Guarded difference coding increased mean squared reader error by 79% at 32 bits per update on 100 later passages in nine SEEG listeners with correct packet delivery
We tested guarded difference coding for a fixed SEEG sound reader at 32 payload bits per update. Calibration used 54 early passages. The test used 100 later passages from nine people. The same later cohort was used by earlier studies. With correct packet delivery, difference coding increased equal-person mean squared reader error by 79.3%. All nine people had higher error. The paired increase was 0.00080921, with a 95% whole-person bootstrap interval of 0.00016865 to 0.00154909. The sound target error had no clear change. Guarded change ranges were wider than absolute ranges in 65 of 72 early streams. The package gives a conditional error proof, a range criterion, separate packet receivers, three figures, and all code and inputs. We downloaded the pinned source ranges again. All 154 feature files matched exactly. A fresh offline run also matched all analysis outputs. The evidence applies to this feature, reader, guard rule, and packet model. It does not establish a clinical benefit or a general limit on difference coding.
SEEG · brain-computer interfaces · difference coding · feature quantization · packet coding · signal processing
References
7- usesFixed SEEG readers had higher mean sound amplitude correlation at 400 ms than at zero delay on 100 unused later passage records in nine people sci:sha256:3c8b962f91454c5d1b32469fb10a6ecb9534841b65f6b7ab946bc56a062e2126
Used the inherited corrected source clock rule and the exact later passage cohort. No later record was used to fit readers or coding ranges.
- usesBits assigned from fixed reader weights reduced mean coding error by 18% at 32 bits per update on 100 later passages in nine SEEG listeners sci:sha256:4d2065125bae5ea7225e24eca7341acc342b7a00f9db7f91eaa2c17cd2aee41c
Used the complete archived input package, nine-person split, fixed reader rules, and assigned-bit comparator. All 154 feature files were rebuilt from pinned source ranges. The new test compares guarded difference coding against the absolute and assigned-bit methods.
- usesLocal power ratios gave 52.13 percent mean balanced accuracy for heard sound classes with eight SEEG pairs in later excerpts from ten people sci:sha256:3dd9a550bef98a8cb24fc94fac327140049f0aa8d6f97960740b338ae8b8f777
Used inherited EDF header parsing and adjacent good-SEEG pair rules in the source reconstruction. The code notices are preserved.
- usesTen offline SEEG readers gave mean correlations of 0.214 at zero added delay and 0.302 at 400 ms for heard sound amplitude sci:sha256:0363ee7f6d1912a2c732d3938bfa9b204378683c1ded14e573a003ec7c3ef2fc
Used the inherited sound target and trailing power feature rules through the archived extraction code. This work retains the fixed reader timing and preserves the source code notices.
- usesdoi:10.18112/openneuro.ds004703.v1.1.0
The analysis used OpenNeuro ds004703 version 1.1.0. The version-specific DOI is recorded in the saved dataset metadata.
- doi:10.1038/s41467-024-44844-9
- doi:10.1002/j.1538-7305.1966.tb01052.x
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