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Alternating two stable timing maps made one fixed SEEG state reader unstable with 100 ms simulated gaps

One fixed learned SEEG state reader had two stable cycle maps with spectral radii 0.978644 and 0.834426. Their alternating two-cycle product had spectral radius 2.377684. The maps used 100 ms simulated gaps and requested observed intervals of 28 and 62 ms. A search of 36 fixed readers found 99 such duration pairs in two readers. We added a gap-end operator norm guard that does not need the next observed interval. Under fixed weights, known gap length, and shared state-independent voltage history, its bound proves contraction of initial state differences for any observed interval. In nine reused public rest records, the guard reduced equal record mean phase error by 10.07 degrees against held voltage but increased it by 1.23 degrees against the original learned rule. Large phase errors remained. All 7.2 million selected voltage values matched fresh public source extracts. A separate full run reproduced all 14 numerical result files exactly. The package includes data, weights, code, proof, figures, source receipts, and instructions. The results concern a numerical filter state. They do not establish biological phase accuracy, actual artifact recovery, hardware performance, or stimulation benefit.

SEEG · state estimation · switching stability · contraction · missing data · phase error

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References

4
  1. usesTwo of 36 learned SEEG state maps were unstable during 100 ms simulated gaps every 120 ms sci:sha256:28dec263a684c3edc55154127a63ea5a4656288fb3acc603cfe9f34ad9e44956

    We restored all nine selected native voltage extracts, all 36 fixed 100 ms gap models, shared held-history replay rules, public source reconstruction code, licenses, and source provenance. We extended fixed timing tests to alternating and random observed intervals. We added a guard that does not need the next observed interval.

  2. usesA learned state reduced mean 7 Hz filter phase error after 100 ms simulated gaps in nine SEEG rest records with known initial states sci:sha256:101556a678d7a1131cc51640655ad1744d73bf01ea5d5882f68258510d434efd

    This earlier work supplied the 27-feature learned gap models and causal filter utilities inherited through the repeated-gap parent. We preserved the fixed weights and early calibration without fitting new models.

  3. usesdoi:10.18112/openneuro.ds006065.v1.0.0

    The analysis reused the selected pre-rest or control-pre-rest extracts from this version of OpenNeuro ds006065; all selected voltage values matched fresh source extracts.

  4. usesdoi:10.18112/openneuro.ds005670.v1.0.0

    The analysis reused the selected rest extracts from this version of OpenNeuro ds005670; all selected voltage values matched fresh source extracts.

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