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eess.SP · Signal Processing

Separate allowed 12-sample errors at the window center changed all 1,348 tested SEEG decisions within a 100 µV RMS limit per pair in eight people

We tested short voltage errors in eight fixed readers of public SEEG data. Each reader used eight contact pairs and three power bands in a 500-sample window. The main test allowed a separate error in 12 central samples of every pair, with an RMS limit of 100 microvolts per pair. Neither a quadratic power bound nor a triangle bound preserved any of the 1,348 later test decisions. After this result, a constrained search found a separate allowed error that changed each decision. Independent spectra replayed all 1,348 errors and verified their limits. In a planned secondary test, the quadratic bound preserved a mean of 99.1 percent of decisions for errors in the first 12 samples. The triangle bound preserved 79.9 percent. A preserved decision can still be wrong. All 2,014 retained source trials were rebuilt from pinned public byte ranges and matched. The package supplies an exact arithmetic proof, fixed readers, compact voltage data, source records, all results, four figures, and code. This is a method test in reused recordings. The errors were constructed. No stimulation artifact, live interface, or new patient was tested.

stereoelectroencephalography · SEEG · brain-computer interface · signal processing · quadratic bounds · robust classification · additive error · power features

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References

8
  1. usesQuadratic bounds certified 39.4 percent of later SEEG decisions for simultaneous constant contact gain changes of up to five percent in eight recordings sci:sha256:84281693cc487ddfcf3c2068318e3a80ccf9052c5526b3cc3992b8438e3deb78

    This work supplied method context for quadratic power bounds and fixed log power reader intervals under gain errors. We applied a score interval to short additive sample errors. We did not use its gain-error results as data.

  2. usesA projected bound shortened 70 to 110 Hz power guards in 400 SEEG pulses under stated input error balls sci:sha256:f2d58decfe90973c2f686776c67fb1fe755b1ff4fccac8c9bcf4a681fe5e7d60

    This work supplied method context for a standard trust-region power bound under short input error balls. We applied this bound to fixed three-band log power readers. We claim no new trust-region theorem.

  3. usesThe last 250 samples gave mixed Brier error changes against 500 samples in eight SEEG task state readers with three tapers sci:sha256:db0a649b736a8d86e3c000cb147a3812525c0a0cee4508122cabf769cf444934

    This work supplied the exact 500-sample pair buffers, trial records, source metadata, range records, and inherited EDF helper. All copied input hashes matched. We used its data and made new error bounds.

  4. usesEight SEEG pairs classify pre-response and rest windows at 70.7% mean balanced accuracy in later trials from eight recordings sci:sha256:c74068384c7c056974c8568aab987cf5a8eee9979a622c22efa1b67a911e77fd

    This work supplied the original early pair choices, trial choices, split, reference features, and EDF helper bodies through the data parent. We kept these choices fixed.

  5. usesA stationary Gaussian variance correction with 5 percent shrinkage reduced SEEG decoding accuracy for 20 percent simulated sample loss in eight recordings sci:sha256:495cd9ff22cc042e1f138d100dbf95110efd76545b22997f0bb2f49092bdf3ae

    This work supplied exact digital extraction and source range records in the inherited data chain. The new source check rebuilt all retained trials and matched their samples.

  6. usesPair coding gave higher later balanced state accuracy than contact coding with early fixed readers and ranges at a uniform 64-bit sample budget in eight SEEG recordings sci:sha256:940020fa46b275fd1d01fe99eb878b75cc6cbb521ffd3d44121ccb5085ce68d3

    This work supplied eight fixed native power readers and their later test records. We used these reader states without a new fit. We matched every nominal decision.

  7. usesdoi:10.18112/openneuro.ds004473.v1.0.2

    The analysis used task recordings from OpenNeuro ds004473 version 1.0.2.

  8. doi:10.1088/1741-2552%2Facae0a

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