Compare image and coordinate based meta-analyses

Run IBMAs and CBMAs on a toy dataset, then compare the results qualitatively.

Collection of NIDM-Results packs downloaded from Neurovault collection 1425, uploaded by Dr. Camille Maumet.

import os

import pandas as pd
from nilearn.plotting import plot_stat_map

from nimare.dataset import Dataset
from nimare.extract import download_nidm_pain
from nimare.meta.cbma import ALE
from nimare.meta.ibma import DerSimonianLaird
from nimare.transforms import ImagesToCoordinates, ImageTransformer
from nimare.utils import get_resource_path

Download data

dset_dir = download_nidm_pain()

Load Dataset

dset_file = os.path.join(get_resource_path(), "nidm_pain_dset.json")
dset = Dataset(dset_file)
dset.update_path(dset_dir)

# Calculate missing statistical images from the available stats.
xformer = ImageTransformer(target=["varcope"])
dset = xformer.transform(dset)

# create coordinates from statistical maps
coord_gen = ImagesToCoordinates(merge_strategy="fill")
dset = coord_gen.transform(dset)

Out:

/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(
/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/maskers/nifti_masker.py:108: UserWarning: imgs are being resampled to the mask_img resolution. This process is memory intensive. You might want to provide a target_affine that is equal to the affine of the imgs or resample the mask beforehand to save memory and computation time.
  warnings.warn(

ALE (CBMA)

meta_cbma = ALE()
cbma_results = meta_cbma.fit(dset)
plot_stat_map(
    cbma_results.get_map("z"),
    cut_coords=[0, 0, -8],
    draw_cross=False,
    cmap="RdBu_r",
)

Out:

<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f9b62341880>

DerSimonian-Laird (IBMA)

We must resample the image data to the same MNI template as the Dataset.

meta_ibma = DerSimonianLaird(resample=True)
ibma_results = meta_ibma.fit(dset)
plot_stat_map(
    ibma_results.get_map("z"),
    cut_coords=[0, 0, -8],
    draw_cross=False,
    cmap="RdBu_r",
)

Out:

/home/docs/checkouts/readthedocs.org/user_builds/nimare/envs/0.2.0/lib/python3.8/site-packages/nilearn/_utils/niimg.py:61: UserWarning: Non-finite values detected. These values will be replaced with zeros.
  warn(

<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f9b6203c4c0>

Compare CBMA and IBMA Z-maps

stat_df = pd.DataFrame(
    {
        "CBMA": cbma_results.get_map("z", return_type="array"),
        "IBMA": ibma_results.get_map("z", return_type="array"),
    }
)
print(stat_df.corr())

Out:

          CBMA      IBMA
CBMA  1.000000  0.443177
IBMA  0.443177  1.000000