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A tie for the best axon order required 20 input label changes in one mouse table with target and axon totals fixed

We tested the stability of a structural axon order in one P6 mouse omohyoid muscle source table. The table has six axons, 297 target rows, and 651 binary partner links. A target scored one when its inputs occupied consecutive ranks. All 360 orders were searched after removal of reversal. One input label change removes a present axon and adds an absent axon in a target. With every target input count and all six axon totals fixed, 19 changes could not end the unique best order. Twenty changes could give a tie, and 21 could give a strict loss. When axon totals were free, ten changes sufficed. Exact first loss of forced neighbor pairs required 20 to 36 changes. A planned check on 52 targets with three or four inputs preferred another order, with score 43 instead of 37 for the full table order. Thus, the full score preference came from targets with two inputs. We provide exact lower bound certificates, integer examples, original code, source provenance, aggregate facts, and figures. A separate checker verified 652,662 inequalities and 1,795 integer examples. These limits concern the stated score and error models. They do not estimate reconstruction error or measure motor recruitment.

connectome · motor recruitment · axon order · annotation errors · consecutive ones · exact verification

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References

7
  1. usesdoi:10.1038/s41593-026-02344-7

    We analyze the Figure 5a source CSV from the journal version of record dated 30 June 2026. The external source has fixed URL and SHA-256 records.

  2. usesAn order learned from 148 targets gave 80% test agreement beyond count controls in one six-axon mouse table sci:sha256:ac8d45daa6e486c18434493f9e3edac4d3a42c301e40b6b088009527d7875049

    We use its source label audit and compare with its test on separate targets. All code in the present package is new.

  3. Three linear orders are needed to cover all input sets in a six-axon mouse muscle table under an exact interval model sci:sha256:ac0ec49c31e54682cd5d01c3f96843a53cba76bc7c1314d1bfd7fce336b5df29

    Its interval coverage result defines prior evidence for the score. We ask how errors can change the best single order.

  4. At fixed totals and order, pair counts forced 234 to 239 consecutive sets in one mouse table with six axons sci:sha256:7000717540781de4256bdefac1ab1647db89ab513616bbceccefa6210081214a

    It fixes pair counts. Our error model permits pair counts to change while target and axon totals stay fixed.

  5. doi:10.1016/S0022-0000(76)80045-1

    The consecutive ones property is an established representation of input sets along an order.

  6. usesdoi:10.1038/s41592-019-0686-2

    SciPy provides the linear and integer optimization interfaces.

  7. usesdoi:10.1007/s12532-017-0130-5

    This is the recommended HiGHS citation. SciPy invokes HiGHS to propose bounds and examples.

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