Description of the problem

read_raw_neuralynx() data loading fails when 1 (non-initial) channel is picked prior to calling raw.load_data().

This is because AnalogSignalGap.load(), which loads zero-arrays representing data gaps, indexes along channel axis in self.signal with idx. But this is not needed since self.signal is constructed based on the size of idx variable. indexing with slice(1, 2) on a 1-dimensional array yields a 0-dim array along channel axis which breaks concatenation with real data.

PR: #12357

Steps to reproduce

from mne.io import read_raw_neuralynx
from mne.datasets.testing import data_path

testing_path = data_path(download=False) / "neuralynx"
exclude = ['LAHC1.ncs', 'LAHC2.ncs', 'LAHC3.ncs', 'xAIR1.ncs', 'xEKG1.ncs', 'LAHCu1.ncs'] # ignore channels with no gaps

raw = read_raw_neuralynx(testing_path, preload=False, exclude_fname_patterns=exclude) # channel names: ['LACH1', 'LAHC2']
raw.pick(picks="LAHC2")
raw.load_data()

Link to data

No response

Expected results

Loads the data and returns raw instance.

Actual results

np.concatenate() in l. 353 of neuralynx.py will yield dimension-mismatch error along channel dimension (real data arrays will be 1-dimensional and zero-arrays will be 0-dimensional).

Additional information

Platform Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
Python 3.11.6 | packaged by conda-forge | (main, Oct 3 2023, 10:40:35) [GCC 12.3.0]
Executable /home/kriarm/miniconda3/envs/mnedev/bin/python3.11
CPU x86_64 (20 cores)
Memory 31.2 GB

Core
├☒ mne 1.6.0.dev163+g7ff8c586e (outdated, release 1.6.0 is available!)
├☑ numpy 1.24.4 (OpenBLAS 0.3.24 with 20 threads)
├☑ scipy 1.11.3
├☑ matplotlib 3.8.0 (backend=agg)
├☑ pooch 1.8.0
└☑ jinja2 3.1.2

Numerical (optional)
├☑ sklearn 1.3.2
├☑ numba 0.57.1
├☑ nibabel 5.1.0
├☑ nilearn 0.10.2
├☑ dipy 1.7.0
├☑ openmeeg 2.5.6
├☑ pandas 2.1.2
└☐ unavailable cupy

Visualization (optional)
├☑ pyvista 0.42.3 (OpenGL unavailable)
├☑ pyvistaqt 0.0.0
├☑ vtk 9.2.6
├☑ qtpy 2.4.1 (None=None)
├☑ ipympl 0.9.3
├☑ pyqtgraph 0.13.3
├☑ mne-qt-browser 0.6.0
├☑ ipywidgets 8.1.1
├☑ trame_client 2.12.6
├☑ trame_server 2.12.1
├☑ trame_vtk 2.5.9
└☑ trame_vuetify 2.3.1

Ecosystem (optional)
├☑ mne-bids 0.14.dev0
├☑ mne-connectivity 0.6.0dev0
├☑ neo 0.12.0
└☐ unavailable mne-nirs, mne-features, mne-icalabel, mne-bids-pipeline