diff --git a/mne/io/meas_info.py b/mne/io/meas_info.py
index 6e850b71a..b55a983b6 100644
--- a/mne/io/meas_info.py
+++ b/mne/io/meas_info.py
@@ -31,7 +31,7 @@ from ..externals.six import b, BytesIO, string_types, text_type
 
 
 _kind_dict = dict(
-    eeg=(FIFF.FIFFV_EEG_CH, FIFF.FIFFV_COIL_NONE, FIFF.FIFF_UNIT_V),
+    eeg=(FIFF.FIFFV_EEG_CH, FIFF.FIFFV_COIL_EEG, FIFF.FIFF_UNIT_V),
     mag=(FIFF.FIFFV_MEG_CH, FIFF.FIFFV_COIL_VV_MAG_T3, FIFF.FIFF_UNIT_T),
     grad=(FIFF.FIFFV_MEG_CH, FIFF.FIFFV_COIL_VV_PLANAR_T1, FIFF.FIFF_UNIT_T_M),
     misc=(FIFF.FIFFV_MISC_CH, FIFF.FIFFV_COIL_NONE, FIFF.FIFF_UNIT_NONE),

Initialise coil types
How to initialize coil types in info object?

```
chans = mne.channels.read_montage('BrainAmpMRIPlus_32sfp', ch_names=None, path= datapath, unit='mm', transform=False)

chanNames = chans.ch_names
info = mne.create_info(chanNames, 250.0, ch_types='eeg')
layout = mne.channels.find_layout(info, ch_type='eeg', exclude=None)

eventOnset = np.array(range(1,41))*2
eventZero = np.ones(40)
eventId = np.ones(40)
events = np.transpose(np.vstack((eventOnset, eventZero, eventId)))

epochs = mne.EpochsArray(cueLtemp, info, events, tmin=0, event_id=None, reject=None, flat=None, reject_tmin=None, reject_tmax=None, verbose=None)

epochs.set_montage(chans)

epochs.plot_projs_topomap(ch_type='eeg', layout=layout)
```

I get RuntimeError: No EEG channels present. Cannot find EEG layout. when I run mne.channels.find_layout()
If I use create_info with ch_types = 'eeg' shouldn't the coil type be eeg also? what exactly is the coil type and coil trans anyway? Should they be initialised?
Since I am learning mne is all this stuff explained somewhere or is this the only place I can ask questions? I went through the examples and they all use standard data sets. I am coming from matlab and my data is preprocessed in matlab.
Thanks for helping me out guys
diff --git a/mne/io/tests/test_meas_info.py b/mne/io/tests/test_meas_info.py
index 7668f36dd..588ac65a1 100644
--- a/mne/io/tests/test_meas_info.py
+++ b/mne/io/tests/test_meas_info.py
@@ -24,6 +24,15 @@ hsp_fname = op.join(data_dir, 'test_hsp.txt')
 elp_fname = op.join(data_dir, 'test_elp.txt')
 
 
+def test_make_info():
+    """Test some create_info properties
+    """
+    n_ch = 1
+    info = create_info(n_ch, 1000., 'eeg')
+    coil_types = set([ch['coil_type'] for ch in info['chs']])
+    assert_true(FIFF.FIFFV_COIL_EEG in coil_types)
+
+
 def test_fiducials_io():
     """Test fiducials i/o"""
     tempdir = _TempDir()

pip install -e .[dev]
parse_log_pytest
requirements.txt
numpy>=1.16.0 pandas>=1.0.0 scikit-learn h5py pysurfer nose nose-timer pytest
apt-get update apt-get install -y gcc
3.7
requirements/base.txt
pytest --no-header -rA --tb=line --color=no -p no:cacheprovider -W ignore::DeprecationWarning
apptools==5.2.1
certifi @ file:///croot/certifi_1671487769961/work/certifi
configobj==5.0.9
cycler==0.11.0
envisage==7.0.3
exceptiongroup==1.2.2
fonttools==4.38.0
h5py==3.8.0
importlib-metadata==6.7.0
importlib-resources==5.12.0
iniconfig==2.0.0
joblib==1.3.2
kiwisolver==1.4.5
matplotlib==3.5.3
mayavi==4.8.1
-e git+https://github.com/mne-tools/mne-python.git@1164d58d954f4dae9266b551d9d3efb979c3f597#egg=mne
nibabel==4.0.2
nose==1.3.7
nose-timer==1.0.1
numpy==1.21.6
packaging==24.0
pandas==1.3.5
Pillow==9.5.0
pluggy==1.2.0
pyface==8.0.0
Pygments==2.17.2
pyparsing==3.1.4
pysurfer==0.11.2
pytest==7.4.4
python-dateutil==2.9.0.post0
pytz==2025.2
scikit-learn==1.0.2
scipy==1.7.3
six==1.17.0
threadpoolctl==3.1.0
tomli==2.0.1
traits==6.4.3
traitsui==8.0.0
typing_extensions==4.7.1
vtk==9.3.1
zipp==3.15.0

name: mne-python
channels:
  - defaults
  - https://repo.anaconda.com/pkgs/main
  - https://repo.anaconda.com/pkgs/r
  - conda-forge
dependencies:
  - _libgcc_mutex=0.1=main
  - _openmp_mutex=5.1=1_gnu
  - ca-certificates=2025.2.25=h06a4308_0
  - certifi=2022.12.7=py37h06a4308_0
  - ld_impl_linux-64=2.40=h12ee557_0
  - libffi=3.4.4=h6a678d5_1
  - libgcc-ng=11.2.0=h1234567_1
  - libgomp=11.2.0=h1234567_1
  - libstdcxx-ng=11.2.0=h1234567_1
  - ncurses=6.4=h6a678d5_0
  - openssl=1.1.1w=h7f8727e_0
  - pip=22.3.1=py37h06a4308_0
  - python=3.7.16=h7a1cb2a_0
  - readline=8.2=h5eee18b_0
  - setuptools=65.6.3=py37h06a4308_0
  - sqlite=3.45.3=h5eee18b_0
  - tk=8.6.14=h39e8969_0
  - wheel=0.38.4=py37h06a4308_0
  - xz=5.6.4=h5eee18b_1
  - zlib=1.2.13=h5eee18b_1
  - pip:
      - apptools==5.2.1
      - configobj==5.0.9
      - cycler==0.11.0
      - envisage==7.0.3
      - exceptiongroup==1.2.2
      - fonttools==4.38.0
      - h5py==3.8.0
      - importlib-metadata==6.7.0
      - importlib-resources==5.12.0
      - iniconfig==2.0.0
      - joblib==1.3.2
      - kiwisolver==1.4.5
      - matplotlib==3.5.3
      - mayavi==4.8.1
      - nibabel==4.0.2
      - nose==1.3.7
      - nose-timer==1.0.1
      - numpy==1.21.6
      - packaging==24.0
      - pandas==1.3.5
      - pillow==9.5.0
      - pluggy==1.2.0
      - pyface==8.0.0
      - pygments==2.17.2
      - pyparsing==3.1.4
      - pysurfer==0.11.2
      - pytest==7.4.4
      - python-dateutil==2.9.0.post0
      - pytz==2025.2
      - scikit-learn==1.0.2
      - scipy==1.7.3
      - six==1.17.0
      - threadpoolctl==3.1.0
      - tomli==2.0.1
      - traits==6.4.3
      - traitsui==8.0.0
      - typing-extensions==4.7.1
      - vtk==9.3.1
      - zipp==3.15.0
prefix: /opt/conda/envs/mne-python

mne/io/tests/test_meas_info.py::test_make_info
mne/io/tests/test_meas_info.py::test_fiducials_io mne/io/tests/test_meas_info.py::test_info mne/io/tests/test_meas_info.py::test_read_write_info mne/io/tests/test_meas_info.py::test_io_dig_points mne/io/tests/test_meas_info.py::test_make_dig_points
mne/io/meas_info.py
mne/io/meas_info.py