Human CCEP N1 probability decreases with distance, but an exponential law is not preferred over a power law
We tested the exponential distance rule (EDR) on human cortico-cortical evoked potentials. We used the expert-checked N1 detections and the electrode coordinates of OpenNeuro ds005448 v1.0.0 (13 patients: 8 SEEG, 5 ECoG). We wrote the plan before the fits. The unit is one (stimulation pair, recording contact) pair. We used only the stimulation columns that the expert checked and the distances 10-100 mm (50729 pairs, 7425 N1). Per patient, we fit p = A exp(-lambda d) and p = A d^-alpha by Bernoulli maximum likelihood. Result 1: lambda is more than zero in 13 of 13 patients; mean 0.070/mm (95% CI 0.058-0.084), length constant 14 mm (per-patient range 7-21 mm); Holm p = 0.0005. Result 2: the EDR does not fit better than the power law (log-likelihood difference 0.003 per pair, 8 of 13 patients, exact sign-flip p = 0.14). The pooled probability is 0.56 at 10-15 mm and 0.05 at 45-50 mm, then stays at 0.02-0.04 to 100 mm. The results are the same for 20-100 mm and when we remove same-shaft contacts. SEEG and ECoG do not differ (p = 0.52). N1 amplitude fits log distance better than distance in 13 of 13 patients. Limits: Euclidean (not tract) distance, clinical electrode positions, threshold-based N1, one centre. The package has numpy-only code, input files with SHA-256 checks, per-patient and per-pair tables, and 1-minute reproduction commands.
cortico-cortical evoked potentials · CCEP · N1 response · response probability · distance dependence · exponential distance rule · power law · intracranial EEG · SEEG · ECoG
References
4- usesExpert-checked CCEP N1 latency increased with Euclidean distance in all 8 SEEG patients; an age effect was not shown in 13 patients sci:sha256:0edf197a069dcfbb5a90b3c78e72e3dc4d41718b6848db0e4b22812aef830255
We used its numpy-only MAT v5 reader (code/mat5.py) to read the N1sChecked.mat files without scipy.
- usesIn six SEEG patients, SOZ contacts did not receive significantly more CCEP N1 responses after distance control sci:sha256:50d7449a6feefc0875ffd1fb06586e32df6d2856efee1a3b0302b99bd622f9bf
This package first downloaded the ds005448 v1.0.0 files and recorded their SHA-256 values. We copied its provenance table and checked 86 of 86 hashes.
- usesCCEP N1 latency increased with distance in 12 of 13 patients, with weaker long-range prediction in SEEG sci:sha256:0329b99af541eabd885a1d2dfb31d897eca4a2554f324f9a7657cc743f38d17b
We used the archived ds005448 v1.0.0 input files (N1sChecked.mat, electrodes.tsv, channels.tsv, participants.tsv) and its contact exclusion rules and SEEG/ECoG labels. That package tested N1 latency versus distance; this package tests N1 probability versus distance.
- usesdoi:10.18112/openneuro.ds005448.v1.0.0
The analysis uses expert-checked N1 detections, electrode coordinates, channel status, and participant labels from OpenNeuro ds005448 v1.0.0 (STReEF).
Cited by
3 publicationsPublic catalog entries on Sciscape.
- supportsCCEP response decreased with distance in three Mayo limbic SEEG patients
The per-mm logistic slope of CCEP response probability in ds004696 (-0.055 to -0.075) is near the 0.070/mm reported for ds005448.
- supportsMayo ECoG CCEP N1 probability decreases with distance, but exponential fit superiority is not supported
At a second centre (Mayo, 5 patients, mostly ECoG), lambda is more than zero in 5 of 5 patients, the 95% CI 0.068-0.121 per mm includes 0.070, and the exponential law does not fit better than the power law (p = 0.31).
- supportsCCEP N1 latency increased and N1 presence decreased with distance in Mayo SEEG data, with effect sizes dependent on detector threshold
N1 presence decreases with distance in 8 of 8 Mayo SEEG patients. The decay constant (0.027 or 0.057 per mm) depends on the detector threshold; 0.070 per mm is inside the 5 SD CI only.