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eess.SP · Signal Processing

In eight SEEG subjects, multitaper power did not improve 0.1 s key-press decoding over Hann; Hann performed better at 0.5 s

Offline decoding in eight subjects from OpenNeuro ds004473 (task SlowFast) compared BOX, Hann, and DPSS multitaper estimates of 70–150 Hz bipolar SEEG power from 0.1, 0.2, and 0.5 s windows. For the prespecified 0.1 s contrast, MT2 (NW 2, K 3) minus Hann had a mean AUC difference of +0.019 (median +0.011; 4/8 subjects positive; exact sign-flip p = 0.62), providing no evidence of a multitaper gain. MT3 (NW 3, K 5) gave +0.025 (5/8; p = 0.55). At 0.5 s, Hann exceeded MT3 by 0.037 AUC and BOX by 0.077 (p = 0.10 and 0.031, respectively). A 0.1 s Hann window was 0.099 AUC below a 0.5 s Hann window (p = 0.039); no tested 0.1 s estimator removed the loss. The study was offline, used one task and session, included eight subjects with 32–60 test trials each, and had limited power for effects near 0.02 AUC. Fixed NW values were tested; adaptive weights and other bandwidths were not. The findings do not establish performance in a real-time decoder.

SEEG · spectral power · multitaper · Hann window · key-press decoding · ROC AUC

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References

5
  1. usesBeta power increased later-trial SEEG key-press AUC in 6 of 8 subjects sci:sha256:b76113878b22b13b8fce6b4b57cf321bb22ce16b618b55ae02c2ef42b972f816

    We copied the helper code from its package and use its trial definition and train 1-100 / test 101+ split.

  2. supportsA 0.1 s SEEG band-power window lowers AUC versus 0.5 s but raises the bit-rate upper bound in an offline key-press task sci:sha256:dc1fd8aa17e25534bd4d76db4b47d11ffdbde97b315057aba201ff0d58938fab

    Short 0.1 s windows decreased key-press AUC here too, and no taper choice removed the loss.

  3. usesSparse SEEG contacts showed an inconclusive small read-out decrease, with no detected penalty at equal channel count sci:sha256:f758ddd6a1f33f92c859c7b0dd2e5465eeb094a9e5d7de64d8afe4381926adbb

    We use its EDF byte-range reader, shaft parsing, bipolar rule and numpy shrinkage LDA.

  4. supportsIn eight SEEG participants, a 0.1 s power window reduced offline key-press detection AUC by 0.063 versus 0.5 s sci:sha256:fc2b8709d95ab55ea817efae09565d852c0d632206f908546fc2b3287d53316d

    With a different power estimator and no padding, a 0.1 s window also lost AUC against 0.5 s (-0.099, p = 0.039).

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

    The analysis used OpenNeuro ds004473 v1.0.2, task SlowFast, for eight subjects.

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