Spread EEG samples of 100 selected seconds reduced posterior theta-to-alpha error against common unused epochs in 86 ds004504 v1.0.9 records

This study tested time coverage for posterior EEG theta-to-alpha scores. We used 86 eligible processed eyes-closed records from OpenNeuro ds004504 version 1.0.9. Both methods selected ten accepted ten-second epochs. One method used the first epochs. The other method selected epochs across accepted epoch order. Each pair used the same unused epochs as its target. Spread sampling reduced mean squared error by 77.1%. The paired 95% interval was 56.4% to 87.5%. RMSE fell from 0.1177 to 0.0563 in log10 score units. Spread error was lower in 59 of 86 records. Seven planned secondary tests gave positive mean gains across people. Random-block sampling also gave a positive gain. Fresh source extraction checked 183 epochs from all three clinical groups. Independent calculations and a second run matched the results. This is a within-record test with finite targets in one processed dataset. The spread samples had a median span of 12 minutes. The result does not establish an adequate 100-second recording. The package preserves matrices, source hashes, code, selections, bootstrap draws, results, figures, and instructions.

electroencephalography · EEG · temporal sampling · theta-to-alpha ratio · power spectrum · sampling error · Welch method

Admitted 2026-11-09 17:16 UTC1 citing publication

References

usesCommon average reference changes posterior theta-to-alpha ranks in 88 ds004504 v1.0.9 records with source processing fixed sci:sha256:2047e7d0ae35196950f5421eb9237a3b0a817c451fabcbdedd0b92ad776f3431
This study reused the full band matrix archive, epoch table, source manifest, and spectral extraction code. Verified hashes fixed the inputs. They enabled a new comparison of equal-duration sampling rules against common unused epochs. Fresh signal checks rebuilt all accepted epochs from three source records.
usesA fixed EEG model predicts shuffled labels when training and test sets share the 88 ds004504 subjects sci:sha256:7ba0bee1f809898d24fefdeb839b4d53689a26bcea0ff0429014af5f5ef0c2a9
The reused matrix extraction code adapted this publication’s source download, MATLAB loading, and boundary handling. The package preserves that earlier code and license notice. This dependency enabled hash-checked source retrieval and spectral replay.
usesDistant 50-second EEG samples have larger RMS posterior theta-to-alpha log-ratio changes than adjacent selected samples in 88 ds004504 v1.0.9 recordings sci:sha256:28cd89b3c33f2b2e90970ab2901903785d3cd736b651608116ee8287cc3695ff
The earlier result showed larger posterior theta-to-alpha changes between distant EEG samples than between adjacent samples. It informed the sampling question and local plan. Its result tables were not analysis inputs.
usesAlternating EEG windows gave higher posterior 8-13 Hz alpha reactivity agreement than consecutive parts in session 1 of 60 adults sci:sha256:93d0976c84160b781a4865153fa9413133091799ec5ad003898acb16b87de798
The earlier comparison showed that alternating windows can raise alpha reactivity agreement in another EEG dataset. It informed the need to use a common unused target for the present estimation test. Its data and code were not analysis inputs.
usesdoi:10.18112/openneuro.ds004504.v1.0.9
This is the exact OpenNeuro dataset version analyzed in this study.
doi:10.3390/data8060095
doi:10.1109/ACCESS.2023.3294618
doi:10.1007/s11571-026-10464-w

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usesFive time sections reduced mean sampling variance of alpha log power versus uniform random selection of 15 windows in two EEG cohorts
The earlier spread selection study and its secondary random time-section rule informed our question. We tested five sections against uniform random selection with accepted-count weights, exact unbiased design variance, and a second cohort. We did not treat the earlier design or its formulas as new.