prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  [DOC] Minor discrepancy in comparing means example
  ### Is there an existing issue for this?
  
  - [X] I have searched the existing issues
  
  ### Describe your proposed suggestion in detail.
  
  Using a movie watching dataset as an example but calling it "resting state" in several places
  
  ### List any pages that would be impacted.
  
  The "comparing means of images with `math_img`" example: https://nilearn.github.io/stable/auto_examples/06_manipulating_images/plot_compare_mean_image.html
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `examples/06_manipulating_images/plot_compare_mean_image.py`
  Content:
  ```
  1 """
  2 Comparing the means of 2 images
  3 ===============================
  4 
  5 The goal of this example is to illustrate the use of the function
  6 :func:`nilearn.image.math_img` with a list of images as input.
  7 We compare the means of 2 resting state 4D images. The mean of the images
  8 could have been computed with nilearn :func:`nilearn.image.mean_img` function.
  9 """
  10 
  11 # %%
  12 # Fetching 2 subject movie watching brain development :term:`fMRI` datasets.
  13 from nilearn import datasets
  14 
  15 dataset = datasets.fetch_development_fmri(n_subjects=2)
  16 
  17 
  18 # %%
  19 # Print basic information on the adhd subjects resting state datasets.
  20 print(f"Subject 1 resting state dataset at: {dataset.func[0]}")
  21 print(f"Subject 2 resting state dataset at: {dataset.func[1]}")
  22 
  23 
  24 # %%
  25 # Comparing the means of the 2 movie watching datasets.
  26 from nilearn import image, plotting
  27 
  28 result_img = image.math_img(
  29     "np.mean(img1, axis=-1) - np.mean(img2, axis=-1)",
  30     img1=dataset.func[0],
  31     img2=dataset.func[1],
  32 )
  33 
  34 plotting.plot_stat_map(
  35     result_img, title="Comparing means of 2 resting state 4D images."
  36 )
  37 plotting.show()
  38
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/examples/06_manipulating_images/plot_compare_mean_image.py b/examples/06_manipulating_images/plot_compare_mean_image.py
  --- a/examples/06_manipulating_images/plot_compare_mean_image.py
  +++ b/examples/06_manipulating_images/plot_compare_mean_image.py
  @@ -4,7 +4,7 @@
   
   The goal of this example is to illustrate the use of the function
   :func:`nilearn.image.math_img` with a list of images as input.
  -We compare the means of 2 resting state 4D images. The mean of the images
  +We compare the means of 2 movie watching 4D images. The mean of the images
   could have been computed with nilearn :func:`nilearn.image.mean_img` function.
   """
   
  @@ -16,9 +16,9 @@
   
   
   # %%
  -# Print basic information on the adhd subjects resting state datasets.
  -print(f"Subject 1 resting state dataset at: {dataset.func[0]}")
  -print(f"Subject 2 resting state dataset at: {dataset.func[1]}")
  +# Print file locations for both subjects.
  +print(f"Subject 1 dataset at: {dataset.func[0]}")
  +print(f"Subject 2 dataset at: {dataset.func[1]}")
   
   
   # %%
  @@ -32,6 +32,6 @@
   )
   
   plotting.plot_stat_map(
  -    result_img, title="Comparing means of 2 resting state 4D images."
  +    result_img, title="Comparing means of 2 movie watching 4D images."
   )
   plotting.show()
  
verification_info: {"golden_diff": "diff --git a/examples/06_manipulating_images/plot_compare_mean_image.py b/examples/06_manipulating_images/plot_compare_mean_image.py\n--- a/examples/06_manipulating_images/plot_compare_mean_image.py\n+++ b/examples/06_manipulating_images/plot_compare_mean_image.py\n@@ -4,7 +4,7 @@\n \n The goal of this example is to illustrate the use of the function\n :func:`nilearn.image.math_img` with a list of images as input.\n-We compare the means of 2 resting state 4D images. The mean of the images\n+We compare the means of 2 movie watching 4D images. The mean of the images\n could have been computed with nilearn :func:`nilearn.image.mean_img` function.\n \"\"\"\n \n@@ -16,9 +16,9 @@\n \n \n # %%\n-# Print basic information on the adhd subjects resting state datasets.\n-print(f\"Subject 1 resting state dataset at: {dataset.func[0]}\")\n-print(f\"Subject 2 resting state dataset at: {dataset.func[1]}\")\n+# Print file locations for both subjects.\n+print(f\"Subject 1 dataset at: {dataset.func[0]}\")\n+print(f\"Subject 2 dataset at: {dataset.func[1]}\")\n \n \n # %%\n@@ -32,6 +32,6 @@\n )\n \n plotting.plot_stat_map(\n-    result_img, title=\"Comparing means of 2 resting state 4D images.\"\n+    result_img, title=\"Comparing means of 2 movie watching 4D images.\"\n )\n plotting.show()\n", "issue": "[DOC] Minor discrepancy in comparing means example\n### Is there an existing issue for this?\n\n- [X] I have searched the existing issues\n\n### Describe your proposed suggestion in detail.\n\nUsing a movie watching dataset as an example but calling it \"resting state\" in several places\n\n### List any pages that would be impacted.\n\nThe \"comparing means of images with `math_img`\" example: https://nilearn.github.io/stable/auto_examples/06_manipulating_images/plot_compare_mean_image.html\n", "before_files": [{"content": "\"\"\"\nComparing the means of 2 images\n===============================\n\nThe goal of this example is to illustrate the use of the function\n:func:`nilearn.image.math_img` with a list of images as input.\nWe compare the means of 2 resting state 4D images. The mean of the images\ncould have been computed with nilearn :func:`nilearn.image.mean_img` function.\n\"\"\"\n\n# %%\n# Fetching 2 subject movie watching brain development :term:`fMRI` datasets.\nfrom nilearn import datasets\n\ndataset = datasets.fetch_development_fmri(n_subjects=2)\n\n\n# %%\n# Print basic information on the adhd subjects resting state datasets.\nprint(f\"Subject 1 resting state dataset at: {dataset.func[0]}\")\nprint(f\"Subject 2 resting state dataset at: {dataset.func[1]}\")\n\n\n# %%\n# Comparing the means of the 2 movie watching datasets.\nfrom nilearn import image, plotting\n\nresult_img = image.math_img(\n    \"np.mean(img1, axis=-1) - np.mean(img2, axis=-1)\",\n    img1=dataset.func[0],\n    img2=dataset.func[1],\n)\n\nplotting.plot_stat_map(\n    result_img, title=\"Comparing means of 2 resting state 4D images.\"\n)\nplotting.show()\n", "path": "examples/06_manipulating_images/plot_compare_mean_image.py"}], "after_files": [{"content": "\"\"\"\nComparing the means of 2 images\n===============================\n\nThe goal of this example is to illustrate the use of the function\n:func:`nilearn.image.math_img` with a list of images as input.\nWe compare the means of 2 movie watching 4D images. The mean of the images\ncould have been computed with nilearn :func:`nilearn.image.mean_img` function.\n\"\"\"\n\n# %%\n# Fetching 2 subject movie watching brain development :term:`fMRI` datasets.\nfrom nilearn import datasets\n\ndataset = datasets.fetch_development_fmri(n_subjects=2)\n\n\n# %%\n# Print file locations for both subjects.\nprint(f\"Subject 1 dataset at: {dataset.func[0]}\")\nprint(f\"Subject 2 dataset at: {dataset.func[1]}\")\n\n\n# %%\n# Comparing the means of the 2 movie watching datasets.\nfrom nilearn import image, plotting\n\nresult_img = image.math_img(\n    \"np.mean(img1, axis=-1) - np.mean(img2, axis=-1)\",\n    img1=dataset.func[0],\n    img2=dataset.func[1],\n)\n\nplotting.plot_stat_map(\n    result_img, title=\"Comparing means of 2 movie watching 4D images.\"\n)\nplotting.show()\n", "path": "examples/06_manipulating_images/plot_compare_mean_image.py"}]}