BUG: Gaps in neuralynx not handled properly

[larsoner]

The low-level read_neuralynx_ncs function detects the presence of gaps in the .ncs file and issues a warning.

It sounds like mne.io.read_raw_neuralynx() should minimally check for temporal gaps between neo segments and issue a warning? For example, it should check that each neo.Segment[i] object starts when the neo.Segment[i-1] ended and raise a warning if this is not the case (i.e. there's temporal gap, assuming the information in neo is accurate)? And potentially also reconstruct/fill/mark missing samples such that the time axis (i.e. raw.times) is continuous and valid.

If this is on track, happy to open a separate issue and work on this.

Originally posted by @KristijanArmeni in https://github.com/mne-tools/mne-python/issues/11969#issuecomment-1832082578