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pymef 1.4.8 segfaulted on MEF3 sample reads from two ds004977 channels; metadata and six tested file hashes matched

This stopped-at-decoding report records a MEF3 reader failure in OpenNeuro ds004977, not neural results. On Linux 7.0.0-38-generic with Python 3.14.4, numpy 2.5.4, gcc 15.2.0, and pymef 1.4.8, metadata for sub-1 run-01 read correctly (2,606,640 samples at 4800 Hz), but read_mef_ts_data() segfaulted (exit 139) on both tested channels, LBC1 and RA4; MefSession(...) also segfaulted on the full session. A gcc 15 source build first failed on incompatible pointer types; with CFLAGS="-std=gnu17 -Wno-incompatible-pointer-types" it built, but reading still crashed. MD5 hashes of all six tested files matched their S3 ETags. The planned CCEP analysis code was not run, and no neural results were produced. The package preserves the 4,479-object, 1.64 GB S3 manifest listed on 2026-10-11, planned extraction code, crash reproduction, and output. The exact OpenNeuro release represented by the live S3 listing is not established. The report recommends testing pymef on Python 3.12 or 3.13 before downloading the full dataset.

SEEG · cortico-cortical evoked potentials · MEF3 · pymef · OpenNeuro · segmentation fault · data decoding

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