运行代码： import scipy.io import mne from mne.bem import make_watershed_bem import random import string # Load .mat files inner_skull = scipy.io.loadmat('E:\MATLABproject\data\MRI\Visit1_040318\\tess_mri_COR_MPRAGE_RECON-mocoMEMPRAGE_FOV_220-298665.inner_skull.mat') outer_skull = scipy.io.loadmat('E:\MATLABproject\data\MRI\Visit1_040318\\tess_mri_COR_MPRAGE_RECON-mocoMEMPRAGE_FOV_220-298665.outer_skull.mat') scalp = scipy.io.loadmat('E:\MATLABproject\data\MRI\Visit1_040318\\tess_mri_COR_MPRAGE_RECON-mocoMEMPRAGE_FOV_220-298665.scalp.mat') print(inner_skull.keys()) # Assuming these .mat files contain triangulated surfaces, we will extract vertices and triangles # This might need adjustment based on the actual structure of your .mat files inner_skull_vertices = inner_skull['Vertices'] inner_skull_triangles = inner_skull['Faces'] outer_skull_vertices = outer_skull['Vertices'] outer_skull_triangles = outer_skull['Faces'] scalp_vertices = scalp['Vertices'] scalp_triangles = scalp['Faces'] subjects_dir = 'E:\MATLABproject\data\MRI\Visit1_040318' subject = ''.join(random.choices(string.ascii_uppercase + string.ascii_lowercase, k=8)) # Prepare surfaces for MNE # Prepare surfaces for MNE surfs = [ mne.make_bem_model(inner_skull_vertices, inner_skull_triangles, conductivity=[0.01], subjects_dir=subjects_dir), # brain mne.make_bem_model(outer_skull_vertices, outer_skull_triangles, conductivity=[0.016], subjects_dir=subjects_dir), # skull mne.make_bem_model(scalp_vertices, scalp_triangles, conductivity=[0.33], subjects_dir=subjects_dir), # skin ] # Create BEM solution model = make_watershed_bem(surfs) solution = mne.make_bem_solution(model) 时报错： Traceback (most recent call last): File "E:\pythonProject\MEG\头模型.py", line 30, in <module> mne.make_bem_model(inner_skull_vertices, inner_skull_triangles, conductivity=[0.01], subjects_dir=subjects_dir), # brain File "<decorator-gen-68>", line 12, in make_bem_model File "E:\anaconda\envs\pythonProject\lib\site-packages\mne\bem.py", line 712, in make_bem_model subject_dir = op.join(subjects_dir, subject) File "E:\anaconda\envs\pythonProject\lib\ntpath.py", line 117, in join genericpath._check_arg_types('join', path, *paths) File "E:\anaconda\envs\pythonProject\lib\genericpath.py", line 152, in _check_arg_types raise TypeError(f'{funcname}() argument must be str, bytes, or ' TypeError: join() argument must be str, bytes, or os.PathLike object, not 'ndarray' 进程已结束,退出代码1

根据错误信息显示，`join()` 函数要求的参数必须是字符串、字节或 os.PathLike 对象，但你传递的是一个 ndarray 对象。

这个问题可能是因为 `subjects_dir` 参数的值不正确。请确保你在调用 `mne.make_bem_model` 函数时传递了正确的 `subjects_dir` 参数。

另外，你在代码中随机生成了一个 `subject` 变量，但它没有在 `mne.make_bem_model` 函数中使用。如果你希望将随机生成的 `subject` 作为参数传递给函数，你需要修改相应的代码。

例如：

import os

# ...

subject = ''.join(random.choices(string.ascii_uppercase + string.ascii_lowercase, k=8))
subjects_dir = 'E:\MATLABproject\data\MRI\Visit1_040318'

# Prepare surfaces for MNE
surfs = [
    mne.make_bem_model(inner_skull_vertices, inner_skull_triangles, conductivity=[0.01], subject=subject, subjects_dir=subjects_dir),  # brain
    mne.make_bem_model(outer_skull_vertices, outer_skull_triangles, conductivity=[0.016], subject=subject, subjects_dir=subjects_dir),  # skull
    mne.make_bem_model(scalp_vertices, scalp_triangles, conductivity=[0.33], subject=subject, subjects_dir=subjects_dir),  # skin
]

# ...

在这个示例中，我假设你的 `subjects_dir` 是 `'E:\MATLABproject\data\MRI\Visit1_040318'`，并将随机生成的 `subject` 作为参数传递给 `mne.make_bem_model` 函数。请根据你的实际情况修改 `subjects_dir` 的值。

希望这次能解决你的问题！如果还有其他疑问，请随时提问。