Agreement between two windows kept one of 38 known sound queries from ten SEEG readers with a ±2 second search
We tested sound selection with public SEEG data from ten people. The fixed readers used eight contact pairs per person. We searched template times from -2 to +2 seconds. Two separate windows had to select the same file and offsets within 0.2 seconds. This rule kept one of 38 queries. That output was correct. It rejected five of six correct matches from the combined windows and all 32 wrong matches. Nine people had no accepted output. Thus the rule reduced wrong outputs with a large loss of useful outputs in this test. One accepted output cannot establish reliability. The SCI text, code, result tables, figures, and checks are retained; restricted source inputs are omitted.
stereoelectroencephalography · brain-computer interface · sound retrieval · speech listening · temporal agreement · selective prediction · known-sound identification
References
5- usesRemoving the true sound file kept best scores unchanged in 33 of 38 six second queries from ten SEEG listeners with ±2 second template search sci:sha256:c6eacaf2416253d04a0c1278f160991c294c71f891bb58be55ea617f93580d2c
Uses its true-file removal audit design to check whether the new agreement rule emits an output when the true candidate is absent.
- usesTemplate search from -2 to +2 seconds reduced known sound selection accuracy from 47.5% to 12.5% in ten fixed SEEG readers with six second queries and supplied excerpt times sci:sha256:c732f31226c3601b8096de46fe6fab4bce50d160ae04024f0a53bc40f0691596
Uses its preserved derived features and sound targets and its inherited reader and extraction code. Extends bounded template timing search with separate window agreement, without reader fitting changes.
- usesAn eight-pair SEEG reader selected known sound files absent from training with 47.5% mean accuracy in ten people with supplied onset times sci:sha256:b56411dc9a4fcfe0c1aa9d1b40dc88167615e1906feca138c8c6c0cc7bbabd2b
Uses its fixed eight-pair SEEG readers, archived predictions, selected passages, native sample audits, and source provenance. Rebuilds each reader and adds a two-window agreement test.
- usesdoi:10.18112/openneuro.ds004703.v1.1.0
The analysis used the ten-person SEEG and known-sound data from OpenNeuro ds004703 version 1.1.0.
- doi:10.1038/s41467-024-44844-9
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