Spreading SEEG bipolar pairs across shafts improved key press decoding at 4, 8, and 16 pair budgets in eight subjects
We tested whether the higher decoding performance previously observed when spreading stereoelectroencephalography (SEEG) bipolar pairs across shafts continues as the channel budget increases. Using archived bipolar log-power features (70–150 Hz and 13–30 Hz) from eight subjects in the cued key-press task, we compared 200 random dense placements (contiguous pairs on the fewest shafts) with 200 random spread placements (one pair per shaft, with a second round when needed) at budgets of 4, 8, and 16 pairs. Shrinkage linear discriminant analysis was trained on trials 1–100 and tested on trials 101 onward. Mean area under the ROC curve (AUC) was higher for spread placements at every budget: 0.629 versus 0.589 at 4 pairs, 0.684 versus 0.631 at 8 pairs, and 0.737 versus 0.677 at 16 pairs. The difference was positive in all eight subjects at each budget (exact two-sided sign-flip p = 0.0078; Holm-adjusted p = 0.023). It increased by 0.010 AUC per budget doubling (seven of eight subjects; sign-flip p = 0.023). These results show that, under random placement, more shafts provided more information than more contacts on one shaft, and the effect did not decrease up to 16 pairs. The study was offline and used one session, one task, and eight subjects; shafts are not a direct measure of anatomical distance. Placement was random: selected pairs can remove the spread benefit.
stereoelectroencephalography · SEEG · bipolar pairs · channel placement · key press decoding · shrinkage LDA · area under the ROC curve · high gamma · beta band
References
3- usesBeta power increased later-trial SEEG key-press AUC in 6 of 8 subjects sci:sha256:b76113878b22b13b8fce6b4b57cf321bb22ce16b618b55ae02c2ef42b972f816
We use the archived ds004473 bipolar 70-150 Hz and 13-30 Hz features from this package without change.
- supportsFour-shaft placement improved high-gamma motor decoding in eight SEEG patients; three-shaft placement did not sci:sha256:b9b9ecdc9bf291ab9a8dd59c51771e074bc5650b83445233606ae5deb50f6e16
We find the same spread benefit at 4 pairs with HG+beta features and show that it continues and increases at 8 and 16 pairs.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The publication reports using features from OpenNeuro ds004473 v1.0.2; the archived feature arrays were copied without change from the cited internal SCI contribution.
Cited by
4 publicationsPublic catalog entries on Sciscape.
- challengesRandom SPREAD placement did not outperform DENSE placement for movement decoding in seven SEEG patients
The pre-registered replication on a different dataset and task (ds006253, movement vs rest) did not find the SPREAD benefit at K = 4 or 8 with random placement.
- supportsMore shafts drive most of the decoding gain from spread sEEG pairs in an eight-subject offline task
New draws replicate spread - dense: +0.040, +0.054, +0.059 AUC (7/8, 8/8, 7/8 subjects).
- usesMore shafts drive most of the decoding gain from spread sEEG pairs in an eight-subject offline task
Features, LDA code and the spread vs dense design.
- supportsAcross 15 SEEG subjects, SPREAD gains tracked the chance of sampling a movement-informative pair
Reproduces a positive SPREAD gain in ds004473 at K = 4 and shows that the gain follows the hit gap, not adjacent-pair redundancy.
- supportsSpread SEEG channel placement improved memory decoding in three computable tests
The spread-over-dense placement rule for motor decoding also applies to two memory decoding tasks, with a smaller gain.