pairs with strong cancellation cut a reciprocity magnitude bound from 2.60 to 1.39 sci:sha256:d6592a9b70ebda3478fcb41c88b82653f072e54539897371fe9c9f1777827f8b

    It supplied the pinned dynamic kernel transforms and cancellation audit used by the later passive bound study. We verify the source coefficients again.

  3. usesdoi:10.1038/s41586-023-06683-4

    This study supplied the original stimulation and calcium measurements.

  4. usesdoi:10.17605/OSF.IO/E2SYT

    This is the source data project for the signal propagation atlas. We use the fixed WormNeuroAtlas export identified in the support files.

  5. supportsdoi:10.6028/jres.064b.003

    The equal-pool endpoint is the established scalar Kantorovich inequality. We add an explicit pool-distance bound and a neural transfer application.

  6. supportsdoi:10.1007/s00422-016-0681-y

    This work gives response methods for electrically coupled neural networks.

  7. usesdoi:10.1098/rstb.1986.0056

    Two native neuronal gap graphs supply passive model controls.

  8. usesdoi:10.1038/s41586-021-03778-8

    Two adult neuronal gap graphs supply passive model controls.

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